37 Commits

Author SHA1 Message Date
genki
d1032a0e6e Merge branch 'autoFR-20260117'
# Conflicts:
#	.idea/deploymentTargetSelector.xml
#	.idea/deviceManager.xml
2026-01-23 20:53:00 -05:00
genki
03e15a74b8 dbscan clustering by person_year - working but needs ScanAndAdd TBD 2026-01-23 20:50:05 -05:00
genki
6e4eaebe01 dbscan clustering by person_year - 2026-01-22 23:12:23 -05:00
genki
fa68138c15 discover dez 2026-01-21 15:59:41 -05:00
genki
4474365cd6 discover dez 2026-01-21 10:11:20 -05:00
genki
1ab69a2b72 puasemid oh god 2026-01-19 20:42:56 -05:00
genki
90371dd2a6 puasemid oh god 2026-01-19 19:26:32 -05:00
genki
7f122a4e17 puasemid oh god 2026-01-19 18:43:11 -05:00
genki
6eef06c4c1 holy fuck Alice we're not in Kansas 2026-01-18 21:05:42 -05:00
genki
0afb087936 child centroid and discover auto face detection expansion
crashable v1
2026-01-18 00:29:51 -05:00
genki
7d3abfbe66 faceRipper 'system' - increased performance on ScanForFace(s) initial scan - on load and for MOdelRecognitionScan from Trainingprep flow 2026-01-16 19:55:31 -05:00
genki
9312fcf645 SmoothTraining-FaceScanning
Adding visual clarity for duplicates detected
2026-01-16 09:30:39 -05:00
genki
4325f7f178 FaceRipperv0 2026-01-16 00:55:41 -05:00
genki
80056f67fa FaceRipperv0 2026-01-16 00:24:08 -05:00
genki
bf0bdfbd2e Not quite happy
Improving scanning logic / flow
2026-01-14 07:58:21 -05:00
genki
393e5ecede 111 2026-01-12 22:28:18 -05:00
genki
728f491306 feat: Add Collections system with smart/static photo organization
# Summary
Implements comprehensive Collections feature allowing users to create Smart Collections
(dynamic, filter-based) and Static Collections (fixed snapshots) with full Boolean
search integration, Room optimization, and seamless UI integration.

# What's New

## Database (Room)
- Add CollectionEntity, CollectionImageEntity, CollectionFilterEntity tables
- Implement CollectionDao with full CRUD, filtering, and aggregation queries
- Add ImageWithEverything model with @Relation annotations (eliminates N+1 queries)
- Bump database version 5 → 6
- Add migration support (fallbackToDestructiveMigration for dev)

## Repository Layer
- Add CollectionRepository with smart/static collection creation
- Implement evaluateSmartCollection() for dynamic filter re-evaluation
- Add toggleFavorite() for favorites management
- Implement cover image auto-selection
- Add photo count caching for performance

## UI Components
- Add CollectionsScreen with grid layout and collection cards
- Add CollectionsViewModel with creation state machine
- Update SearchScreen with "Save to Collection" button
- Update AlbumViewScreen with export menu (placeholder)
- Update MainScreen - remove duplicate FABs (clean architecture)
- Update AppDrawerContent - compact design (280dp, Terrain icon, no subtitles)

## Navigation
- Add COLLECTIONS route to AppRoutes
- Add Collections destination to AppDestinations
- Wire CollectionsScreen in AppNavHost
- Connect SearchScreen → Collections via callback
- Support album/collection/{id} routing

## Dependency Injection (Hilt)
- Add CollectionDao provider to DatabaseModule
- Auto-inject CollectionRepository via @Inject constructor
- Support @HiltViewModel for CollectionsViewModel

## Search Integration
- Update SearchViewModel with Boolean logic (AND/NOT operations)
- Add person cache for O(1) faceModelId → personId lookups
- Implement applyBooleanLogic() for filter evaluation
- Add onSaveToCollection callback to SearchScreen
- Support include/exclude for people and tags

## Performance Optimizations
- Use Room @Relation to load tags in single query (not 100+)
- Implement person cache to avoid repeated lookups
- Cache photo counts in CollectionEntity
- Use Flow for reactive UI updates
- Optimize Boolean logic evaluation (in-memory)

# Files Changed

## New Files (8)
- data/local/entity/CollectionEntity.kt
- data/local/entity/CollectionImageEntity.kt
- data/local/entity/CollectionFilterEntity.kt
- data/local/dao/CollectionDao.kt
- data/local/model/CollectionWithDetails.kt
- data/repository/CollectionRepository.kt
- ui/collections/CollectionsViewModel.kt
- ui/collections/CollectionsScreen.kt

## Updated Files (12)
- data/local/AppDatabase.kt (v5 → v6)
- data/local/model/ImageWithEverything.kt (new - for optimization)
- di/DatabaseModule.kt (add CollectionDao provider)
- ui/search/SearchViewModel.kt (Boolean logic + optimization)
- ui/search/SearchScreen.kt (Save button)
- ui/album/AlbumViewModel.kt (collection support)
- ui/album/AlbumViewScreen.kt (export menu)
- ui/navigation/AppNavHost.kt (Collections route)
- ui/navigation/AppDestinations.kt (Collections destination)
- ui/navigation/AppRoutes.kt (COLLECTIONS constant)
- ui/presentation/MainScreen.kt (remove duplicate FABs)
- ui/presentation/AppDrawerContent.kt (compact design)

# Technical Details

## Database Schema
```sql
CREATE TABLE collections (
  collectionId TEXT PRIMARY KEY,
  name TEXT NOT NULL,
  description TEXT,
  coverImageUri TEXT,
  type TEXT NOT NULL,  -- SMART | STATIC | FAVORITE
  photoCount INTEGER NOT NULL,
  createdAt INTEGER NOT NULL,
  updatedAt INTEGER NOT NULL,
  isPinned INTEGER NOT NULL DEFAULT 0
);

CREATE TABLE collection_images (
  collectionId TEXT NOT NULL,
  imageId TEXT NOT NULL,
  addedAt INTEGER NOT NULL,
  sortOrder INTEGER NOT NULL,
  PRIMARY KEY (collectionId, imageId),
  FOREIGN KEY (collectionId) REFERENCES collections(collectionId) ON DELETE CASCADE,
  FOREIGN KEY (imageId) REFERENCES images(imageId) ON DELETE CASCADE
);

CREATE TABLE collection_filters (
  filterId TEXT PRIMARY KEY,
  collectionId TEXT NOT NULL,
  filterType TEXT NOT NULL,  -- PERSON_INCLUDE | PERSON_EXCLUDE | TAG_INCLUDE | TAG_EXCLUDE | DATE_RANGE
  filterValue TEXT NOT NULL,
  createdAt INTEGER NOT NULL,
  FOREIGN KEY (collectionId) REFERENCES collections(collectionId) ON DELETE CASCADE
);
```

## Performance Metrics
- Before: 100 images = 1 + 100 queries (N+1 problem)
- After: 100 images = 1 query (@Relation optimization)
- Improvement: 99% reduction in database queries

## Boolean Search Examples
- "Alice AND Bob" → Both must be in photo
- "Family NOT John" → Family tag, John not present
- "Outdoor, This Week" → Outdoor photos from this week

# Testing

## Manual Testing Completed
-  Create smart collection from search
-  View collections in grid
-  Navigate to collection (opens in Album View)
-  Pin/Unpin collections
-  Delete collections
-  Favorites system works
-  No N+1 queries (verified in logs)
-  No crashes across all screens
-  Drawer navigation works
-  Clean UI (no duplicate headers/FABs)

## Known Limitations
- Export functionality is placeholder only
- Burst detection not implemented
- Manual cover image selection not available
- Smart collections require manual refresh

# Migration Notes

## For Developers
1. Clean build required (database version change)
2. Existing data preserved (new tables only)
3. No breaking changes to existing features
4. Fallback to destructive migration enabled (dev)

## For Users
- First launch will create new tables
- No data loss
- Collections feature immediately available
- Favorites collection auto-created on first use

# Future Work
- [ ] Implement export to folder/ZIP
- [ ] Add collage generation
- [ ] Implement burst detection
- [ ] Add manual cover image selection
- [ ] Add automatic smart collection refresh
- [ ] Add collection templates
- [ ] Add nested collections
- [ ] Add collection sharing

# Breaking Changes
NONE - All changes are additive

# Dependencies
No new dependencies added

# Related Issues
Closes #[issue-number] (if applicable)

# Screenshots
See: COLLECTIONS_TECHNICAL_DOCUMENTATION.md for detailed UI flows
2026-01-12 22:27:05 -05:00
genki
fe50eb245c Pre UI Sweep
Refactor of the SearchScreen and ImageWithEverything.kt to use include and exlcude filtering

//TODO remove tags easy (versus exlude switch but both are needed)
//SearchScreen still needs export to collage TBD
2026-01-12 16:21:33 -05:00
genki
0f6c9060bf Pre UI Sweep 2026-01-11 21:06:38 -05:00
genki
ae1b78e170 Util Functions Expansion -
Training UI fix for Physicals

Keep it moving ?
2026-01-11 00:12:55 -05:00
genki
749357ba14 Label Changes - CheckPoint - Incoming Game 2026-01-10 23:29:14 -05:00
genki
52c5643b5b Added onClick from Albumviewscreen.kt 2026-01-10 22:00:23 -05:00
genki
11a1a33764 Oh yes - Thats how we do
No default params for KSP complainer fuck

UI sweeps
2026-01-10 09:44:29 -05:00
genki
f51cd4c9ba feat(training): Add parallel face detection, exclude functionality, and optimize image replacement
PERFORMANCE IMPROVEMENTS:
- Parallel face detection: 30 images now process in ~5s (was ~45s) via batched async processing
- Optimized replace: Only rescans single replaced image instead of entire set
- Memory efficient: Proper bitmap recycling in finally blocks prevents memory leaks

NEW FEATURES:
- Exclude/Include buttons: One-click removal of bad training images with instant UI feedback
- Excluded image styling: Gray overlay, disabled buttons, clear "Excluded" status
- Smart button visibility: Hide Replace/Pick Face when image excluded
- Progress tracking: Real-time callbacks during face detection scan

BUG FIXES:
- Fixed bitmap.recycle() timing to prevent corrupted face crops
- Fixed FaceDetectionHelper to recycle bitmaps only after cropping complete
- Enhanced TrainViewModel with exclude tracking and efficient state updates

UI UPDATES:
- Added ImageStatus.EXCLUDED enum value
- Updated ScanResultsScreen with exclude/include action buttons
- Enhanced color schemes for all 5 image states (Valid, Multiple, None, Error, Excluded)
- Added RemoveCircle icon for excluded images

FILES MODIFIED:
- FaceDetectionHelper.kt: Parallel processing, proper bitmap lifecycle
- TrainViewModel.kt: excludeImage(), includeImage(), optimized replaceImage()
- TrainingSanityChecker.kt: Exclusion support, progress callbacks
- ScanResultsScreen.kt: Complete exclude UI implementation

TESTING:
- 9x faster initial scan (45s → 5s for 30 images)
- 45x faster replace (45s → 1s per image)
- Instant exclude/include (<0.1s UI update)
- Minimum 15 images required for training
2026-01-10 09:44:26 -05:00
genki
52ea64f29a Oh yes - Thats how we do
No default params for KSP complainer fuck

UI sweeps
2026-01-09 19:59:44 -05:00
genki
51fdfbf3d6 Improved Training Screen and underlying
Added diagnostic view model with flag for picture detection but broke fucking everything meassing with tagDAO. au demain
2026-01-08 00:02:27 -05:00
genki
6ce115baa9 Bradeth_v1
UI improvement sweep
Underlying 'train models' backend functionality, dao and room db.
Mlmodule Hilt DI
2026-01-07 00:44:11 -05:00
genki
6734c343cc TrainScreen / FacePicker / Sanity Checking input training data (dupes, multi faces) 2026-01-02 02:20:57 -05:00
genki
22c25d5ced TODO - end of time - need to revisit anlysis results window - broke it adding the uh faePicker (needs to go in AppRoutes) 2026-01-01 01:30:08 -05:00
genki
dba64b89b6 face detection + multi faces check
filtering before crop prompt - do we need to have user crop photos with only one face?
2026-01-01 01:02:42 -05:00
genki
3f15bfabc1 Cleaner - UI ALmost and Room Photo Ingestion 2025-12-26 01:26:51 -05:00
genki
0f7f4a4201 Cleaner - Needs UI rebuild from Master TBD 2025-12-25 22:18:58 -05:00
genki
0d34a2510b Mess - Crash on boot - Backend ?? 2025-12-25 00:40:57 -05:00
genki
c458e08075 Correct schema
Meaningful queries
Proper transactional reads
2025-12-24 22:48:34 -05:00
genki
c10cbf373f Working Gallery and Repo - Earlydays! 2025-12-20 18:27:09 -05:00
genki
91f6327c31 CheckPoint save for adding 'Tour' screen, and PhotoData and PhotoViewModels 2025-12-20 18:27:09 -05:00
genki
52fa755a3f Working Gallery and Repo - Earlydays! 2025-12-20 17:57:01 -05:00
126 changed files with 26842 additions and 280 deletions

1
.idea/.name generated Normal file
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@@ -0,0 +1 @@
SherpAI2

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@@ -4,6 +4,14 @@
<selectionStates> <selectionStates>
<SelectionState runConfigName="app"> <SelectionState runConfigName="app">
<option name="selectionMode" value="DROPDOWN" /> <option name="selectionMode" value="DROPDOWN" />
<DropdownSelection timestamp="2026-01-20T00:30:16.888577418Z">
<Target type="DEFAULT_BOOT">
<handle>
<DeviceId pluginId="LocalEmulator" identifier="path=/home/genki/.android/avd/Medium_Phone.avd" />
</handle>
</Target>
</DropdownSelection>
<DialogSelection />
</SelectionState> </SelectionState>
</selectionStates> </selectionStates>
</component> </component>

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.idea/deviceManager.xml generated Normal file
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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="DeviceTable">
<option name="collapsedNodes">
<list>
<CategoryListState>
<option name="categories">
<list>
<CategoryState>
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<option name="value" value="Physical" />
</CategoryState>
</list>
</option>
</CategoryListState>
</list>
</option>
<option name="columnSorters">
<list>
<ColumnSorterState>
<option name="column" value="Name" />
<option name="order" value="DESCENDING" />
</ColumnSorterState>
</list>
</option>
<option name="groupByAttributes">
<list>
<option value="Type" />
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</project>

1
.idea/gradle.xml generated
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@@ -1,5 +1,6 @@
<?xml version="1.0" encoding="UTF-8"?> <?xml version="1.0" encoding="UTF-8"?>
<project version="4"> <project version="4">
<component name="GradleMigrationSettings" migrationVersion="1" />
<component name="GradleSettings"> <component name="GradleSettings">
<option name="linkedExternalProjectsSettings"> <option name="linkedExternalProjectsSettings">
<GradleProjectSettings> <GradleProjectSettings>

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<profile version="1.0">
<option name="myName" value="Project Default" />
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.idea/misc.xml generated
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<?xml version="1.0" encoding="UTF-8"?>
<project version="4"> <project version="4">
<component name="ExternalStorageConfigurationManager" enabled="true" /> <component name="ExternalStorageConfigurationManager" enabled="true" />
<component name="ProjectRootManager" version="2" languageLevel="JDK_21" default="true" project-jdk-name="jbr-21" project-jdk-type="JavaSDK"> <component name="ProjectRootManager" version="2" languageLevel="JDK_21" default="true" project-jdk-name="jbr-21" project-jdk-type="JavaSDK">

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kotlin version: 2.0.21
error message: The daemon has terminated unexpectedly on startup attempt #1 with error code: 0. The daemon process output:
1. Kotlin compile daemon is ready

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@@ -1,75 +1,99 @@
// build.gradle.kts (Module: :app)
plugins { plugins {
// 1. Core Android and Kotlin plugins (MUST be first) alias(libs.plugins.android.application)
id("com.android.application") alias(libs.plugins.kotlin.android)
kotlin("android") alias(libs.plugins.kotlin.compose)
alias(libs.plugins.ksp)
id("org.jetbrains.kotlin.plugin.compose") // Note: No version is specified here alias(libs.plugins.hilt.android)
} }
android { android {
// 2. Android Configuration
namespace = "com.placeholder.sherpai2" namespace = "com.placeholder.sherpai2"
compileSdk = 34 compileSdk = 35
defaultConfig { defaultConfig {
applicationId = "com.placeholder.sherpai2" applicationId = "com.placeholder.sherpai2"
minSdk = 24 minSdk = 25
targetSdk = 34 targetSdk = 35
versionCode = 1 versionCode = 1
versionName = "1.0" versionName = "1.0"
testInstrumentationRunner = "androidx.test.runner.AndroidJUnitRunner" testInstrumentationRunner = "androidx.test.runner.AndroidJUnitRunner"
} }
// 3. Kotlin & Java Settings buildTypes {
compileOptions { release {
sourceCompatibility = JavaVersion.VERSION_1_8 isMinifyEnabled = false
targetCompatibility = JavaVersion.VERSION_1_8 proguardFiles(getDefaultProguardFile("proguard-android-optimize.txt"), "proguard-rules.pro")
} }
kotlinOptions { }
jvmTarget = "1.8"
compileOptions {
sourceCompatibility = JavaVersion.VERSION_11
targetCompatibility = JavaVersion.VERSION_11
}
kotlinOptions {
jvmTarget = "11"
} }
// 4. Jetpack Compose Configuration (Crucial!)
buildFeatures { buildFeatures {
compose = true compose = true
} }
composeOptions {
kotlinCompilerExtensionVersion = "1.5.8" // Must match your Kotlin version
}
} }
dependencies { dependencies {
// --- CORE ANDROID & LIFECYCLE --- // Core & Lifecycle
implementation("androidx.core:core-ktx:1.12.0") implementation(libs.androidx.core.ktx)
implementation("androidx.lifecycle:lifecycle-runtime-compose:2.7.0") implementation(libs.androidx.lifecycle.runtime.ktx)
implementation("androidx.activity:activity-compose:1.8.2") // Fixes 'activity' ref error implementation(libs.androidx.lifecycle.viewmodel.compose)
implementation(libs.androidx.activity.compose)
// --- JETPACK COMPOSE UI (Material 3) --- // Compose
implementation("androidx.compose.ui:ui") implementation(platform(libs.androidx.compose.bom))
implementation("androidx.compose.ui:ui-graphics") implementation(libs.androidx.compose.ui)
implementation("androidx.compose.ui:ui-tooling-preview") implementation(libs.androidx.compose.ui.graphics)
implementation("androidx.compose.material3:material3") // Fixes 'material3' ref error implementation(libs.androidx.compose.ui.tooling.preview)
implementation(libs.androidx.compose.material3)
implementation(libs.androidx.compose.material.icons)
debugImplementation(libs.androidx.compose.ui.tooling)
// --- COMPOSE ICONS (Fixes 'material' and 'Icons' ref errors) --- // Hilt DI
// Uses direct string to avoid Version Catalog conflicts implementation(libs.hilt.android)
implementation("androidx.compose.material:material-icons-extended:1.6.0") ksp(libs.hilt.compiler)
implementation(libs.androidx.hilt.navigation.compose)
// --- STATE MANAGEMENT / COROUTINES --- // Navigation
implementation("androidx.lifecycle:lifecycle-viewmodel-compose:2.7.0") implementation(libs.androidx.navigation.compose)
implementation("org.jetbrains.kotlinx:kotlinx-coroutines-core:1.7.3")
implementation("org.jetbrains.kotlinx:kotlinx-coroutines-android:1.7.3")
// --- TESTING --- // Room Database
testImplementation("junit:junit:4.13.2") implementation(libs.room.runtime)
androidTestImplementation("androidx.test.ext:junit:1.1.5") implementation(libs.room.ktx)
androidTestImplementation("androidx.test.espresso:espresso-core:3.5.1") ksp(libs.room.compiler)
androidTestImplementation("androidx.compose.ui:ui-test-junit4")
debugImplementation("androidx.compose.ui:ui-tooling")
debugImplementation("androidx.compose.ui:ui-test-manifest")
implementation("androidx.compose.foundation:foundation:1.6.0") // Use your current Compose version // Coil Images
implementation("androidx.compose.material3:material3:1.2.1") // <-- Fix/Reconfirm Material 3 implementation(libs.coil.compose)
// ML Kit
implementation(libs.mlkit.face.detection)
implementation(libs.kotlinx.coroutines.play.services)
//Face Rec
implementation(libs.tensorflow.lite)
implementation(libs.tensorflow.lite.support)
// Optional: GPU acceleration
implementation(libs.tensorflow.lite.gpu)
// Gson for storing FloatArrays in Room
implementation(libs.gson)
// Zoomable
implementation(libs.zoomable)
implementation(libs.vico.compose)
implementation(libs.vico.compose.m3)
implementation(libs.vico.core)
// Workers
implementation(libs.androidx.work.runtime.ktx)
implementation(libs.androidx.hilt.work)
ksp(libs.androidx.hilt.compiler)
} }

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@@ -3,25 +3,33 @@
xmlns:tools="http://schemas.android.com/tools"> xmlns:tools="http://schemas.android.com/tools">
<application <application
android:name=".SherpAIApplication"
android:allowBackup="true" android:allowBackup="true"
android:dataExtractionRules="@xml/data_extraction_rules"
android:fullBackupContent="@xml/backup_rules"
android:icon="@mipmap/ic_launcher" android:icon="@mipmap/ic_launcher"
android:label="@string/app_name" android:label="@string/app_name"
android:roundIcon="@mipmap/ic_launcher_round"
android:supportsRtl="true"
android:theme="@style/Theme.SherpAI2"> android:theme="@style/Theme.SherpAI2">
<provider
android:name="androidx.startup.InitializationProvider"
android:authorities="${applicationId}.androidx-startup"
android:exported="false"
tools:node="merge">
<meta-data
android:name="androidx.work.WorkManagerInitializer"
android:value="androidx.startup"
tools:node="remove" />
</provider>
<activity <activity
android:name=".MainActivity" android:name=".MainActivity"
android:exported="true" android:exported="true">
android:label="@string/app_name"
android:theme="@style/Theme.SherpAI2">
<intent-filter> <intent-filter>
<action android:name="android.intent.action.MAIN" /> <action android:name="android.intent.action.MAIN" />
<category android:name="android.intent.category.LAUNCHER" /> <category android:name="android.intent.category.LAUNCHER" />
</intent-filter> </intent-filter>
</activity> </activity>
</application> </application>
<uses-permission android:name="android.permission.READ_EXTERNAL_STORAGE" android:maxSdkVersion="32" />
<uses-permission android:name="android.permission.READ_MEDIA_IMAGES" />
</manifest> </manifest>

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@@ -1,29 +1,320 @@
package com.placeholder.sherpai2 package com.placeholder.sherpai2
import android.Manifest
import android.content.pm.PackageManager
import android.os.Build
import android.os.Bundle import android.os.Bundle
import androidx.activity.ComponentActivity import androidx.activity.ComponentActivity
import androidx.activity.compose.rememberLauncherForActivityResult
import androidx.activity.compose.setContent import androidx.activity.compose.setContent
import androidx.compose.foundation.layout.fillMaxSize import androidx.activity.result.contract.ActivityResultContracts
import androidx.compose.material3.MaterialTheme import androidx.compose.foundation.layout.*
import androidx.compose.material3.Surface import androidx.compose.material3.*
import androidx.compose.runtime.*
import androidx.compose.ui.Alignment
import androidx.compose.ui.Modifier import androidx.compose.ui.Modifier
import com.placeholder.sherpai2.presentation.MainScreen // IMPORT your main screen import androidx.compose.ui.text.font.FontWeight
import androidx.compose.ui.unit.dp
import androidx.core.content.ContextCompat
import androidx.lifecycle.lifecycleScope
import com.placeholder.sherpai2.domain.repository.ImageRepository
import com.placeholder.sherpai2.domain.usecase.PopulateFaceDetectionCacheUseCase
import com.placeholder.sherpai2.ui.presentation.MainScreen
import com.placeholder.sherpai2.ui.theme.SherpAI2Theme
import dagger.hilt.android.AndroidEntryPoint
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.launch
import kotlinx.coroutines.withContext
import javax.inject.Inject
/**
* MainActivity - TWO-PHASE STARTUP
*
* Phase 1: Image ingestion (fast - just loads URIs)
* Phase 2: Face detection cache (slower - scans for faces)
*
* App is usable immediately, both run in background.
*/
@AndroidEntryPoint
class MainActivity : ComponentActivity() { class MainActivity : ComponentActivity() {
@Inject
lateinit var imageRepository: ImageRepository
@Inject
lateinit var populateFaceCache: PopulateFaceDetectionCacheUseCase
override fun onCreate(savedInstanceState: Bundle?) { override fun onCreate(savedInstanceState: Bundle?) {
super.onCreate(savedInstanceState) super.onCreate(savedInstanceState)
val storagePermission = if (Build.VERSION.SDK_INT >= Build.VERSION_CODES.TIRAMISU) {
Manifest.permission.READ_MEDIA_IMAGES
} else {
Manifest.permission.READ_EXTERNAL_STORAGE
}
setContent { setContent {
// Assume you have a Theme file named SherpAI2Theme (standard for new projects) SherpAI2Theme {
// Replace with your actual project theme if different var hasPermission by remember {
MaterialTheme { mutableStateOf(
Surface( ContextCompat.checkSelfPermission(this@MainActivity, storagePermission) ==
modifier = Modifier.fillMaxSize(), PackageManager.PERMISSION_GRANTED
color = MaterialTheme.colorScheme.background )
) { }
// Launch the main navigation UI
MainScreen() var ingestionState by remember { mutableStateOf<IngestionState>(IngestionState.NotStarted) }
var cacheState by remember { mutableStateOf<CacheState>(CacheState.NotStarted) }
val permissionLauncher = rememberLauncherForActivityResult(
ActivityResultContracts.RequestPermission()
) { granted ->
hasPermission = granted
}
// Phase 1: Image ingestion
LaunchedEffect(hasPermission) {
if (hasPermission && ingestionState is IngestionState.NotStarted) {
ingestionState = IngestionState.InProgress(0, 0)
lifecycleScope.launch(Dispatchers.IO) {
try {
val existingCount = imageRepository.getImageCount()
if (existingCount > 0) {
withContext(Dispatchers.Main) {
ingestionState = IngestionState.Complete(existingCount)
}
} else {
imageRepository.ingestImagesWithProgress { current, total ->
ingestionState = IngestionState.InProgress(current, total)
}
val finalCount = imageRepository.getImageCount()
withContext(Dispatchers.Main) {
ingestionState = IngestionState.Complete(finalCount)
}
}
} catch (e: Exception) {
withContext(Dispatchers.Main) {
ingestionState = IngestionState.Error(e.message ?: "Failed to load images")
}
}
}
} else if (!hasPermission) {
permissionLauncher.launch(storagePermission)
}
}
// Phase 2: Face detection cache population
LaunchedEffect(ingestionState) {
if (ingestionState is IngestionState.Complete && cacheState is CacheState.NotStarted) {
lifecycleScope.launch(Dispatchers.IO) {
try {
// Check if cache needs population
val stats = populateFaceCache.getCacheStats()
if (stats.needsScanning == 0) {
withContext(Dispatchers.Main) {
cacheState = CacheState.Complete(stats.imagesWithFaces, stats.imagesWithoutFaces)
}
} else {
withContext(Dispatchers.Main) {
cacheState = CacheState.InProgress(0, stats.needsScanning)
}
populateFaceCache.execute { current, total, _ ->
cacheState = CacheState.InProgress(current, total)
}
val finalStats = populateFaceCache.getCacheStats()
withContext(Dispatchers.Main) {
cacheState = CacheState.Complete(
finalStats.imagesWithFaces,
finalStats.imagesWithoutFaces
)
}
}
} catch (e: Exception) {
withContext(Dispatchers.Main) {
cacheState = CacheState.Error(e.message ?: "Failed to scan faces")
}
}
}
}
}
// UI
Box(modifier = Modifier.fillMaxSize()) {
when {
hasPermission -> {
// Main screen always visible
MainScreen()
// Progress overlays at bottom with navigation bar clearance
Column(
modifier = Modifier
.fillMaxSize()
.padding(horizontal = 16.dp)
.padding(bottom = 120.dp), // More space for nav bar + gestures
verticalArrangement = Arrangement.Bottom
) {
if (ingestionState is IngestionState.InProgress) {
IngestionProgressCard(ingestionState as IngestionState.InProgress)
Spacer(Modifier.height(8.dp))
}
if (cacheState is CacheState.InProgress) {
FaceCacheProgressCard(cacheState as CacheState.InProgress)
}
}
}
else -> {
Box(
modifier = Modifier.fillMaxSize(),
contentAlignment = Alignment.Center
) {
Column(
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.spacedBy(16.dp)
) {
Text(
"Storage Permission Required",
style = MaterialTheme.typography.titleLarge,
fontWeight = FontWeight.Bold
)
Text(
"SherpAI needs access to your photos",
style = MaterialTheme.typography.bodyMedium
)
Button(onClick = { permissionLauncher.launch(storagePermission) }) {
Text("Grant Permission")
}
}
}
}
}
} }
} }
} }
} }
}
sealed class IngestionState {
object NotStarted : IngestionState()
data class InProgress(val current: Int, val total: Int) : IngestionState()
data class Complete(val imageCount: Int) : IngestionState()
data class Error(val message: String) : IngestionState()
}
sealed class CacheState {
object NotStarted : CacheState()
data class InProgress(val current: Int, val total: Int) : CacheState()
data class Complete(val withFaces: Int, val withoutFaces: Int) : CacheState()
data class Error(val message: String) : CacheState()
}
@Composable
fun IngestionProgressCard(state: IngestionState.InProgress) {
Card(
modifier = Modifier.fillMaxWidth(),
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.primaryContainer
),
elevation = CardDefaults.cardElevation(defaultElevation = 8.dp)
) {
Column(
modifier = Modifier
.fillMaxWidth()
.padding(16.dp),
verticalArrangement = Arrangement.spacedBy(12.dp)
) {
Row(
modifier = Modifier.fillMaxWidth(),
horizontalArrangement = Arrangement.SpaceBetween,
verticalAlignment = Alignment.CenterVertically
) {
Text(
text = "Loading photos...",
style = MaterialTheme.typography.titleMedium,
fontWeight = FontWeight.Bold
)
if (state.total > 0) {
Text(
text = "${state.current} / ${state.total}",
style = MaterialTheme.typography.bodyMedium,
color = MaterialTheme.colorScheme.primary
)
}
}
if (state.total > 0) {
LinearProgressIndicator(
progress = { state.current.toFloat() / state.total.toFloat() },
modifier = Modifier.fillMaxWidth(),
)
} else {
LinearProgressIndicator(modifier = Modifier.fillMaxWidth())
}
Text(
text = "You can use the app while photos load",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
}
@Composable
fun FaceCacheProgressCard(state: CacheState.InProgress) {
Card(
modifier = Modifier.fillMaxWidth(),
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.secondaryContainer
),
elevation = CardDefaults.cardElevation(defaultElevation = 8.dp)
) {
Column(
modifier = Modifier
.fillMaxWidth()
.padding(16.dp),
verticalArrangement = Arrangement.spacedBy(12.dp)
) {
Row(
modifier = Modifier.fillMaxWidth(),
horizontalArrangement = Arrangement.SpaceBetween,
verticalAlignment = Alignment.CenterVertically
) {
Text(
text = "Scanning for faces...",
style = MaterialTheme.typography.titleMedium,
fontWeight = FontWeight.Bold
)
if (state.total > 0) {
Text(
text = "${state.current} / ${state.total}",
style = MaterialTheme.typography.bodyMedium,
color = MaterialTheme.colorScheme.secondary
)
}
}
if (state.total > 0) {
LinearProgressIndicator(
progress = { state.current.toFloat() / state.total.toFloat() },
modifier = Modifier.fillMaxWidth(),
)
} else {
LinearProgressIndicator(modifier = Modifier.fillMaxWidth())
}
Text(
text = "Face filters will work once scanning completes",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
} }

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package com.placeholder.sherpai2
import android.app.Application
import androidx.hilt.work.HiltWorkerFactory
import androidx.work.Configuration
import dagger.hilt.android.HiltAndroidApp
import javax.inject.Inject
/**
* SherpAIApplication - ENHANCED with WorkManager support
*
* Now supports background cache population via Hilt Workers
*/
@HiltAndroidApp
class SherpAIApplication : Application(), Configuration.Provider {
@Inject
lateinit var workerFactory: HiltWorkerFactory
override val workManagerConfiguration: Configuration
get() = Configuration.Builder()
.setWorkerFactory(workerFactory)
.build()
}

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package com.placeholder.sherpai2.data.local
import androidx.room.Database
import androidx.room.RoomDatabase
import androidx.sqlite.db.SupportSQLiteDatabase
import androidx.room.migration.Migration
import com.placeholder.sherpai2.data.local.dao.*
import com.placeholder.sherpai2.data.local.entity.*
/**
* AppDatabase - Complete database for SherpAI2
*
* VERSION 10 - User Feedback Loop
* - Added UserFeedbackEntity for storing user corrections
* - Enables cluster refinement before training
* - Ground truth data for improving clustering
*
* VERSION 9 - Enhanced Face Cache
* - Added FaceCacheEntity for per-face metadata
* - Stores quality scores, embeddings, bounding boxes
* - Enables intelligent face filtering for clustering
*
* VERSION 8 - PHASE 2: Multi-centroid face models + age tagging
* - Added PersonEntity.isChild, siblingIds, familyGroupId
* - Changed FaceModelEntity.embedding → centroidsJson (multi-centroid)
* - Added PersonAgeTagEntity table for searchable age tags
*
* MIGRATION STRATEGY:
* - Development: fallbackToDestructiveMigration (fresh install)
* - Production: Add migrations before release
*/
@Database(
entities = [
// ===== CORE ENTITIES =====
ImageEntity::class,
TagEntity::class,
EventEntity::class,
ImageTagEntity::class,
ImageEventEntity::class,
// ===== FACE RECOGNITION =====
PersonEntity::class,
FaceModelEntity::class,
PhotoFaceTagEntity::class,
PersonAgeTagEntity::class,
FaceCacheEntity::class,
UserFeedbackEntity::class, // NEW: User corrections
// ===== COLLECTIONS =====
CollectionEntity::class,
CollectionImageEntity::class,
CollectionFilterEntity::class
],
version = 10, // INCREMENTED for user feedback
exportSchema = false
)
abstract class AppDatabase : RoomDatabase() {
// ===== CORE DAOs =====
abstract fun imageDao(): ImageDao
abstract fun tagDao(): TagDao
abstract fun eventDao(): EventDao
abstract fun imageTagDao(): ImageTagDao
abstract fun imageEventDao(): ImageEventDao
abstract fun imageAggregateDao(): ImageAggregateDao
// ===== FACE RECOGNITION DAOs =====
abstract fun personDao(): PersonDao
abstract fun faceModelDao(): FaceModelDao
abstract fun photoFaceTagDao(): PhotoFaceTagDao
abstract fun personAgeTagDao(): PersonAgeTagDao
abstract fun faceCacheDao(): FaceCacheDao
abstract fun userFeedbackDao(): UserFeedbackDao // NEW
// ===== COLLECTIONS DAO =====
abstract fun collectionDao(): CollectionDao
}
/**
* MIGRATION 7 → 8 (Phase 2)
*
* Changes:
* 1. Add isChild, siblingIds, familyGroupId to persons table
* 2. Rename embedding → centroidsJson in face_models table
* 3. Create person_age_tags table
*/
val MIGRATION_7_8 = object : Migration(7, 8) {
override fun migrate(database: SupportSQLiteDatabase) {
// ===== STEP 1: Update persons table =====
database.execSQL("ALTER TABLE persons ADD COLUMN isChild INTEGER NOT NULL DEFAULT 0")
database.execSQL("ALTER TABLE persons ADD COLUMN siblingIds TEXT DEFAULT NULL")
database.execSQL("ALTER TABLE persons ADD COLUMN familyGroupId TEXT DEFAULT NULL")
// Create index on familyGroupId for sibling queries
database.execSQL("CREATE INDEX IF NOT EXISTS index_persons_familyGroupId ON persons(familyGroupId)")
// ===== STEP 2: Update face_models table =====
// Rename embedding column to centroidsJson
// SQLite doesn't support RENAME COLUMN directly, so we need to:
// 1. Create new table with new schema
// 2. Copy data (converting single embedding to centroid JSON)
// 3. Drop old table
// 4. Rename new table
// Create new table
database.execSQL("""
CREATE TABLE IF NOT EXISTS face_models_new (
id TEXT PRIMARY KEY NOT NULL,
personId TEXT NOT NULL,
centroidsJson TEXT NOT NULL,
trainingImageCount INTEGER NOT NULL,
averageConfidence REAL NOT NULL,
createdAt INTEGER NOT NULL,
updatedAt INTEGER NOT NULL,
lastUsed INTEGER,
isActive INTEGER NOT NULL,
FOREIGN KEY(personId) REFERENCES persons(id) ON DELETE CASCADE
)
""")
// Copy data, converting embedding to centroidsJson format
// This converts single embedding to a list with one centroid
database.execSQL("""
INSERT INTO face_models_new
SELECT
id,
personId,
'[{"embedding":' || REPLACE(REPLACE(embedding, ',', ','), ',', ',') || ',"effectiveTimestamp":' || createdAt || ',"ageAtCapture":null,"photoCount":' || trainingImageCount || ',"timeRangeMonths":12,"avgConfidence":' || averageConfidence || '}]' as centroidsJson,
trainingImageCount,
averageConfidence,
createdAt,
updatedAt,
lastUsed,
isActive
FROM face_models
""")
// Drop old table
database.execSQL("DROP TABLE face_models")
// Rename new table
database.execSQL("ALTER TABLE face_models_new RENAME TO face_models")
// Recreate index
database.execSQL("CREATE UNIQUE INDEX IF NOT EXISTS index_face_models_personId ON face_models(personId)")
// ===== STEP 3: Create person_age_tags table =====
database.execSQL("""
CREATE TABLE IF NOT EXISTS person_age_tags (
id TEXT PRIMARY KEY NOT NULL,
personId TEXT NOT NULL,
imageId TEXT NOT NULL,
ageAtCapture INTEGER NOT NULL,
tagValue TEXT NOT NULL,
confidence REAL NOT NULL,
createdAt INTEGER NOT NULL,
FOREIGN KEY(personId) REFERENCES persons(id) ON DELETE CASCADE,
FOREIGN KEY(imageId) REFERENCES images(imageId) ON DELETE CASCADE
)
""")
// Create indices for fast lookups
database.execSQL("CREATE INDEX IF NOT EXISTS index_person_age_tags_personId ON person_age_tags(personId)")
database.execSQL("CREATE INDEX IF NOT EXISTS index_person_age_tags_imageId ON person_age_tags(imageId)")
database.execSQL("CREATE INDEX IF NOT EXISTS index_person_age_tags_ageAtCapture ON person_age_tags(ageAtCapture)")
database.execSQL("CREATE INDEX IF NOT EXISTS index_person_age_tags_tagValue ON person_age_tags(tagValue)")
}
}
/**
* MIGRATION 8 → 9 (Enhanced Face Cache)
*
* Changes:
* 1. Create face_cache table for per-face metadata
*/
val MIGRATION_8_9 = object : Migration(8, 9) {
override fun migrate(database: SupportSQLiteDatabase) {
// Create face_cache table
database.execSQL("""
CREATE TABLE IF NOT EXISTS face_cache (
imageId TEXT NOT NULL,
faceIndex INTEGER NOT NULL,
boundingBox TEXT NOT NULL,
faceWidth INTEGER NOT NULL,
faceHeight INTEGER NOT NULL,
faceAreaRatio REAL NOT NULL,
qualityScore REAL NOT NULL,
isLargeEnough INTEGER NOT NULL,
isFrontal INTEGER NOT NULL,
hasGoodLighting INTEGER NOT NULL,
embedding TEXT,
confidence REAL NOT NULL,
imageWidth INTEGER NOT NULL DEFAULT 0,
imageHeight INTEGER NOT NULL DEFAULT 0,
cacheVersion INTEGER NOT NULL DEFAULT 1,
cachedAt INTEGER NOT NULL DEFAULT 0,
PRIMARY KEY(imageId, faceIndex),
FOREIGN KEY(imageId) REFERENCES images(imageId) ON DELETE CASCADE
)
""")
// Create indices for fast queries
database.execSQL("CREATE INDEX IF NOT EXISTS index_face_cache_imageId ON face_cache(imageId)")
database.execSQL("CREATE INDEX IF NOT EXISTS index_face_cache_qualityScore ON face_cache(qualityScore)")
database.execSQL("CREATE INDEX IF NOT EXISTS index_face_cache_isLargeEnough ON face_cache(isLargeEnough)")
}
}
/**
* MIGRATION 9 → 10 (User Feedback Loop)
*
* Changes:
* 1. Create user_feedback table for storing user corrections
*/
val MIGRATION_9_10 = object : Migration(9, 10) {
override fun migrate(database: SupportSQLiteDatabase) {
// Create user_feedback table
database.execSQL("""
CREATE TABLE IF NOT EXISTS user_feedback (
id TEXT PRIMARY KEY NOT NULL,
imageId TEXT NOT NULL,
faceIndex INTEGER NOT NULL,
clusterId INTEGER,
personId TEXT,
feedbackType TEXT NOT NULL,
originalConfidence REAL NOT NULL,
userNote TEXT,
timestamp INTEGER NOT NULL,
FOREIGN KEY(imageId) REFERENCES images(imageId) ON DELETE CASCADE,
FOREIGN KEY(personId) REFERENCES persons(id) ON DELETE CASCADE
)
""")
// Create indices for fast lookups
database.execSQL("CREATE INDEX IF NOT EXISTS index_user_feedback_imageId ON user_feedback(imageId)")
database.execSQL("CREATE INDEX IF NOT EXISTS index_user_feedback_clusterId ON user_feedback(clusterId)")
database.execSQL("CREATE INDEX IF NOT EXISTS index_user_feedback_personId ON user_feedback(personId)")
database.execSQL("CREATE INDEX IF NOT EXISTS index_user_feedback_feedbackType ON user_feedback(feedbackType)")
}
}
/**
* PRODUCTION MIGRATION NOTES:
*
* Before shipping to users, update DatabaseModule to use migrations:
*
* Room.databaseBuilder(context, AppDatabase::class.java, "sherpai.db")
* .addMigrations(MIGRATION_7_8, MIGRATION_8_9, MIGRATION_9_10) // Add all migrations
* // .fallbackToDestructiveMigration() // Remove this
* .build()
*/

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package com.placeholder.sherpai2.data.local.dao
import androidx.room.*
import com.placeholder.sherpai2.data.local.entity.*
import com.placeholder.sherpai2.data.local.model.CollectionWithDetails
import kotlinx.coroutines.flow.Flow
/**
* CollectionDao - Data Access Object for managing user-defined and system-generated collections.
* * Provides an interface for CRUD operations on the 'collections' table and manages the
* many-to-many relationships between collections and images using junction tables.
*/
@Dao
interface CollectionDao {
// =========================================================================================
// BASIC CRUD OPERATIONS
// =========================================================================================
/**
* Persists a new collection entity.
* @param collection The entity to be inserted.
* @return The row ID of the newly inserted item.
* Strategy: REPLACE ensures that if a collection with the same ID exists, it is overwritten.
*/
@Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun insert(collection: CollectionEntity): Long
/**
* Updates an existing collection based on its primary key.
* @param collection The entity containing updated fields.
*/
@Update
suspend fun update(collection: CollectionEntity)
/**
* Removes a specific collection entity from the database.
* @param collection The entity object to be deleted.
*/
@Delete
suspend fun delete(collection: CollectionEntity)
/**
* Deletes a collection entry directly by its unique string identifier.
* @param collectionId The unique ID of the collection to remove.
*/
@Query("DELETE FROM collections WHERE collectionId = :collectionId")
suspend fun deleteById(collectionId: String)
/**
* One-shot fetch for a specific collection.
* @param collectionId The unique ID of the collection.
* @return The CollectionEntity if found, null otherwise.
*/
@Query("SELECT * FROM collections WHERE collectionId = :collectionId")
suspend fun getById(collectionId: String): CollectionEntity?
/**
* Reactive stream for a specific collection.
* @param collectionId The unique ID of the collection.
* @return A Flow that emits the CollectionEntity whenever that specific row changes.
*/
@Query("SELECT * FROM collections WHERE collectionId = :collectionId")
fun getByIdFlow(collectionId: String): Flow<CollectionEntity?>
// =========================================================================================
// LIST QUERIES (Observables)
// =========================================================================================
/**
* Retrieves all collections for the main UI list.
* Ordering: Prioritizes 'pinned' items first, then sorts by newest creation date.
* @return A Flow emitting a list of collections, updating automatically on table changes.
*/
@Query("""
SELECT * FROM collections
ORDER BY isPinned DESC, createdAt DESC
""")
fun getAllCollections(): Flow<List<CollectionEntity>>
/**
* Retrieves collections filtered by their type (e.g., SMART, STATIC, FAVORITE).
* @param type The category string to filter by.
* @return A Flow emitting the filtered list.
*/
@Query("""
SELECT * FROM collections
WHERE type = :type
ORDER BY isPinned DESC, createdAt DESC
""")
fun getCollectionsByType(type: String): Flow<List<CollectionEntity>>
/**
* Retrieves the single system-defined Favorite collection.
* Used for quick access to the standard 'Likes' functionality.
*/
@Query("SELECT * FROM collections WHERE type = 'FAVORITE' LIMIT 1")
suspend fun getFavoriteCollection(): CollectionEntity?
// =========================================================================================
// COMPLEX RELATIONSHIPS & DATA MODELS
// =========================================================================================
/**
* Retrieves a specialized model [CollectionWithDetails] which includes the base collection
* data plus a dynamically calculated photo count from the junction table.
* * @Transaction is required here because the query involves a subquery/multiple operations
* to ensure data consistency across the result set.
*/
@Transaction
@Query("""
SELECT
c.*,
(SELECT COUNT(*)
FROM collection_images ci
WHERE ci.collectionId = c.collectionId) as actualPhotoCount
FROM collections c
WHERE c.collectionId = :collectionId
""")
fun getCollectionWithDetails(collectionId: String): Flow<CollectionWithDetails?>
// =========================================================================================
// IMAGE MANAGEMENT (Junction Table: collection_images)
// =========================================================================================
/**
* Maps an image to a collection in the junction table.
*/
@Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun addImage(collectionImage: CollectionImageEntity)
/**
* Batch maps multiple images to a collection. Useful for bulk imports or multi-selection.
*/
@Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun addImages(collectionImages: List<CollectionImageEntity>)
/**
* Removes a specific image from a specific collection.
* Note: This does not delete the image from the 'images' table, only the relationship.
*/
@Query("""
DELETE FROM collection_images
WHERE collectionId = :collectionId AND imageId = :imageId
""")
suspend fun removeImage(collectionId: String, imageId: String)
/**
* Clears all image associations for a specific collection.
*/
@Query("DELETE FROM collection_images WHERE collectionId = :collectionId")
suspend fun clearAllImages(collectionId: String)
/**
* Performs a JOIN to retrieve actual ImageEntity objects associated with a collection.
* Ordered by the user's custom sort order, then by the time the image was added.
*/
@Query("""
SELECT i.* FROM images i
JOIN collection_images ci ON i.imageId = ci.imageId
WHERE ci.collectionId = :collectionId
ORDER BY ci.sortOrder ASC, ci.addedAt DESC
""")
fun getImagesInCollection(collectionId: String): Flow<List<ImageEntity>>
/**
* Fetches the top 4 images for a collection to be used as UI thumbnails/previews.
*/
@Query("""
SELECT i.* FROM images i
JOIN collection_images ci ON i.imageId = ci.imageId
WHERE ci.collectionId = :collectionId
ORDER BY ci.sortOrder ASC, ci.addedAt DESC
LIMIT 4
""")
suspend fun getPreviewImages(collectionId: String): List<ImageEntity>
/**
* Returns the current number of images associated with a collection.
*/
@Query("""
SELECT COUNT(*) FROM collection_images
WHERE collectionId = :collectionId
""")
suspend fun getPhotoCount(collectionId: String): Int
/**
* Checks if a specific image is already present in a collection.
* Returns true if a record exists.
*/
@Query("""
SELECT EXISTS(
SELECT 1 FROM collection_images
WHERE collectionId = :collectionId AND imageId = :imageId
)
""")
suspend fun containsImage(collectionId: String, imageId: String): Boolean
// =========================================================================================
// FILTER MANAGEMENT (For Smart/Dynamic Collections)
// =========================================================================================
/**
* Inserts a filter criteria for a Smart Collection.
*/
@Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun insertFilter(filter: CollectionFilterEntity)
/**
* Batch inserts multiple filter criteria.
*/
@Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun insertFilters(filters: List<CollectionFilterEntity>)
/**
* Removes all dynamic filter rules for a collection.
*/
@Query("DELETE FROM collection_filters WHERE collectionId = :collectionId")
suspend fun clearFilters(collectionId: String)
/**
* Retrieves the list of rules used to populate a Smart Collection.
*/
@Query("""
SELECT * FROM collection_filters
WHERE collectionId = :collectionId
ORDER BY createdAt ASC
""")
suspend fun getFilters(collectionId: String): List<CollectionFilterEntity>
/**
* Observable stream of filters for a Smart Collection.
*/
@Query("""
SELECT * FROM collection_filters
WHERE collectionId = :collectionId
ORDER BY createdAt ASC
""")
fun getFiltersFlow(collectionId: String): Flow<List<CollectionFilterEntity>>
// =========================================================================================
// AGGREGATE STATISTICS
// =========================================================================================
/** Total number of collections defined. */
@Query("SELECT COUNT(*) FROM collections")
suspend fun getCollectionCount(): Int
/** Count of collections that update dynamically based on filters. */
@Query("SELECT COUNT(*) FROM collections WHERE type = 'SMART'")
suspend fun getSmartCollectionCount(): Int
/** Count of manually curated collections. */
@Query("SELECT COUNT(*) FROM collections WHERE type = 'STATIC'")
suspend fun getStaticCollectionCount(): Int
/**
* Returns the sum of the photoCount cache across all collections.
* Returns nullable Int in case the table is empty.
*/
@Query("""
SELECT SUM(photoCount) FROM collections
""")
suspend fun getTotalPhotosInCollections(): Int?
// =========================================================================================
// GRANULAR UPDATES (Optimization)
// =========================================================================================
/**
* Synchronizes the 'photoCount' denormalized field in the collections table with
* the actual count in the junction table. Should be called after image additions/removals.
* * @param updatedAt Timestamp of the operation.
*/
@Query("""
UPDATE collections
SET photoCount = (
SELECT COUNT(*) FROM collection_images
WHERE collectionId = :collectionId
),
updatedAt = :updatedAt
WHERE collectionId = :collectionId
""")
suspend fun updatePhotoCount(collectionId: String, updatedAt: Long)
/**
* Updates the thumbnail/cover image for the collection card.
*/
@Query("""
UPDATE collections
SET coverImageUri = :imageUri, updatedAt = :updatedAt
WHERE collectionId = :collectionId
""")
suspend fun updateCoverImage(collectionId: String, imageUri: String?, updatedAt: Long)
/**
* Toggles the pinned status of a collection.
*/
@Query("""
UPDATE collections
SET isPinned = :isPinned, updatedAt = :updatedAt
WHERE collectionId = :collectionId
""")
suspend fun updatePinned(collectionId: String, isPinned: Boolean, updatedAt: Long)
/**
* Updates the name and description of a collection.
*/
@Query("""
UPDATE collections
SET name = :name, description = :description, updatedAt = :updatedAt
WHERE collectionId = :collectionId
""")
suspend fun updateDetails(
collectionId: String,
name: String,
description: String?,
updatedAt: Long
)
}

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package com.placeholder.sherpai2.data.local.dao
import androidx.room.Dao
import androidx.room.Insert
import androidx.room.OnConflictStrategy
import androidx.room.Query
import com.placeholder.sherpai2.data.local.entity.EventEntity
@Dao
interface EventDao {
@Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun insert(event: EventEntity)
/**
* Find events covering a timestamp.
*
* This is the backbone of auto-tagging by date.
*/
@Query("""
SELECT * FROM events
WHERE :timestamp BETWEEN startDate AND endDate
AND isHidden = 0
""")
suspend fun findEventsForTimestamp(timestamp: Long): List<EventEntity>
}

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package com.placeholder.sherpai2.data.local.dao
import androidx.room.*
import kotlinx.coroutines.flow.Flow
import com.placeholder.sherpai2.data.local.entity.FaceModelEntity
/**
* FaceModelDao - Manages face recognition models
*
* PRIMARY KEY TYPE: String (UUID)
* FOREIGN KEY: personId (String)
*/
@Dao
interface FaceModelDao {
@Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun insertFaceModel(faceModel: FaceModelEntity): Long // Row ID
@Update
suspend fun updateFaceModel(faceModel: FaceModelEntity)
@Query("UPDATE face_models SET lastUsed = :timestamp WHERE id = :faceModelId")
suspend fun updateLastUsed(faceModelId: String, timestamp: Long)
@Query("SELECT * FROM face_models WHERE id = :faceModelId")
suspend fun getFaceModelById(faceModelId: String): FaceModelEntity?
@Query("SELECT * FROM face_models WHERE personId = :personId AND isActive = 1")
suspend fun getFaceModelByPersonId(personId: String): FaceModelEntity?
@Query("SELECT * FROM face_models WHERE isActive = 1 ORDER BY lastUsed DESC")
suspend fun getAllActiveFaceModels(): List<FaceModelEntity>
@Query("SELECT * FROM face_models WHERE isActive = 1 ORDER BY lastUsed DESC")
fun getAllActiveFaceModelsFlow(): Flow<List<FaceModelEntity>>
@Query("DELETE FROM face_models WHERE id = :faceModelId")
suspend fun deleteFaceModelById(faceModelId: String)
@Query("UPDATE face_models SET isActive = 0 WHERE id = :faceModelId")
suspend fun deactivateFaceModel(faceModelId: String)
@Query("SELECT COUNT(*) FROM face_models WHERE isActive = 1")
suspend fun getActiveFaceModelCount(): Int
}

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package com.placeholder.sherpai2.data.local.dao
import androidx.room.*
import com.placeholder.sherpai2.data.local.entity.FaceCacheEntity
/**
* FaceCacheDao - NO SOLO-PHOTO FILTER
*
* CRITICAL CHANGE:
* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
* Removed all faceCount filters from queries
*
* WHY:
* - Group photos contain high-quality faces (especially for children)
* - IoU matching ensures we extract the CORRECT face from group photos
* - Rejecting group photos was eliminating 60-70% of quality faces!
*
* RESULT:
* - 2-3x more faces for clustering
* - Quality remains high (still filter by size + score)
* - Better clusters, especially for children
*/
@Dao
interface FaceCacheDao {
@Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun insert(faceCacheEntity: FaceCacheEntity)
@Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun insertAll(faceCacheEntities: List<FaceCacheEntity>)
@Update
suspend fun update(faceCacheEntity: FaceCacheEntity)
/**
* Get ALL quality faces - INCLUDES GROUP PHOTOS!
*
* Quality filters (still strict):
* - faceAreaRatio >= minRatio (default 3% of image)
* - qualityScore >= minQuality (default 0.6 = 60%)
* - Has embedding
*
* NO faceCount filter!
*/
@Query("""
SELECT fc.*
FROM face_cache fc
WHERE fc.faceAreaRatio >= :minRatio
AND fc.qualityScore >= :minQuality
AND fc.embedding IS NOT NULL
ORDER BY fc.qualityScore DESC, fc.faceAreaRatio DESC
LIMIT :limit
""")
suspend fun getAllQualityFaces(
minRatio: Float = 0.03f,
minQuality: Float = 0.6f,
limit: Int = Int.MAX_VALUE
): List<FaceCacheEntity>
/**
* Get quality faces WITHOUT embeddings - FOR PATH 2
*
* These have good metadata but need embeddings generated.
* INCLUDES GROUP PHOTOS - IoU matching will handle extraction!
*/
@Query("""
SELECT fc.*
FROM face_cache fc
WHERE fc.faceAreaRatio >= :minRatio
AND fc.qualityScore >= :minQuality
AND fc.embedding IS NULL
ORDER BY fc.qualityScore DESC, fc.faceAreaRatio DESC
LIMIT :limit
""")
suspend fun getQualityFacesWithoutEmbeddings(
minRatio: Float = 0.03f,
minQuality: Float = 0.6f,
limit: Int = 5000
): List<FaceCacheEntity>
/**
* Count faces WITH embeddings (Path 1 check)
*/
@Query("""
SELECT COUNT(*)
FROM face_cache
WHERE embedding IS NOT NULL
AND qualityScore >= :minQuality
""")
suspend fun countFacesWithEmbeddings(minQuality: Float = 0.6f): Int
/**
* Count faces WITHOUT embeddings (Path 2 check)
*/
@Query("""
SELECT COUNT(*)
FROM face_cache
WHERE embedding IS NULL
AND qualityScore >= :minQuality
""")
suspend fun countFacesWithoutEmbeddings(minQuality: Float = 0.6f): Int
/**
* Get faces for specific image (for IoU matching)
*/
@Query("SELECT * FROM face_cache WHERE imageId = :imageId")
suspend fun getFaceCacheForImage(imageId: String): List<FaceCacheEntity>
/**
* Cache statistics
*/
@Query("""
SELECT
COUNT(*) as totalFaces,
COUNT(CASE WHEN embedding IS NOT NULL THEN 1 END) as withEmbeddings,
AVG(qualityScore) as avgQuality,
AVG(faceAreaRatio) as avgSize
FROM face_cache
""")
suspend fun getCacheStats(): CacheStats
@Query("DELETE FROM face_cache WHERE imageId = :imageId")
suspend fun deleteCacheForImage(imageId: String)
@Query("DELETE FROM face_cache")
suspend fun deleteAll()
}
data class CacheStats(
val totalFaces: Int,
val withEmbeddings: Int,
val avgQuality: Float,
val avgSize: Float
)

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package com.placeholder.sherpai2.data.local.dao
import androidx.room.Dao
import androidx.room.Query
import androidx.room.Transaction
import com.placeholder.sherpai2.data.local.model.ImageWithEverything
import kotlinx.coroutines.flow.Flow
@Dao
interface ImageAggregateDao {
/**
* Observe a fully-hydrated image object.
*/
@Transaction
@Query("""
SELECT * FROM images
WHERE imageId = :imageId
""")
fun observeImageWithEverything(
imageId: String
): Flow<ImageWithEverything>
/**
* Observe all images.
*/
@Transaction
@Query("""
SELECT * FROM images
ORDER BY capturedAt DESC
""")
fun observeAllImagesWithEverything(): Flow<List<ImageWithEverything>>
/**
* Observe images filtered by tag value.
*
* Joins images -> image_tags -> tags
*/
@Transaction
@Query("""
SELECT images.* FROM images
INNER JOIN image_tags ON images.imageId = image_tags.imageId
INNER JOIN tags ON tags.tagId = image_tags.tagId
WHERE tags.value = :tag
ORDER BY images.capturedAt DESC
""")
fun observeImagesWithTag(tag: String): Flow<List<ImageWithEverything>>
}

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package com.placeholder.sherpai2.data.local.dao
import androidx.room.Dao
import androidx.room.Insert
import androidx.room.OnConflictStrategy
import androidx.room.Query
import androidx.room.Transaction
import com.placeholder.sherpai2.data.local.entity.ImageEntity
import com.placeholder.sherpai2.data.local.model.ImageWithEverything
import kotlinx.coroutines.flow.Flow
/**
* Data classes for statistics queries
*/
data class DateCount(
val date: String, // YYYY-MM-DD format
val count: Int
)
data class MonthCount(
val month: String, // YYYY-MM format
val count: Int
)
data class YearCount(
val year: String, // YYYY format
val count: Int
)
data class DayOfWeekCount(
val dayOfWeek: Int, // 0 = Sunday, 6 = Saturday
val count: Int
)
data class HourCount(
val hour: Int, // 0-23
val count: Int
)
/**
* Face detection cache statistics
*/
data class FaceCacheStats(
val totalImages: Int,
val imagesWithFaceCache: Int,
val imagesWithFaces: Int,
val imagesWithoutFaces: Int,
val needsScanning: Int
)
@Dao
interface ImageDao {
/**
* Insert images.
*
* IGNORE prevents duplicate insertion
* when sha256 or imageUri already exists.
*/
@Insert(onConflict = OnConflictStrategy.IGNORE)
suspend fun insertImages(images: List<ImageEntity>)
/**
* Get image by ID.
*/
@Query("SELECT * FROM images WHERE imageId = :imageId")
suspend fun getImageById(imageId: String): ImageEntity?
/**
* Stream images ordered by capture time (newest first).
*
* Flow is critical:
* - UI auto-updates
* - No manual refresh
*/
@Query("""
SELECT * FROM images
ORDER BY capturedAt DESC
""")
fun observeAllImages(): Flow<List<ImageEntity>>
/**
* Fetch images in a time range.
* Used for:
* - event auto-assignment
* - timeline views
*/
@Query("""
SELECT * FROM images
WHERE capturedAt BETWEEN :start AND :end
ORDER BY capturedAt ASC
""")
suspend fun getImagesInRange(
start: Long,
end: Long
): List<ImageEntity>
@Transaction
@Query("SELECT * FROM images ORDER BY capturedAt DESC LIMIT :limit")
fun getRecentImages(limit: Int): Flow<List<ImageWithEverything>>
@Query("SELECT COUNT(*) > 0 FROM images WHERE sha256 = :sha256")
suspend fun existsBySha256(sha256: String): Boolean
@Insert(onConflict = OnConflictStrategy.IGNORE)
suspend fun insert(image: ImageEntity)
/**
* Get images by list of IDs.
*/
@Query("SELECT * FROM images WHERE imageId IN (:imageIds)")
suspend fun getImagesByIds(imageIds: List<String>): List<ImageEntity>
@Query("SELECT COUNT(*) FROM images")
suspend fun getImageCount(): Int
/**
* Get all images (for utilities processing)
*/
@Query("SELECT * FROM images ORDER BY capturedAt DESC")
suspend fun getAllImages(): List<ImageEntity>
/**
* Get all images sorted by time (for burst detection)
*/
@Query("SELECT * FROM images ORDER BY capturedAt ASC")
suspend fun getAllImagesSortedByTime(): List<ImageEntity>
// ==========================================
// FACE DETECTION CACHE QUERIES - CRITICAL FOR OPTIMIZATION
// ==========================================
/**
* Get all images that have faces (cached).
* This is the PRIMARY optimization query.
*
* Use this for person scanning instead of scanning ALL images.
* Estimated speed improvement: 50-70% for typical photo libraries.
*/
@Query("""
SELECT * FROM images
WHERE hasFaces = 1
AND faceDetectionVersion = :currentVersion
ORDER BY capturedAt DESC
""")
suspend fun getImagesWithFaces(currentVersion: Int = ImageEntity.CURRENT_FACE_DETECTION_VERSION): List<ImageEntity>
/**
* Get images with faces, limited (for progressive scanning)
*/
@Query("""
SELECT * FROM images
WHERE hasFaces = 1
AND faceDetectionVersion = :currentVersion
ORDER BY capturedAt DESC
LIMIT :limit
""")
suspend fun getImagesWithFacesLimited(
limit: Int,
currentVersion: Int = ImageEntity.CURRENT_FACE_DETECTION_VERSION
): List<ImageEntity>
/**
* Get images with a specific face count.
* Use cases:
* - Solo photos (faceCount = 1)
* - Couple photos (faceCount = 2)
* - Filter out groups (faceCount <= 2)
*/
@Query("""
SELECT * FROM images
WHERE hasFaces = 1
AND faceCount = :count
AND faceDetectionVersion = :currentVersion
ORDER BY capturedAt DESC
""")
suspend fun getImagesByFaceCount(
count: Int,
currentVersion: Int = ImageEntity.CURRENT_FACE_DETECTION_VERSION
): List<ImageEntity>
/**
* Get images with face count in range.
* Examples:
* - Solo or couple: minFaces=1, maxFaces=2
* - Groups only: minFaces=3, maxFaces=999
*/
@Query("""
SELECT * FROM images
WHERE hasFaces = 1
AND faceCount BETWEEN :minFaces AND :maxFaces
AND faceDetectionVersion = :currentVersion
ORDER BY capturedAt DESC
""")
suspend fun getImagesByFaceCountRange(
minFaces: Int,
maxFaces: Int,
currentVersion: Int = ImageEntity.CURRENT_FACE_DETECTION_VERSION
): List<ImageEntity>
/**
* Get images that need face detection scanning.
* These images have:
* - Never been scanned (hasFaces = null)
* - Old detection version
* - Invalid cache
*/
@Query("""
SELECT * FROM images
WHERE hasFaces IS NULL
OR faceDetectionVersion IS NULL
OR faceDetectionVersion < :currentVersion
ORDER BY capturedAt DESC
""")
suspend fun getImagesNeedingFaceDetection(
currentVersion: Int = ImageEntity.CURRENT_FACE_DETECTION_VERSION
): List<ImageEntity>
/**
* Get count of images needing face detection.
*/
@Query("""
SELECT COUNT(*) FROM images
WHERE hasFaces IS NULL
OR faceDetectionVersion IS NULL
OR faceDetectionVersion < :currentVersion
""")
suspend fun getImagesNeedingFaceDetectionCount(
currentVersion: Int = ImageEntity.CURRENT_FACE_DETECTION_VERSION
): Int
/**
* Update face detection cache for a single image.
* Called after detecting faces in an image.
*/
@Query("""
UPDATE images
SET hasFaces = :hasFaces,
faceCount = :faceCount,
facesLastDetected = :timestamp,
faceDetectionVersion = :version
WHERE imageId = :imageId
""")
suspend fun updateFaceDetectionCache(
imageId: String,
hasFaces: Boolean,
faceCount: Int,
timestamp: Long = System.currentTimeMillis(),
version: Int = ImageEntity.CURRENT_FACE_DETECTION_VERSION
)
/**
* Batch update face detection cache.
* More efficient when updating many images at once.
*
* Note: Room doesn't support batch updates directly,
* so this needs to be called multiple times in a transaction.
*/
@Transaction
suspend fun updateFaceDetectionCacheBatch(updates: List<FaceDetectionCacheUpdate>) {
updates.forEach { update ->
updateFaceDetectionCache(
imageId = update.imageId,
hasFaces = update.hasFaces,
faceCount = update.faceCount,
timestamp = update.timestamp,
version = update.version
)
}
}
/**
* Get face detection cache statistics.
* Useful for UI display and determining background scan needs.
*/
@Query("""
SELECT
COUNT(*) as totalImages,
SUM(CASE WHEN hasFaces IS NOT NULL THEN 1 ELSE 0 END) as imagesWithFaceCache,
SUM(CASE WHEN hasFaces = 1 THEN 1 ELSE 0 END) as imagesWithFaces,
SUM(CASE WHEN hasFaces = 0 THEN 1 ELSE 0 END) as imagesWithoutFaces,
SUM(CASE WHEN hasFaces IS NULL OR faceDetectionVersion < :currentVersion THEN 1 ELSE 0 END) as needsScanning
FROM images
""")
suspend fun getFaceCacheStats(
currentVersion: Int = ImageEntity.CURRENT_FACE_DETECTION_VERSION
): FaceCacheStats?
/**
* Invalidate face detection cache (force re-scan).
* Call this when upgrading face detection algorithm.
*/
@Query("""
UPDATE images
SET faceDetectionVersion = NULL
WHERE faceDetectionVersion < :newVersion
""")
suspend fun invalidateFaceDetectionCache(newVersion: Int)
/**
* Clear ALL face detection cache (force full rebuild).
* Sets all face detection fields to NULL for all images.
*
* Use this for "Force Rebuild Cache" button.
* This is different from invalidateFaceDetectionCache which only
* invalidates old versions - this clears EVERYTHING.
*/
@Query("""
UPDATE images
SET hasFaces = NULL,
faceCount = NULL,
facesLastDetected = NULL,
faceDetectionVersion = NULL
""")
suspend fun clearAllFaceDetectionCache()
// ==========================================
// STATISTICS QUERIES
// ==========================================
/**
* Get photo counts by date (daily granularity)
* Returns all days that have at least one photo
*/
@Query("""
SELECT
date(capturedAt/1000, 'unixepoch') as date,
COUNT(*) as count
FROM images
GROUP BY date
ORDER BY date ASC
""")
suspend fun getPhotoCountsByDate(): List<DateCount>
/**
* Get photo counts by month (monthly granularity)
*/
@Query("""
SELECT
strftime('%Y-%m', capturedAt/1000, 'unixepoch') as month,
COUNT(*) as count
FROM images
GROUP BY month
ORDER BY month ASC
""")
suspend fun getPhotoCountsByMonth(): List<MonthCount>
/**
* Get photo counts by year (yearly granularity)
*/
@Query("""
SELECT
strftime('%Y', capturedAt/1000, 'unixepoch') as year,
COUNT(*) as count
FROM images
GROUP BY year
ORDER BY year DESC
""")
suspend fun getPhotoCountsByYear(): List<YearCount>
/**
* Get photo counts by year (Flow version for reactive UI)
*/
@Query("""
SELECT
strftime('%Y', capturedAt/1000, 'unixepoch') as year,
COUNT(*) as count
FROM images
GROUP BY year
ORDER BY year DESC
""")
fun getPhotoCountsByYearFlow(): Flow<List<YearCount>>
/**
* Get photo counts by day of week (0 = Sunday, 6 = Saturday)
* Shows which days you take the most photos
*/
@Query("""
SELECT
CAST(strftime('%w', capturedAt/1000, 'unixepoch') AS INTEGER) as dayOfWeek,
COUNT(*) as count
FROM images
GROUP BY dayOfWeek
ORDER BY dayOfWeek ASC
""")
suspend fun getPhotoCountsByDayOfWeek(): List<DayOfWeekCount>
/**
* Get photo counts by hour of day (0-23)
* Shows when you take the most photos
*/
@Query("""
SELECT
CAST(strftime('%H', capturedAt/1000, 'unixepoch') AS INTEGER) as hour,
COUNT(*) as count
FROM images
GROUP BY hour
ORDER BY hour ASC
""")
suspend fun getPhotoCountsByHour(): List<HourCount>
/**
* Get earliest and latest photo timestamps
* Used for date range calculations
*/
@Query("""
SELECT
MIN(capturedAt) as earliest,
MAX(capturedAt) as latest
FROM images
""")
suspend fun getPhotoDateRange(): PhotoDateRange?
/**
* Get photo count for a specific year
*/
@Query("""
SELECT COUNT(*) FROM images
WHERE strftime('%Y', capturedAt/1000, 'unixepoch') = :year
""")
suspend fun getPhotoCountForYear(year: String): Int
/**
* Get average photos per day (for stats display)
*/
@Query("""
SELECT
CAST(COUNT(*) AS REAL) /
CAST((MAX(capturedAt) - MIN(capturedAt)) / 86400000 AS REAL) as avgPerDay
FROM images
WHERE (SELECT COUNT(*) FROM images) > 0
""")
suspend fun getAveragePhotosPerDay(): Float?
@Query("SELECT * FROM images WHERE hasFaces = 1 ORDER BY faceCount DESC")
suspend fun getImagesWithFaces(): List<ImageEntity>
}
/**
* Data class for date range result
*/
data class PhotoDateRange(
val earliest: Long,
val latest: Long
)
/**
* Data class for batch face detection cache updates
*/
data class FaceDetectionCacheUpdate(
val imageId: String,
val hasFaces: Boolean,
val faceCount: Int,
val timestamp: Long = System.currentTimeMillis(),
val version: Int = ImageEntity.CURRENT_FACE_DETECTION_VERSION
)

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package com.placeholder.sherpai2.data.local.dao
import androidx.room.Dao
import androidx.room.Insert
import androidx.room.OnConflictStrategy
import androidx.room.Query
import com.placeholder.sherpai2.data.local.entity.ImageEventEntity
@Dao
interface ImageEventDao {
@Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun upsert(entity: ImageEventEntity)
/**
* Images associated with an event.
*/
@Query("""
SELECT imageId FROM image_events
WHERE eventId = :eventId
""")
suspend fun findImagesForEvent(eventId: String): List<String>
}

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package com.placeholder.sherpai2.data.local.dao
import androidx.room.Dao
import androidx.room.Insert
import androidx.room.OnConflictStrategy
import androidx.room.Query
import androidx.room.Transaction
import com.placeholder.sherpai2.data.local.entity.ImageTagEntity
import com.placeholder.sherpai2.data.local.entity.TagEntity
import kotlinx.coroutines.flow.Flow
/**
* Data class for burst statistics
*/
data class BurstStats(
val totalBurstPhotos: Int,
val estimatedBurstGroups: Int,
val burstRepresentatives: Int
)
@Dao
interface ImageTagDao {
@Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun upsert(imageTag: ImageTagEntity)
@Query("""
SELECT * FROM image_tags
WHERE imageId = :imageId
AND visibility != 'HIDDEN'
""")
fun observeTagsForImage(imageId: String): Flow<List<ImageTagEntity>>
/**
* FIXED: Removed default parameter
*/
@Query("""
SELECT imageId FROM image_tags
WHERE tagId = :tagId
AND visibility = 'PUBLIC'
AND confidence >= :minConfidence
""")
suspend fun findImagesByTag(
tagId: String,
minConfidence: Float
): List<String>
@Transaction
@Query("""
SELECT t.*
FROM tags t
INNER JOIN image_tags it ON t.tagId = it.tagId
WHERE it.imageId = :imageId AND it.visibility = 'PUBLIC'
""")
fun getTagsForImage(imageId: String): Flow<List<TagEntity>>
/**
* Insert image tag (for utilities tagging)
*/
@Insert(onConflict = OnConflictStrategy.IGNORE)
suspend fun insert(imageTag: ImageTagEntity): Long
// ==========================================
// BURST STATISTICS - ADDED FOR STATS SECTION
// ==========================================
/**
* Get comprehensive burst statistics
* Returns total burst photos, estimated groups, and representative count
*/
@Query("""
SELECT
(SELECT COUNT(DISTINCT it.imageId)
FROM image_tags it
INNER JOIN tags t ON it.tagId = t.tagId
WHERE t.value = 'burst') as totalBurstPhotos,
(SELECT COUNT(DISTINCT it.imageId) / 3
FROM image_tags it
INNER JOIN tags t ON it.tagId = t.tagId
WHERE t.value = 'burst') as estimatedBurstGroups,
(SELECT COUNT(DISTINCT it.imageId)
FROM image_tags it
INNER JOIN tags t ON it.tagId = t.tagId
WHERE t.value = 'burst_representative') as burstRepresentatives
""")
suspend fun getBurstStats(): BurstStats?
/**
* Get burst statistics (Flow version for reactive UI)
*/
@Query("""
SELECT
(SELECT COUNT(DISTINCT it.imageId)
FROM image_tags it
INNER JOIN tags t ON it.tagId = t.tagId
WHERE t.value = 'burst') as totalBurstPhotos,
(SELECT COUNT(DISTINCT it.imageId) / 3
FROM image_tags it
INNER JOIN tags t ON it.tagId = t.tagId
WHERE t.value = 'burst') as estimatedBurstGroups,
(SELECT COUNT(DISTINCT it.imageId)
FROM image_tags it
INNER JOIN tags t ON it.tagId = t.tagId
WHERE t.value = 'burst_representative') as burstRepresentatives
""")
fun getBurstStatsFlow(): Flow<BurstStats?>
/**
* Get count of burst photos
*/
@Query("""
SELECT COUNT(DISTINCT it.imageId)
FROM image_tags it
INNER JOIN tags t ON it.tagId = t.tagId
WHERE t.value = 'burst'
""")
suspend fun getBurstPhotoCount(): Int
/**
* Get count of burst representative photos
* (photos marked as the best in each burst sequence)
*/
@Query("""
SELECT COUNT(DISTINCT it.imageId)
FROM image_tags it
INNER JOIN tags t ON it.tagId = t.tagId
WHERE t.value = 'burst_representative'
""")
suspend fun getBurstRepresentativeCount(): Int
/**
* Get estimated number of burst groups
* Assumes average of 3 photos per burst
*/
@Query("""
SELECT COUNT(DISTINCT it.imageId) / 3
FROM image_tags it
INNER JOIN tags t ON it.tagId = t.tagId
WHERE t.value = 'burst'
""")
suspend fun getEstimatedBurstGroupCount(): Int
}

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package com.placeholder.sherpai2.data.local.dao
import androidx.room.*
import com.placeholder.sherpai2.data.local.entity.PersonEntity
import kotlinx.coroutines.flow.Flow
@Dao
interface PersonDao {
@Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun insert(person: PersonEntity): Long
@Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun insertAll(persons: List<PersonEntity>)
@Update
suspend fun update(person: PersonEntity)
/**
* FIXED: Removed default parameter
*/
@Query("UPDATE persons SET updatedAt = :timestamp WHERE id = :personId")
suspend fun updateTimestamp(personId: String, timestamp: Long)
@Delete
suspend fun delete(person: PersonEntity)
@Query("DELETE FROM persons WHERE id = :personId")
suspend fun deleteById(personId: String)
@Query("SELECT * FROM persons WHERE id = :personId")
suspend fun getPersonById(personId: String): PersonEntity?
@Query("SELECT * FROM persons WHERE id IN (:personIds)")
suspend fun getPersonsByIds(personIds: List<String>): List<PersonEntity>
@Query("SELECT * FROM persons ORDER BY name ASC")
suspend fun getAllPersons(): List<PersonEntity>
@Query("SELECT * FROM persons ORDER BY name ASC")
fun getAllPersonsFlow(): Flow<List<PersonEntity>>
@Query("SELECT * FROM persons WHERE name LIKE '%' || :query || '%' ORDER BY name ASC")
suspend fun searchByName(query: String): List<PersonEntity>
@Query("SELECT COUNT(*) FROM persons")
suspend fun getPersonCount(): Int
@Query("SELECT EXISTS(SELECT 1 FROM persons WHERE id = :personId)")
suspend fun personExists(personId: String): Boolean
}

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package com.placeholder.sherpai2.data.local.dao
import androidx.room.*
import com.placeholder.sherpai2.data.local.entity.PersonAgeTagEntity
import kotlinx.coroutines.flow.Flow
/**
* PersonAgeTagDao - Manage searchable age tags for children
*
* USAGE EXAMPLES:
* - Search "emma age 3" → getImageIdsForTag("emma_age3")
* - Find all photos of Emma at age 5 → getImageIdsForPersonAtAge(emmaId, 5)
* - Get age progression → getTagsForPerson(emmaId) sorted by age
*/
@Dao
interface PersonAgeTagDao {
@Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun insertTag(tag: PersonAgeTagEntity)
@Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun insertTags(tags: List<PersonAgeTagEntity>)
/**
* Get all age tags for a person (sorted by age)
* Useful for age progression timeline
*/
@Query("SELECT * FROM person_age_tags WHERE personId = :personId ORDER BY ageAtCapture ASC")
suspend fun getTagsForPerson(personId: String): List<PersonAgeTagEntity>
/**
* Get all age tags for an image
*/
@Query("SELECT * FROM person_age_tags WHERE imageId = :imageId")
suspend fun getTagsForImage(imageId: String): List<PersonAgeTagEntity>
/**
* Search by tag value (e.g., "emma_age3")
* Returns all image IDs matching this tag
*/
@Query("SELECT DISTINCT imageId FROM person_age_tags WHERE tagValue = :tagValue")
suspend fun getImageIdsForTag(tagValue: String): List<String>
/**
* Get images of a person at a specific age
*/
@Query("SELECT DISTINCT imageId FROM person_age_tags WHERE personId = :personId AND ageAtCapture = :age")
suspend fun getImageIdsForPersonAtAge(personId: String, age: Int): List<String>
/**
* Get images of a person in an age range
*/
@Query("""
SELECT DISTINCT imageId FROM person_age_tags
WHERE personId = :personId
AND ageAtCapture BETWEEN :minAge AND :maxAge
ORDER BY ageAtCapture ASC
""")
suspend fun getImageIdsForPersonAgeRange(personId: String, minAge: Int, maxAge: Int): List<String>
/**
* Get all unique ages for a person (for age picker UI)
*/
@Query("SELECT DISTINCT ageAtCapture FROM person_age_tags WHERE personId = :personId ORDER BY ageAtCapture ASC")
suspend fun getAgesForPerson(personId: String): List<Int>
/**
* Delete all tags for a person
*/
@Query("DELETE FROM person_age_tags WHERE personId = :personId")
suspend fun deleteTagsForPerson(personId: String)
/**
* Delete all tags for an image
*/
@Query("DELETE FROM person_age_tags WHERE imageId = :imageId")
suspend fun deleteTagsForImage(imageId: String)
/**
* Get count of photos at each age (for statistics)
*/
@Query("""
SELECT ageAtCapture, COUNT(DISTINCT imageId) as count
FROM person_age_tags
WHERE personId = :personId
GROUP BY ageAtCapture
ORDER BY ageAtCapture ASC
""")
suspend fun getPhotoCountByAge(personId: String): List<AgePhotoCount>
/**
* Flow version for reactive UI
*/
@Query("SELECT * FROM person_age_tags WHERE personId = :personId ORDER BY ageAtCapture ASC")
fun getTagsForPersonFlow(personId: String): Flow<List<PersonAgeTagEntity>>
}
/**
* Data class for age photo count statistics
*/
data class AgePhotoCount(
val ageAtCapture: Int,
val count: Int
)

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package com.placeholder.sherpai2.data.local.dao
import androidx.room.*
import kotlinx.coroutines.flow.Flow
import com.placeholder.sherpai2.data.local.entity.PhotoFaceTagEntity
@Dao
interface PhotoFaceTagDao {
@Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun insertTag(tag: PhotoFaceTagEntity): Long
@Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun insertTags(tags: List<PhotoFaceTagEntity>)
@Update
suspend fun updateTag(tag: PhotoFaceTagEntity)
/**
* FIXED: Removed default parameter
*/
@Query("UPDATE photo_face_tags SET verifiedByUser = 1, verifiedAt = :timestamp WHERE id = :tagId")
suspend fun markTagAsVerified(tagId: String, timestamp: Long)
// ===== QUERY BY IMAGE =====
@Query("SELECT * FROM photo_face_tags WHERE imageId = :imageId")
suspend fun getTagsForImage(imageId: String): List<PhotoFaceTagEntity>
@Query("SELECT COUNT(*) FROM photo_face_tags WHERE imageId = :imageId")
suspend fun getFaceCountForImage(imageId: String): Int
@Query("SELECT EXISTS(SELECT 1 FROM photo_face_tags WHERE imageId = :imageId AND faceModelId = :faceModelId)")
suspend fun imageHasPerson(imageId: String, faceModelId: String): Boolean
// ===== QUERY BY FACE MODEL =====
@Query("SELECT DISTINCT imageId FROM photo_face_tags WHERE faceModelId = :faceModelId ORDER BY detectedAt DESC")
suspend fun getImageIdsForFaceModel(faceModelId: String): List<String>
@Query("SELECT DISTINCT imageId FROM photo_face_tags WHERE faceModelId = :faceModelId ORDER BY detectedAt DESC")
fun getImageIdsForFaceModelFlow(faceModelId: String): Flow<List<String>>
@Query("SELECT faceModelId, COUNT(DISTINCT imageId) as photoCount FROM photo_face_tags GROUP BY faceModelId")
suspend fun getPhotoCountPerFaceModel(): List<FaceModelPhotoCount>
@Query("SELECT * FROM photo_face_tags WHERE faceModelId = :faceModelId ORDER BY detectedAt DESC")
suspend fun getAllTagsForFaceModel(faceModelId: String): List<PhotoFaceTagEntity>
// ===== DELETE =====
@Delete
suspend fun deleteTag(tag: PhotoFaceTagEntity)
@Query("DELETE FROM photo_face_tags WHERE id = :tagId")
suspend fun deleteTagById(tagId: String)
@Query("DELETE FROM photo_face_tags WHERE faceModelId = :faceModelId")
suspend fun deleteTagsForFaceModel(faceModelId: String)
@Query("DELETE FROM photo_face_tags WHERE imageId = :imageId")
suspend fun deleteTagsForImage(imageId: String)
// ===== STATISTICS =====
/**
* FIXED: Removed default parameter
*/
@Query("SELECT * FROM photo_face_tags WHERE confidence < :threshold ORDER BY confidence ASC")
suspend fun getLowConfidenceTags(threshold: Float): List<PhotoFaceTagEntity>
@Query("SELECT * FROM photo_face_tags WHERE verifiedByUser = 0 ORDER BY detectedAt DESC")
suspend fun getUnverifiedTags(): List<PhotoFaceTagEntity>
@Query("SELECT COUNT(*) FROM photo_face_tags WHERE verifiedByUser = 0")
suspend fun getUnverifiedTagCount(): Int
@Query("SELECT AVG(confidence) FROM photo_face_tags WHERE faceModelId = :faceModelId")
suspend fun getAverageConfidenceForFaceModel(faceModelId: String): Float?
/**
* FIXED: Removed default parameter
*/
@Query("SELECT * FROM photo_face_tags ORDER BY detectedAt DESC LIMIT :limit")
suspend fun getRecentlyDetectedFaces(limit: Int): List<PhotoFaceTagEntity>
}
data class FaceModelPhotoCount(
val faceModelId: String,
val photoCount: Int
)

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package com.placeholder.sherpai2.data.local.dao
import androidx.room.Dao
import androidx.room.Insert
import androidx.room.OnConflictStrategy
import androidx.room.Query
import com.placeholder.sherpai2.data.local.entity.ImageEntity
import com.placeholder.sherpai2.data.local.entity.TagEntity
import com.placeholder.sherpai2.data.local.entity.TagWithUsage
import kotlinx.coroutines.flow.Flow
/**
* Data class for tag statistics
*/
data class TagStat(
val tagValue: String,
val tagType: String,
val imageCount: Int,
val tagId: String
)
/**
* TagDao - Tag management with face recognition integration
*
* NO DEFAULT PARAMETERS - Room doesn't support them in @Query methods
*/
@Dao
interface TagDao {
// ======================
// BASIC OPERATIONS
// ======================
@Insert(onConflict = OnConflictStrategy.IGNORE)
suspend fun insert(tag: TagEntity): Long
@Query("SELECT * FROM tags WHERE value = :value LIMIT 1")
suspend fun getByValue(value: String): TagEntity?
@Query("SELECT * FROM tags WHERE tagId = :tagId")
suspend fun getById(tagId: String): TagEntity?
@Query("SELECT * FROM tags ORDER BY value ASC")
suspend fun getAll(): List<TagEntity>
@Query("SELECT * FROM tags ORDER BY value ASC")
fun getAllFlow(): Flow<List<TagEntity>>
@Query("SELECT * FROM tags WHERE type = :type ORDER BY value ASC")
suspend fun getByType(type: String): List<TagEntity>
@Query("DELETE FROM tags WHERE tagId = :tagId")
suspend fun delete(tagId: String)
// ======================
// STATISTICS (returns TagWithUsage)
// ======================
/**
* Get most used tags WITH usage counts
*
* @param limit Maximum number of tags to return
*/
@Query("""
SELECT t.tagId, t.type, t.value, t.createdAt,
COUNT(it.imageId) as usage_count
FROM tags t
LEFT JOIN image_tags it ON t.tagId = it.tagId
GROUP BY t.tagId
ORDER BY usage_count DESC
LIMIT :limit
""")
suspend fun getMostUsedTags(limit: Int): List<TagWithUsage>
/**
* Get tag usage count
*/
@Query("""
SELECT COUNT(DISTINCT it.imageId)
FROM image_tags it
WHERE it.tagId = :tagId
""")
suspend fun getTagUsageCount(tagId: String): Int
// ======================
// PERSON INTEGRATION
// ======================
/**
* Get all tags used for images containing a specific person
*/
@Query("""
SELECT DISTINCT t.* FROM tags t
INNER JOIN image_tags it ON t.tagId = it.tagId
INNER JOIN photo_face_tags pft ON it.imageId = pft.imageId
INNER JOIN face_models fm ON pft.faceModelId = fm.id
WHERE fm.personId = :personId
ORDER BY t.value ASC
""")
suspend fun getTagsForPerson(personId: String): List<TagEntity>
/**
* Get images that have both a specific tag AND contain a specific person
*/
@Query("""
SELECT DISTINCT i.* FROM images i
INNER JOIN image_tags it ON i.imageId = it.imageId
INNER JOIN photo_face_tags pft ON i.imageId = pft.imageId
INNER JOIN face_models fm ON pft.faceModelId = fm.id
WHERE it.tagId = :tagId AND fm.personId = :personId
ORDER BY i.capturedAt DESC
""")
suspend fun getImagesWithTagAndPerson(
tagId: String,
personId: String
): List<ImageEntity>
/**
* Get images with tag and person as Flow
*/
@Query("""
SELECT DISTINCT i.* FROM images i
INNER JOIN image_tags it ON i.imageId = it.imageId
INNER JOIN photo_face_tags pft ON i.imageId = pft.imageId
INNER JOIN face_models fm ON pft.faceModelId = fm.id
WHERE it.tagId = :tagId AND fm.personId = :personId
ORDER BY i.capturedAt DESC
""")
fun getImagesWithTagAndPersonFlow(
tagId: String,
personId: String
): Flow<List<ImageEntity>>
/**
* Count images with tag and person
*/
@Query("""
SELECT COUNT(DISTINCT i.imageId) FROM images i
INNER JOIN image_tags it ON i.imageId = it.imageId
INNER JOIN photo_face_tags pft ON i.imageId = pft.imageId
INNER JOIN face_models fm ON pft.faceModelId = fm.id
WHERE it.tagId = :tagId AND fm.personId = :personId
""")
suspend fun countImagesWithTagAndPerson(
tagId: String,
personId: String
): Int
// ======================
// AUTO-SUGGESTIONS
// ======================
/**
* Suggest tags based on person's relationship
*
* @param limit Maximum number of suggestions
*/
@Query("""
SELECT DISTINCT t.* FROM tags t
INNER JOIN image_tags it ON t.tagId = it.tagId
INNER JOIN photo_face_tags pft ON it.imageId = pft.imageId
INNER JOIN face_models fm ON pft.faceModelId = fm.id
INNER JOIN persons p ON fm.personId = p.id
WHERE p.relationship = :relationship
AND p.id != :excludePersonId
GROUP BY t.tagId
ORDER BY COUNT(it.imageId) DESC
LIMIT :limit
""")
suspend fun suggestTagsBasedOnRelationship(
relationship: String,
excludePersonId: String,
limit: Int
): List<TagEntity>
/**
* Get tags commonly used with this tag
*
* @param limit Maximum number of related tags
*/
@Query("""
SELECT DISTINCT t2.* FROM tags t2
INNER JOIN image_tags it2 ON t2.tagId = it2.tagId
WHERE it2.imageId IN (
SELECT it1.imageId FROM image_tags it1
WHERE it1.tagId = :tagId
)
AND t2.tagId != :tagId
GROUP BY t2.tagId
ORDER BY COUNT(it2.imageId) DESC
LIMIT :limit
""")
suspend fun getRelatedTags(
tagId: String,
limit: Int
): List<TagEntity>
// ======================
// SEARCH
// ======================
/**
* Search tags by value (partial match)
*
* @param limit Maximum number of results
*/
@Query("""
SELECT * FROM tags
WHERE value LIKE '%' || :query || '%'
ORDER BY value ASC
LIMIT :limit
""")
suspend fun searchTags(query: String, limit: Int): List<TagEntity>
/**
* Search tags with usage count
*
* @param limit Maximum number of results
*/
@Query("""
SELECT t.tagId, t.type, t.value, t.createdAt,
COUNT(it.imageId) as usage_count
FROM tags t
LEFT JOIN image_tags it ON t.tagId = it.tagId
WHERE t.value LIKE '%' || :query || '%'
GROUP BY t.tagId
ORDER BY usage_count DESC, t.value ASC
LIMIT :limit
""")
suspend fun searchTagsWithUsage(query: String, limit: Int): List<TagWithUsage>
// ==========================================
// STATISTICS QUERIES - ADDED FOR STATS SECTION
// ==========================================
/**
* Get system tag statistics (for utilities stats display)
* Returns tag value, type, and count of tagged images
*/
@Query("""
SELECT
t.value as tagValue,
t.type as tagType,
COUNT(DISTINCT it.imageId) as imageCount,
t.tagId as tagId
FROM tags t
INNER JOIN image_tags it ON t.tagId = it.tagId
WHERE t.type = 'SYSTEM'
GROUP BY t.tagId
ORDER BY imageCount DESC
""")
suspend fun getSystemTagStats(): List<TagStat>
/**
* Get system tag statistics (Flow version for reactive UI)
*/
@Query("""
SELECT
t.value as tagValue,
t.type as tagType,
COUNT(DISTINCT it.imageId) as imageCount,
t.tagId as tagId
FROM tags t
INNER JOIN image_tags it ON t.tagId = it.tagId
WHERE t.type = 'SYSTEM'
GROUP BY t.tagId
ORDER BY imageCount DESC
""")
fun getSystemTagStatsFlow(): Flow<List<TagStat>>
/**
* Get count of photos with a specific system tag
*/
@Query("""
SELECT COUNT(DISTINCT it.imageId)
FROM image_tags it
INNER JOIN tags t ON it.tagId = t.tagId
WHERE t.value = :tagValue AND t.type = 'SYSTEM'
""")
suspend fun getSystemTagCount(tagValue: String): Int
/**
* Get all tag types with counts
* Shows breakdown of SYSTEM vs USER vs GENERIC tags
*/
@Query("""
SELECT
t.type as tagValue,
t.type as tagType,
COUNT(DISTINCT t.tagId) as imageCount,
'' as tagId
FROM tags t
GROUP BY t.type
ORDER BY imageCount DESC
""")
suspend fun getTagTypeBreakdown(): List<TagStat>
}

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package com.placeholder.sherpai2.data.local.dao
import androidx.room.*
import com.placeholder.sherpai2.data.local.entity.FeedbackType
import com.placeholder.sherpai2.data.local.entity.UserFeedbackEntity
import kotlinx.coroutines.flow.Flow
/**
* UserFeedbackDao - Query user corrections and feedback
*
* KEY QUERIES:
* - Get feedback for cluster validation
* - Find rejected faces to exclude from training
* - Track feedback statistics for quality metrics
* - Support cluster refinement workflow
*/
@Dao
interface UserFeedbackDao {
// ═══════════════════════════════════════
// INSERT / UPDATE
// ═══════════════════════════════════════
@Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun insert(feedback: UserFeedbackEntity): Long
@Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun insertAll(feedbacks: List<UserFeedbackEntity>)
@Update
suspend fun update(feedback: UserFeedbackEntity)
@Delete
suspend fun delete(feedback: UserFeedbackEntity)
// ═══════════════════════════════════════
// CLUSTER VALIDATION QUERIES
// ═══════════════════════════════════════
/**
* Get all feedback for a cluster
* Used during validation to see what user has reviewed
*/
@Query("SELECT * FROM user_feedback WHERE clusterId = :clusterId ORDER BY timestamp DESC")
suspend fun getFeedbackForCluster(clusterId: Int): List<UserFeedbackEntity>
/**
* Get rejected faces for a cluster
* These faces should be EXCLUDED from training
*/
@Query("""
SELECT * FROM user_feedback
WHERE clusterId = :clusterId
AND feedbackType = 'REJECTED_MATCH'
""")
suspend fun getRejectedFacesForCluster(clusterId: Int): List<UserFeedbackEntity>
/**
* Get confirmed faces for a cluster
* These faces are SAFE for training
*/
@Query("""
SELECT * FROM user_feedback
WHERE clusterId = :clusterId
AND feedbackType = 'CONFIRMED_MATCH'
""")
suspend fun getConfirmedFacesForCluster(clusterId: Int): List<UserFeedbackEntity>
/**
* Count feedback by type for a cluster
* Used to show stats: "15 confirmed, 3 rejected"
*/
@Query("""
SELECT feedbackType, COUNT(*) as count
FROM user_feedback
WHERE clusterId = :clusterId
GROUP BY feedbackType
""")
suspend fun getFeedbackStatsByCluster(clusterId: Int): List<FeedbackStat>
// ═══════════════════════════════════════
// PERSON FEEDBACK QUERIES
// ═══════════════════════════════════════
/**
* Get all feedback for a person
* Used to show history of corrections
*/
@Query("SELECT * FROM user_feedback WHERE personId = :personId ORDER BY timestamp DESC")
suspend fun getFeedbackForPerson(personId: String): List<UserFeedbackEntity>
/**
* Get rejected faces for a person
* User said "this is NOT X" - exclude from model improvement
*/
@Query("""
SELECT * FROM user_feedback
WHERE personId = :personId
AND feedbackType = 'REJECTED_MATCH'
""")
suspend fun getRejectedFacesForPerson(personId: String): List<UserFeedbackEntity>
/**
* Flow version for reactive UI
*/
@Query("SELECT * FROM user_feedback WHERE personId = :personId ORDER BY timestamp DESC")
fun observeFeedbackForPerson(personId: String): Flow<List<UserFeedbackEntity>>
// ═══════════════════════════════════════
// IMAGE QUERIES
// ═══════════════════════════════════════
/**
* Get feedback for a specific image
*/
@Query("SELECT * FROM user_feedback WHERE imageId = :imageId")
suspend fun getFeedbackForImage(imageId: String): List<UserFeedbackEntity>
/**
* Check if user has provided feedback for a specific face
*/
@Query("""
SELECT EXISTS(
SELECT 1 FROM user_feedback
WHERE imageId = :imageId
AND faceIndex = :faceIndex
)
""")
suspend fun hasFeedbackForFace(imageId: String, faceIndex: Int): Boolean
// ═══════════════════════════════════════
// STATISTICS & ANALYTICS
// ═══════════════════════════════════════
/**
* Get total feedback count
*/
@Query("SELECT COUNT(*) FROM user_feedback")
suspend fun getTotalFeedbackCount(): Int
/**
* Get feedback count by type (global)
*/
@Query("""
SELECT feedbackType, COUNT(*) as count
FROM user_feedback
GROUP BY feedbackType
""")
suspend fun getGlobalFeedbackStats(): List<FeedbackStat>
/**
* Get average original confidence for rejected faces
* Helps identify if low confidence → more rejections
*/
@Query("""
SELECT AVG(originalConfidence)
FROM user_feedback
WHERE feedbackType = 'REJECTED_MATCH'
""")
suspend fun getAverageConfidenceForRejectedFaces(): Float?
/**
* Find faces with low confidence that were confirmed
* These are "surprising successes" - model worked despite low confidence
*/
@Query("""
SELECT * FROM user_feedback
WHERE feedbackType = 'CONFIRMED_MATCH'
AND originalConfidence < :threshold
ORDER BY originalConfidence ASC
""")
suspend fun getLowConfidenceSuccesses(threshold: Float = 0.7f): List<UserFeedbackEntity>
// ═══════════════════════════════════════
// CLEANUP
// ═══════════════════════════════════════
/**
* Delete all feedback for a cluster
* Called when cluster is deleted or refined
*/
@Query("DELETE FROM user_feedback WHERE clusterId = :clusterId")
suspend fun deleteFeedbackForCluster(clusterId: Int)
/**
* Delete all feedback for a person
* Called when person is deleted
*/
@Query("DELETE FROM user_feedback WHERE personId = :personId")
suspend fun deleteFeedbackForPerson(personId: String)
/**
* Delete old feedback (older than X days)
* Keep database size manageable
*/
@Query("DELETE FROM user_feedback WHERE timestamp < :cutoffTimestamp")
suspend fun deleteOldFeedback(cutoffTimestamp: Long)
/**
* Clear all feedback (nuclear option)
*/
@Query("DELETE FROM user_feedback")
suspend fun deleteAll()
}
/**
* Result class for feedback statistics
*/
data class FeedbackStat(
val feedbackType: String,
val count: Int
)

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package com.placeholder.sherpai2.data.local.entity
import androidx.room.Entity
import androidx.room.Index
import androidx.room.PrimaryKey
import java.util.UUID
/**
* CollectionEntity - User-created photo collections
*
* Types:
* - SMART: Dynamic collection based on filters (re-evaluated)
* - STATIC: Fixed snapshot of photos
* - FAVORITE: Special favorites collection
*/
@Entity(
tableName = "collections",
indices = [
Index(value = ["name"]),
Index(value = ["type"]),
Index(value = ["createdAt"])
]
)
data class CollectionEntity(
@PrimaryKey
val collectionId: String,
val name: String,
val description: String?,
/**
* Cover image (auto-selected or user-chosen)
*/
val coverImageUri: String?,
/**
* SMART | STATIC | FAVORITE
*/
val type: String,
/**
* Cached photo count for performance
*/
val photoCount: Int,
val createdAt: Long,
val updatedAt: Long,
/**
* Pinned to top of collections list
*/
val isPinned: Boolean
) {
companion object {
fun createSmart(
name: String,
description: String? = null
): CollectionEntity {
val now = System.currentTimeMillis()
return CollectionEntity(
collectionId = UUID.randomUUID().toString(),
name = name,
description = description,
coverImageUri = null,
type = "SMART",
photoCount = 0,
createdAt = now,
updatedAt = now,
isPinned = false
)
}
fun createStatic(
name: String,
description: String? = null,
photoCount: Int = 0
): CollectionEntity {
val now = System.currentTimeMillis()
return CollectionEntity(
collectionId = UUID.randomUUID().toString(),
name = name,
description = description,
coverImageUri = null,
type = "STATIC",
photoCount = photoCount,
createdAt = now,
updatedAt = now,
isPinned = false
)
}
fun createFavorite(): CollectionEntity {
val now = System.currentTimeMillis()
return CollectionEntity(
collectionId = "favorites",
name = "Favorites",
description = "Your favorite photos",
coverImageUri = null,
type = "FAVORITE",
photoCount = 0,
createdAt = now,
updatedAt = now,
isPinned = true
)
}
}
}

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package com.placeholder.sherpai2.data.local.entity
import androidx.room.Entity
import androidx.room.ForeignKey
import androidx.room.Index
import androidx.room.PrimaryKey
import java.util.UUID
/**
* CollectionFilterEntity - Filters for SMART collections
*
* Filter Types:
* - PERSON_INCLUDE: Person must be in photo
* - PERSON_EXCLUDE: Person must NOT be in photo
* - TAG_INCLUDE: Tag must be present
* - TAG_EXCLUDE: Tag must NOT be present
* - DATE_RANGE: Date filter (TODAY, THIS_WEEK, etc)
*/
@Entity(
tableName = "collection_filters",
foreignKeys = [
ForeignKey(
entity = CollectionEntity::class,
parentColumns = ["collectionId"],
childColumns = ["collectionId"],
onDelete = ForeignKey.CASCADE
)
],
indices = [
Index("collectionId"),
Index("filterType")
]
)
data class CollectionFilterEntity(
@PrimaryKey
val filterId: String,
val collectionId: String,
/**
* PERSON_INCLUDE | PERSON_EXCLUDE | TAG_INCLUDE | TAG_EXCLUDE | DATE_RANGE
*/
val filterType: String,
/**
* The filter value:
* - For PERSON_*: personId
* - For TAG_*: tag value
* - For DATE_RANGE: "TODAY", "THIS_WEEK", etc
*/
val filterValue: String,
val createdAt: Long
) {
companion object {
fun create(
collectionId: String,
filterType: String,
filterValue: String
): CollectionFilterEntity {
return CollectionFilterEntity(
filterId = UUID.randomUUID().toString(),
collectionId = collectionId,
filterType = filterType,
filterValue = filterValue,
createdAt = System.currentTimeMillis()
)
}
}
}

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package com.placeholder.sherpai2.data.local.entity
import androidx.room.Entity
import androidx.room.ForeignKey
import androidx.room.Index
/**
* CollectionImageEntity - Join table linking collections to images
*
* Supports:
* - Custom sort order
* - Timestamp when added
*/
@Entity(
tableName = "collection_images",
primaryKeys = ["collectionId", "imageId"],
foreignKeys = [
ForeignKey(
entity = CollectionEntity::class,
parentColumns = ["collectionId"],
childColumns = ["collectionId"],
onDelete = ForeignKey.CASCADE
),
ForeignKey(
entity = ImageEntity::class,
parentColumns = ["imageId"],
childColumns = ["imageId"],
onDelete = ForeignKey.CASCADE
)
],
indices = [
Index("collectionId"),
Index("imageId"),
Index("addedAt")
]
)
data class CollectionImageEntity(
val collectionId: String,
val imageId: String,
/**
* When this image was added to the collection
*/
val addedAt: Long,
/**
* Custom sort order (lower = earlier)
*/
val sortOrder: Int
)

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package com.placeholder.sherpai2.data.local.entity
import androidx.room.Entity
import androidx.room.Index
import androidx.room.PrimaryKey
/**
* Represents a meaningful event spanning a time range.
*
* Events allow auto-association of images by timestamp.
*/
@Entity(
tableName = "events",
indices = [
Index(value = ["startDate"]),
Index(value = ["endDate"])
]
)
data class EventEntity(
@PrimaryKey
val eventId: String,
val name: String,
/**
* Inclusive start date (UTC millis).
*/
val startDate: Long,
/**
* Inclusive end date (UTC millis).
*/
val endDate: Long,
val location: String?,
/**
* 0.0 1.0 importance weight
*/
val importance: Float,
val isHidden: Boolean
)

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package com.placeholder.sherpai2.data.local.entity
import androidx.room.ColumnInfo
import androidx.room.Entity
import androidx.room.ForeignKey
import androidx.room.Index
import androidx.room.PrimaryKey
import java.util.UUID
/**
* FaceCacheEntity - Per-face metadata for intelligent filtering
*
* PURPOSE: Store face quality metrics during initial cache population
* BENEFIT: Pre-filter to high-quality faces BEFORE clustering
*
* ENABLES QUERIES LIKE:
* - "Give me all solo photos with large, clear faces"
* - "Filter to faces that are > 15% of image"
* - "Exclude blurry/distant/profile faces"
*
* POPULATED BY: PopulateFaceDetectionCacheUseCase (enhanced version)
* USED BY: FaceClusteringService for smart photo selection
*/
@Entity(
tableName = "face_cache",
foreignKeys = [
ForeignKey(
entity = ImageEntity::class,
parentColumns = ["imageId"],
childColumns = ["imageId"],
onDelete = ForeignKey.CASCADE
)
],
indices = [
Index(value = ["imageId"]),
Index(value = ["faceIndex"]),
Index(value = ["faceAreaRatio"]),
Index(value = ["qualityScore"]),
Index(value = ["imageId", "faceIndex"], unique = true)
]
)
data class FaceCacheEntity(
@PrimaryKey
@ColumnInfo(name = "id")
val id: String = UUID.randomUUID().toString(),
@ColumnInfo(name = "imageId")
val imageId: String,
@ColumnInfo(name = "faceIndex")
val faceIndex: Int, // 0-based index for multiple faces in image
// FACE METRICS (for filtering)
@ColumnInfo(name = "boundingBox")
val boundingBox: String, // "left,top,right,bottom"
@ColumnInfo(name = "faceWidth")
val faceWidth: Int, // pixels
@ColumnInfo(name = "faceHeight")
val faceHeight: Int, // pixels
@ColumnInfo(name = "faceAreaRatio")
val faceAreaRatio: Float, // face area / image area (0.0 - 1.0)
@ColumnInfo(name = "imageWidth")
val imageWidth: Int, // Full image width
@ColumnInfo(name = "imageHeight")
val imageHeight: Int, // Full image height
// QUALITY INDICATORS
@ColumnInfo(name = "qualityScore")
val qualityScore: Float, // 0.0-1.0 (combines size + clarity + angle)
@ColumnInfo(name = "isLargeEnough")
val isLargeEnough: Boolean, // faceAreaRatio >= 0.15 AND min 200x200px
@ColumnInfo(name = "isFrontal")
val isFrontal: Boolean, // Face angle roughly frontal (from ML Kit)
@ColumnInfo(name = "hasGoodLighting")
val hasGoodLighting: Boolean, // Not too dark/bright (heuristic)
// EMBEDDING (optional - for super fast clustering)
@ColumnInfo(name = "embedding")
val embedding: String?, // Pre-computed 192D embedding (comma-separated)
// METADATA
@ColumnInfo(name = "confidence")
val confidence: Float, // ML Kit detection confidence
@ColumnInfo(name = "detectedAt")
val detectedAt: Long = System.currentTimeMillis(),
@ColumnInfo(name = "cacheVersion")
val cacheVersion: Int = CURRENT_CACHE_VERSION
) {
companion object {
const val CURRENT_CACHE_VERSION = 1
/**
* Create from ML Kit face detection result
*/
fun create(
imageId: String,
faceIndex: Int,
boundingBox: android.graphics.Rect,
imageWidth: Int,
imageHeight: Int,
confidence: Float,
isFrontal: Boolean,
embedding: FloatArray? = null
): FaceCacheEntity {
val faceWidth = boundingBox.width()
val faceHeight = boundingBox.height()
val faceArea = faceWidth * faceHeight
val imageArea = imageWidth * imageHeight
val faceAreaRatio = faceArea.toFloat() / imageArea.toFloat()
// Calculate quality score
val sizeScore = (faceAreaRatio * 5).coerceIn(0f, 1f) // 20% = perfect
val pixelScore = if (faceWidth >= 200 && faceHeight >= 200) 1f else 0.5f
val angleScore = if (isFrontal) 1f else 0.7f
val qualityScore = (sizeScore + pixelScore + angleScore) / 3f
val isLargeEnough = faceAreaRatio >= 0.15f && faceWidth >= 200 && faceHeight >= 200
return FaceCacheEntity(
imageId = imageId,
faceIndex = faceIndex,
boundingBox = "${boundingBox.left},${boundingBox.top},${boundingBox.right},${boundingBox.bottom}",
faceWidth = faceWidth,
faceHeight = faceHeight,
faceAreaRatio = faceAreaRatio,
imageWidth = imageWidth,
imageHeight = imageHeight,
qualityScore = qualityScore,
isLargeEnough = isLargeEnough,
isFrontal = isFrontal,
hasGoodLighting = true, // TODO: Implement lighting analysis
embedding = embedding?.joinToString(","),
confidence = confidence
)
}
}
fun getBoundingBox(): android.graphics.Rect {
val parts = boundingBox.split(",").map { it.toInt() }
return android.graphics.Rect(parts[0], parts[1], parts[2], parts[3])
}
fun getEmbedding(): FloatArray? {
return embedding?.split(",")?.map { it.toFloat() }?.toFloatArray()
}
}

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package com.placeholder.sherpai2.data.local.entity
import androidx.room.ColumnInfo
import androidx.room.Entity
import androidx.room.ForeignKey
import androidx.room.Index
import androidx.room.PrimaryKey
import org.json.JSONArray
import org.json.JSONObject
import java.util.UUID
/**
* PersonEntity - ENHANCED with child tracking and sibling relationships
*/
@Entity(
tableName = "persons",
indices = [
Index(value = ["name"]),
Index(value = ["familyGroupId"])
]
)
data class PersonEntity(
@PrimaryKey
@ColumnInfo(name = "id")
val id: String,
@ColumnInfo(name = "name")
val name: String,
@ColumnInfo(name = "dateOfBirth")
val dateOfBirth: Long?,
@ColumnInfo(name = "isChild")
val isChild: Boolean, // NEW: Auto-set based on age
@ColumnInfo(name = "siblingIds")
val siblingIds: String?, // NEW: JSON list ["uuid1", "uuid2"]
@ColumnInfo(name = "familyGroupId")
val familyGroupId: String?, // NEW: UUID for family unit
@ColumnInfo(name = "relationship")
val relationship: String?,
@ColumnInfo(name = "createdAt")
val createdAt: Long,
@ColumnInfo(name = "updatedAt")
val updatedAt: Long
) {
companion object {
fun create(
name: String,
dateOfBirth: Long? = null,
isChild: Boolean = false,
siblingIds: List<String> = emptyList(),
relationship: String? = null
): PersonEntity {
val now = System.currentTimeMillis()
// Create family group if siblings exist
val familyGroupId = if (siblingIds.isNotEmpty()) {
UUID.randomUUID().toString()
} else null
return PersonEntity(
id = UUID.randomUUID().toString(),
name = name,
dateOfBirth = dateOfBirth,
isChild = isChild,
siblingIds = if (siblingIds.isNotEmpty()) {
JSONArray(siblingIds).toString()
} else null,
familyGroupId = familyGroupId,
relationship = relationship,
createdAt = now,
updatedAt = now
)
}
}
fun getSiblingIds(): List<String> {
return if (siblingIds != null) {
try {
val jsonArray = JSONArray(siblingIds)
(0 until jsonArray.length()).map { jsonArray.getString(it) }
} catch (e: Exception) {
emptyList()
}
} else emptyList()
}
fun getAge(): Int? {
if (dateOfBirth == null) return null
val now = System.currentTimeMillis()
val ageInMillis = now - dateOfBirth
return (ageInMillis / (1000L * 60 * 60 * 24 * 365)).toInt()
}
fun getRelationshipEmoji(): String {
return when (relationship) {
"Family" -> "👨‍👩‍👧‍👦"
"Friend" -> "🤝"
"Partner" -> "❤️"
"Child" -> "👶"
"Parent" -> "👪"
"Sibling" -> "👫"
"Colleague" -> "💼"
else -> "👤"
}
}
}
/**
* FaceModelEntity - MULTI-CENTROID support for temporal tracking
*/
@Entity(
tableName = "face_models",
foreignKeys = [
ForeignKey(
entity = PersonEntity::class,
parentColumns = ["id"],
childColumns = ["personId"],
onDelete = ForeignKey.CASCADE
)
],
indices = [Index(value = ["personId"], unique = true)]
)
data class FaceModelEntity(
@PrimaryKey
@ColumnInfo(name = "id")
val id: String,
@ColumnInfo(name = "personId")
val personId: String,
@ColumnInfo(name = "centroidsJson")
val centroidsJson: String, // NEW: List<TemporalCentroid> as JSON
@ColumnInfo(name = "trainingImageCount")
val trainingImageCount: Int,
@ColumnInfo(name = "averageConfidence")
val averageConfidence: Float,
@ColumnInfo(name = "createdAt")
val createdAt: Long,
@ColumnInfo(name = "updatedAt")
val updatedAt: Long,
@ColumnInfo(name = "lastUsed")
val lastUsed: Long?,
@ColumnInfo(name = "isActive")
val isActive: Boolean
) {
companion object {
/**
* Backwards compatible create() method
* Used by existing FaceRecognitionRepository code
*/
fun create(
personId: String,
embeddingArray: FloatArray,
trainingImageCount: Int,
averageConfidence: Float
): FaceModelEntity {
return createFromEmbedding(personId, embeddingArray, trainingImageCount, averageConfidence)
}
/**
* Create from single embedding (backwards compatible)
*/
fun createFromEmbedding(
personId: String,
embeddingArray: FloatArray,
trainingImageCount: Int,
averageConfidence: Float
): FaceModelEntity {
val now = System.currentTimeMillis()
val centroid = TemporalCentroid(
embedding = embeddingArray.toList(),
effectiveTimestamp = now,
ageAtCapture = null,
photoCount = trainingImageCount,
timeRangeMonths = 12,
avgConfidence = averageConfidence
)
return FaceModelEntity(
id = UUID.randomUUID().toString(),
personId = personId,
centroidsJson = serializeCentroids(listOf(centroid)),
trainingImageCount = trainingImageCount,
averageConfidence = averageConfidence,
createdAt = now,
updatedAt = now,
lastUsed = null,
isActive = true
)
}
/**
* Create from multiple centroids (temporal tracking)
*/
fun createFromCentroids(
personId: String,
centroids: List<TemporalCentroid>,
trainingImageCount: Int,
averageConfidence: Float
): FaceModelEntity {
val now = System.currentTimeMillis()
return FaceModelEntity(
id = UUID.randomUUID().toString(),
personId = personId,
centroidsJson = serializeCentroids(centroids),
trainingImageCount = trainingImageCount,
averageConfidence = averageConfidence,
createdAt = now,
updatedAt = now,
lastUsed = null,
isActive = true
)
}
/**
* Serialize list of centroids to JSON
*/
private fun serializeCentroids(centroids: List<TemporalCentroid>): String {
val jsonArray = JSONArray()
centroids.forEach { centroid ->
val jsonObj = JSONObject()
jsonObj.put("embedding", JSONArray(centroid.embedding))
jsonObj.put("effectiveTimestamp", centroid.effectiveTimestamp)
jsonObj.put("ageAtCapture", centroid.ageAtCapture)
jsonObj.put("photoCount", centroid.photoCount)
jsonObj.put("timeRangeMonths", centroid.timeRangeMonths)
jsonObj.put("avgConfidence", centroid.avgConfidence)
jsonArray.put(jsonObj)
}
return jsonArray.toString()
}
/**
* Deserialize JSON to list of centroids
*/
private fun deserializeCentroids(json: String): List<TemporalCentroid> {
val jsonArray = JSONArray(json)
return (0 until jsonArray.length()).map { i ->
val jsonObj = jsonArray.getJSONObject(i)
val embeddingArray = jsonObj.getJSONArray("embedding")
val embedding = (0 until embeddingArray.length()).map { j ->
embeddingArray.getDouble(j).toFloat()
}
TemporalCentroid(
embedding = embedding,
effectiveTimestamp = jsonObj.getLong("effectiveTimestamp"),
ageAtCapture = if (jsonObj.isNull("ageAtCapture")) null else jsonObj.getDouble("ageAtCapture").toFloat(),
photoCount = jsonObj.getInt("photoCount"),
timeRangeMonths = jsonObj.getInt("timeRangeMonths"),
avgConfidence = jsonObj.getDouble("avgConfidence").toFloat()
)
}
}
}
fun getCentroids(): List<TemporalCentroid> {
return try {
FaceModelEntity.deserializeCentroids(centroidsJson)
} catch (e: Exception) {
emptyList()
}
}
// Backwards compatibility: get first centroid as single embedding
fun getEmbeddingArray(): FloatArray {
val centroids = getCentroids()
return if (centroids.isNotEmpty()) {
centroids.first().getEmbeddingArray()
} else {
FloatArray(192) // Empty embedding
}
}
}
/**
* TemporalCentroid - Represents a face appearance at a specific time period
*/
data class TemporalCentroid(
val embedding: List<Float>, // 192D vector
val effectiveTimestamp: Long, // Center of time window
val ageAtCapture: Float?, // Age in years (for children)
val photoCount: Int, // Number of photos in this cluster
val timeRangeMonths: Int, // Width of time window (e.g., 6 months)
val avgConfidence: Float // Quality indicator
) {
fun getEmbeddingArray(): FloatArray = embedding.toFloatArray()
}
/**
* PhotoFaceTagEntity - Unchanged
*/
@Entity(
tableName = "photo_face_tags",
foreignKeys = [
ForeignKey(
entity = ImageEntity::class,
parentColumns = ["imageId"],
childColumns = ["imageId"],
onDelete = ForeignKey.CASCADE
),
ForeignKey(
entity = FaceModelEntity::class,
parentColumns = ["id"],
childColumns = ["faceModelId"],
onDelete = ForeignKey.CASCADE
)
],
indices = [
Index(value = ["imageId"]),
Index(value = ["faceModelId"]),
Index(value = ["imageId", "faceModelId"])
]
)
data class PhotoFaceTagEntity(
@PrimaryKey
@ColumnInfo(name = "id")
val id: String,
@ColumnInfo(name = "imageId")
val imageId: String,
@ColumnInfo(name = "faceModelId")
val faceModelId: String,
@ColumnInfo(name = "boundingBox")
val boundingBox: String,
@ColumnInfo(name = "confidence")
val confidence: Float,
@ColumnInfo(name = "embedding")
val embedding: String,
@ColumnInfo(name = "detectedAt")
val detectedAt: Long,
@ColumnInfo(name = "verifiedByUser")
val verifiedByUser: Boolean,
@ColumnInfo(name = "verifiedAt")
val verifiedAt: Long?
) {
companion object {
fun create(
imageId: String,
faceModelId: String,
boundingBox: android.graphics.Rect,
confidence: Float,
faceEmbedding: FloatArray
): PhotoFaceTagEntity {
return PhotoFaceTagEntity(
id = UUID.randomUUID().toString(),
imageId = imageId,
faceModelId = faceModelId,
boundingBox = "${boundingBox.left},${boundingBox.top},${boundingBox.right},${boundingBox.bottom}",
confidence = confidence,
embedding = faceEmbedding.joinToString(","),
detectedAt = System.currentTimeMillis(),
verifiedByUser = false,
verifiedAt = null
)
}
}
fun getBoundingBox(): android.graphics.Rect {
val parts = boundingBox.split(",").map { it.toInt() }
return android.graphics.Rect(parts[0], parts[1], parts[2], parts[3])
}
fun getEmbeddingArray(): FloatArray {
return embedding.split(",").map { it.toFloat() }.toFloatArray()
}
}
/**
* PersonAgeTagEntity - NEW: Searchable age tags
*/
@Entity(
tableName = "person_age_tags",
foreignKeys = [
ForeignKey(
entity = PersonEntity::class,
parentColumns = ["id"],
childColumns = ["personId"],
onDelete = ForeignKey.CASCADE
),
ForeignKey(
entity = ImageEntity::class,
parentColumns = ["imageId"],
childColumns = ["imageId"],
onDelete = ForeignKey.CASCADE
)
],
indices = [
Index(value = ["personId"]),
Index(value = ["imageId"]),
Index(value = ["ageAtCapture"]),
Index(value = ["tagValue"])
]
)
data class PersonAgeTagEntity(
@PrimaryKey
@ColumnInfo(name = "id")
val id: String,
@ColumnInfo(name = "personId")
val personId: String,
@ColumnInfo(name = "imageId")
val imageId: String,
@ColumnInfo(name = "ageAtCapture")
val ageAtCapture: Int,
@ColumnInfo(name = "tagValue")
val tagValue: String, // e.g., "emma_age3"
@ColumnInfo(name = "confidence")
val confidence: Float,
@ColumnInfo(name = "createdAt")
val createdAt: Long
) {
companion object {
fun create(
personId: String,
personName: String,
imageId: String,
ageAtCapture: Int,
confidence: Float
): PersonAgeTagEntity {
return PersonAgeTagEntity(
id = UUID.randomUUID().toString(),
personId = personId,
imageId = imageId,
ageAtCapture = ageAtCapture,
tagValue = "${personName.lowercase().replace(" ", "_")}_age$ageAtCapture",
confidence = confidence,
createdAt = System.currentTimeMillis()
)
}
}
}

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package com.placeholder.sherpai2.data.local.entity
import androidx.room.Entity
import androidx.room.Index
import androidx.room.PrimaryKey
/**
* Represents a single image on the device.
*
* This entity is intentionally immutable (mostly):
* - imageUri identifies where the image lives
* - sha256 prevents duplicates
* - capturedAt is the EXIF timestamp
*
* FACE DETECTION CACHE (mutable for performance):
* - hasFaces: Boolean flag to skip images without faces
* - faceCount: Number of faces detected (0 if no faces)
* - facesLastDetected: Timestamp of last face detection
* - faceDetectionVersion: Version number for cache invalidation
*
* These fields are populated during:
* 1. Initial model training (already detecting faces)
* 2. Utility scans (burst detection, quality analysis)
* 3. Any face detection operation
* 4. Background maintenance scans
*/
@Entity(
tableName = "images",
indices = [
Index(value = ["imageUri"], unique = true),
Index(value = ["sha256"], unique = true),
Index(value = ["capturedAt"]),
Index(value = ["hasFaces"]), // NEW: For fast filtering
Index(value = ["faceCount"]) // NEW: For range queries (singles, couples, groups)
]
)
data class ImageEntity(
@PrimaryKey
val imageId: String,
val imageUri: String,
/**
* Cryptographic hash of image bytes.
* Used for deduplication and re-indexing.
*/
val sha256: String,
/**
* EXIF timestamp (UTC millis).
*/
val capturedAt: Long,
/**
* When this image was indexed into the app.
*/
val ingestedAt: Long,
val width: Int,
val height: Int,
/**
* CAMERA | SCREENSHOT | IMPORTED
*/
val source: String,
// ============================================================================
// FACE DETECTION CACHE - Populated asynchronously
// ============================================================================
/**
* Whether this image contains any faces.
* - true: At least one face detected
* - false: No faces detected
* - null: Not yet scanned (default for newly ingested images)
*
* Use this to skip images without faces during person scanning.
*/
val hasFaces: Boolean? = null,
/**
* Number of faces detected in this image.
* - 0: No faces
* - 1: Solo person (useful for filtering)
* - 2: Couple (useful for filtering)
* - 3+: Group photo (useful for filtering)
* - null: Not yet scanned
*
* Use this for:
* - Finding solo photos of a person
* - Identifying couple photos
* - Filtering out group photos if needed
*/
val faceCount: Int? = null,
/**
* Timestamp when faces were last detected in this image.
* Used for cache invalidation logic.
*
* Invalidate cache if:
* - Image modified date > facesLastDetected
* - faceDetectionVersion < current version
*/
val facesLastDetected: Long? = null,
/**
* Face detection algorithm version.
* Increment this when improving face detection to invalidate old cache.
*
* Current version: 1
* - If detection algorithm improves, increment to 2
* - Query will re-scan images with version < 2
*/
val faceDetectionVersion: Int? = null
) {
companion object {
/**
* Current face detection algorithm version.
* Increment when making significant improvements to face detection.
*/
const val CURRENT_FACE_DETECTION_VERSION = 1
/**
* Check if face detection cache is valid.
* Invalid if:
* - Never scanned (hasFaces == null)
* - Old detection version
* - Image modified after detection (would need file system check)
*/
fun isFaceDetectionCacheValid(image: ImageEntity): Boolean {
return image.hasFaces != null &&
image.faceDetectionVersion == CURRENT_FACE_DETECTION_VERSION
}
}
/**
* Check if this image needs face detection scanning.
*/
fun needsFaceDetection(): Boolean {
return hasFaces == null ||
faceDetectionVersion == null ||
faceDetectionVersion < CURRENT_FACE_DETECTION_VERSION
}
/**
* Check if this image definitely has faces (cached).
*/
fun hasCachedFaces(): Boolean {
return hasFaces == true && !needsFaceDetection()
}
/**
* Check if this image definitely has no faces (cached).
*/
fun hasCachedNoFaces(): Boolean {
return hasFaces == false && !needsFaceDetection()
}
/**
* Get a copy with updated face detection cache.
*/
fun withFaceDetectionCache(
hasFaces: Boolean,
faceCount: Int,
timestamp: Long = System.currentTimeMillis()
): ImageEntity {
return copy(
hasFaces = hasFaces,
faceCount = faceCount,
facesLastDetected = timestamp,
faceDetectionVersion = CURRENT_FACE_DETECTION_VERSION
)
}
}

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package com.placeholder.sherpai2.data.local.entity
import androidx.room.Entity
import androidx.room.ForeignKey
import androidx.room.Index
@Entity(
tableName = "image_events",
primaryKeys = ["imageId", "eventId"],
foreignKeys = [
ForeignKey(
entity = ImageEntity::class,
parentColumns = ["imageId"],
childColumns = ["imageId"],
onDelete = ForeignKey.CASCADE
),
ForeignKey(
entity = EventEntity::class,
parentColumns = ["eventId"],
childColumns = ["eventId"],
onDelete = ForeignKey.CASCADE
)
],
indices = [
Index("eventId")
]
)
data class ImageEventEntity(
val imageId: String,
val eventId: String,
/**
* AUTO | MANUAL
*/
val source: String,
/**
* User override flag.
*/
val override: Boolean
)

View File

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package com.placeholder.sherpai2.data.local.entity
import androidx.room.Entity
import androidx.room.ForeignKey
import androidx.room.Index
/**
* Join table linking images to tags.
*
* This is NOT optional.
* Do not inline tag lists on ImageEntity.
*/
@Entity(
tableName = "image_tags",
primaryKeys = ["imageId", "tagId"],
foreignKeys = [
ForeignKey(
entity = ImageEntity::class,
parentColumns = ["imageId"],
childColumns = ["imageId"],
onDelete = ForeignKey.CASCADE
),
ForeignKey(
entity = TagEntity::class,
parentColumns = ["tagId"],
childColumns = ["tagId"],
onDelete = ForeignKey.CASCADE
)
],
indices = [
Index("tagId"),
Index("imageId")
]
)
data class ImageTagEntity(
val imageId: String,
val tagId: String,
/**
* AUTO | MANUAL
*/
val source: String,
/**
* ML confidence (01).
*/
val confidence: Float,
/**
* PUBLIC | PRIVATE | HIDDEN
*/
val visibility: String,
val createdAt: Long
)

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package com.placeholder.sherpai2.data.local.entity
import androidx.room.ColumnInfo
import androidx.room.Entity
import androidx.room.PrimaryKey
import java.util.UUID
/**
* Tag type constants - MUST be defined BEFORE TagEntity
* to avoid KSP initialization order issues
*/
object TagType {
const val GENERIC = "GENERIC" // User tags
const val SYSTEM = "SYSTEM" // AI/auto tags
const val HIDDEN = "HIDDEN" // Internal
}
/**
* Common system tag values
*/
object SystemTags {
const val HAS_FACES = "has_faces"
const val MULTIPLE_PEOPLE = "multiple_people"
const val LANDSCAPE = "landscape"
const val PORTRAIT = "portrait"
const val LOW_QUALITY = "low_quality"
const val BLURRY = "blurry"
}
/**
* TagEntity - Normalized tag storage
*
* EXPLICIT COLUMN MAPPINGS for KSP compatibility
*/
@Entity(tableName = "tags")
data class TagEntity(
@PrimaryKey
@ColumnInfo(name = "tagId")
val tagId: String,
@ColumnInfo(name = "type")
val type: String,
@ColumnInfo(name = "value")
val value: String,
@ColumnInfo(name = "createdAt")
val createdAt: Long
) {
companion object {
/**
* Create a generic user tag
*/
fun createUserTag(value: String): TagEntity {
return TagEntity(
tagId = UUID.randomUUID().toString(),
type = TagType.GENERIC,
value = value.trim().lowercase(),
createdAt = System.currentTimeMillis()
)
}
/**
* Create a system tag (auto-generated)
*/
fun createSystemTag(value: String): TagEntity {
return TagEntity(
tagId = UUID.randomUUID().toString(),
type = TagType.SYSTEM,
value = value.trim().lowercase(),
createdAt = System.currentTimeMillis()
)
}
/**
* Create hidden tag (internal use)
*/
fun createHiddenTag(value: String): TagEntity {
return TagEntity(
tagId = UUID.randomUUID().toString(),
type = TagType.HIDDEN,
value = value.trim().lowercase(),
createdAt = System.currentTimeMillis()
)
}
}
/**
* Check if this is a user-created tag
*/
fun isUserTag(): Boolean = type == TagType.GENERIC
/**
* Check if this is a system tag
*/
fun isSystemTag(): Boolean = type == TagType.SYSTEM
/**
* Check if this is a hidden tag
*/
fun isHiddenTag(): Boolean = type == TagType.HIDDEN
/**
* Get display value (capitalized for UI)
*/
fun getDisplayValue(): String = value.replaceFirstChar { it.uppercase() }
}
/**
* TagWithUsage - For queries that include usage count
*
* NOT AN ENTITY - just a POJO for query results
* Do NOT add this to @Database entities list!
*/
data class TagWithUsage(
@ColumnInfo(name = "tagId")
val tagId: String,
@ColumnInfo(name = "type")
val type: String,
@ColumnInfo(name = "value")
val value: String,
@ColumnInfo(name = "createdAt")
val createdAt: Long,
@ColumnInfo(name = "usage_count")
val usageCount: Int
) {
/**
* Convert to TagEntity (without usage count)
*/
fun toTagEntity(): TagEntity {
return TagEntity(
tagId = tagId,
type = type,
value = value,
createdAt = createdAt
)
}
}

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package com.placeholder.sherpai2.data.local.entity
import androidx.room.Entity
import androidx.room.ForeignKey
import androidx.room.Index
import androidx.room.PrimaryKey
import java.util.UUID
/**
* UserFeedbackEntity - Stores user corrections during cluster validation
*
* PURPOSE:
* - Capture which faces user marked as correct/incorrect
* - Ground truth data for improving clustering
* - Enable cluster refinement before training
* - Track confidence in automated detections
*
* USAGE FLOW:
* 1. Clustering creates initial clusters
* 2. User reviews ValidationPreview
* 3. User swipes faces: ✅ Correct / ❌ Incorrect
* 4. Feedback stored here
* 5. If too many incorrect → Re-cluster without those faces
* 6. If approved → Train model with confirmed faces only
*
* INDEXES:
* - imageId: Fast lookup of feedback for specific images
* - clusterId: Get all feedback for a cluster
* - feedbackType: Filter by correction type
* - personId: Track feedback after person created
*/
@Entity(
tableName = "user_feedback",
foreignKeys = [
ForeignKey(
entity = ImageEntity::class,
parentColumns = ["imageId"],
childColumns = ["imageId"],
onDelete = ForeignKey.CASCADE
),
ForeignKey(
entity = PersonEntity::class,
parentColumns = ["id"],
childColumns = ["personId"],
onDelete = ForeignKey.CASCADE
)
],
indices = [
Index(value = ["imageId"]),
Index(value = ["clusterId"]),
Index(value = ["personId"]),
Index(value = ["feedbackType"])
]
)
data class UserFeedbackEntity(
@PrimaryKey
val id: String = UUID.randomUUID().toString(),
/**
* Image containing the face
*/
val imageId: String,
/**
* Face index within the image (0-based)
* Multiple faces per image possible
*/
val faceIndex: Int,
/**
* Cluster ID from clustering (before person created)
* Null if feedback given after person exists
*/
val clusterId: Int?,
/**
* Person ID if feedback is about an existing person
* Null during initial cluster validation
*/
val personId: String?,
/**
* Type of feedback user provided
*/
val feedbackType: String, // FeedbackType enum stored as string
/**
* Confidence score that led to this face being shown
* Helps identify if low confidence = more errors
*/
val originalConfidence: Float,
/**
* Optional user note
*/
val userNote: String? = null,
/**
* When feedback was provided
*/
val timestamp: Long = System.currentTimeMillis()
) {
companion object {
fun create(
imageId: String,
faceIndex: Int,
clusterId: Int? = null,
personId: String? = null,
feedbackType: FeedbackType,
originalConfidence: Float,
userNote: String? = null
): UserFeedbackEntity {
return UserFeedbackEntity(
imageId = imageId,
faceIndex = faceIndex,
clusterId = clusterId,
personId = personId,
feedbackType = feedbackType.name,
originalConfidence = originalConfidence,
userNote = userNote
)
}
}
fun getFeedbackType(): FeedbackType {
return try {
FeedbackType.valueOf(feedbackType)
} catch (e: Exception) {
FeedbackType.UNCERTAIN
}
}
}
/**
* FeedbackType - Types of user corrections
*/
enum class FeedbackType {
/**
* User confirmed this face IS the person
* Boosts confidence, use for training
*/
CONFIRMED_MATCH,
/**
* User said this face is NOT the person
* Remove from cluster, exclude from training
*/
REJECTED_MATCH,
/**
* User marked as outlier during cluster review
* Face doesn't belong in this cluster
*/
MARKED_OUTLIER,
/**
* User is uncertain
* Skip this face for training, revisit later
*/
UNCERTAIN
}

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package com.placeholder.sherpai2.data.local.model
import androidx.room.ColumnInfo
import androidx.room.Embedded
import com.placeholder.sherpai2.data.local.entity.CollectionEntity
/**
* CollectionWithDetails - Collection with computed preview data
*
* Room maps this directly from query results
*/
data class CollectionWithDetails(
@Embedded
val collection: CollectionEntity,
@ColumnInfo(name = "actualPhotoCount")
val actualPhotoCount: Int
)

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package com.placeholder.sherpai2.data.local.model
import androidx.room.Embedded
import androidx.room.Junction
import androidx.room.Relation
import com.placeholder.sherpai2.data.local.entity.*
/**
* ImageWithEverything - Fully hydrated image with ALL relationships
*
* Room loads this in ONE query using @Transaction!
* NO N+1 problem - all tags and face tags loaded together
*
* Usage:
* - ImageAggregateDao.observeAllImagesWithEverything()
* - Search, Explore, Albums
*/
data class ImageWithEverything(
@Embedded
val image: ImageEntity,
/**
* Tags for this image (via image_tags join table)
* Room automatically joins through ImageTagEntity
*/
@Relation(
parentColumn = "imageId",
entityColumn = "tagId",
associateBy = Junction(
value = ImageTagEntity::class,
parentColumn = "imageId",
entityColumn = "tagId"
)
)
val tags: List<TagEntity>,
/**
* Face tags for this image
* Room automatically loads all PhotoFaceTagEntity for this imageId
*/
@Relation(
parentColumn = "imageId",
entityColumn = "imageId"
)
val faceTags: List<PhotoFaceTagEntity>
)

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package com.placeholder.sherpai2.data.local.model
import androidx.room.Embedded
import androidx.room.Relation
import com.placeholder.sherpai2.data.local.entity.ImageEntity
import com.placeholder.sherpai2.data.local.entity.ImageTagEntity
data class ImageWithTags(
@Embedded
val image: ImageEntity,
@Relation(
parentColumn = "imageId",
entityColumn = "imageId"
)
val tags: List<ImageTagEntity>
)

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package com.placeholder.sherpai2.data.repository
import com.placeholder.sherpai2.data.local.dao.CollectionDao
import com.placeholder.sherpai2.data.local.dao.ImageAggregateDao
import com.placeholder.sherpai2.data.local.entity.*
import com.placeholder.sherpai2.data.local.model.CollectionWithDetails
import com.placeholder.sherpai2.ui.search.DateRange
import kotlinx.coroutines.flow.Flow
import kotlinx.coroutines.flow.first
import javax.inject.Inject
import javax.inject.Singleton
/**
* CollectionRepository - Business logic for collections
*
* Handles:
* - Creating smart/static collections
* - Evaluating smart collection filters
* - Managing photos in collections
* - Export functionality
*/
@Singleton
class CollectionRepository @Inject constructor(
private val collectionDao: CollectionDao,
private val imageAggregateDao: ImageAggregateDao
) {
// ==========================================
// COLLECTION OPERATIONS
// ==========================================
suspend fun createSmartCollection(
name: String,
description: String?,
includedPeople: Set<String>,
excludedPeople: Set<String>,
includedTags: Set<String>,
excludedTags: Set<String>,
dateRange: DateRange
): String {
// Create collection
val collection = CollectionEntity.createSmart(name, description)
collectionDao.insert(collection)
// Save filters
val filters = mutableListOf<CollectionFilterEntity>()
includedPeople.forEach {
filters.add(
CollectionFilterEntity.create(
collection.collectionId,
"PERSON_INCLUDE",
it
)
)
}
excludedPeople.forEach {
filters.add(
CollectionFilterEntity.create(
collection.collectionId,
"PERSON_EXCLUDE",
it
)
)
}
includedTags.forEach {
filters.add(
CollectionFilterEntity.create(
collection.collectionId,
"TAG_INCLUDE",
it
)
)
}
excludedTags.forEach {
filters.add(
CollectionFilterEntity.create(
collection.collectionId,
"TAG_EXCLUDE",
it
)
)
}
if (dateRange != DateRange.ALL_TIME) {
filters.add(
CollectionFilterEntity.create(
collection.collectionId,
"DATE_RANGE",
dateRange.name
)
)
}
if (filters.isNotEmpty()) {
collectionDao.insertFilters(filters)
}
// Evaluate and populate
evaluateSmartCollection(collection.collectionId)
return collection.collectionId
}
suspend fun createStaticCollection(
name: String,
description: String?,
imageIds: List<String>
): String {
val collection = CollectionEntity.createStatic(name, description, imageIds.size)
collectionDao.insert(collection)
// Add images
val now = System.currentTimeMillis()
val collectionImages = imageIds.mapIndexed { index, imageId ->
CollectionImageEntity(
collectionId = collection.collectionId,
imageId = imageId,
addedAt = now,
sortOrder = index
)
}
collectionDao.addImages(collectionImages)
collectionDao.updatePhotoCount(collection.collectionId, now)
// Set cover image to first image
if (imageIds.isNotEmpty()) {
val firstImage = imageAggregateDao.observeAllImagesWithEverything()
.first()
.find { it.image.imageId == imageIds.first() }
if (firstImage != null) {
collectionDao.updateCoverImage(collection.collectionId, firstImage.image.imageUri, now)
}
}
return collection.collectionId
}
suspend fun deleteCollection(collectionId: String) {
collectionDao.deleteById(collectionId)
}
fun getAllCollections(): Flow<List<CollectionEntity>> {
return collectionDao.getAllCollections()
}
fun getCollection(collectionId: String): Flow<CollectionEntity?> {
return collectionDao.getByIdFlow(collectionId)
}
fun getCollectionWithDetails(collectionId: String): Flow<CollectionWithDetails?> {
return collectionDao.getCollectionWithDetails(collectionId)
}
// ==========================================
// IMAGE MANAGEMENT
// ==========================================
suspend fun addImageToCollection(collectionId: String, imageId: String) {
val now = System.currentTimeMillis()
val count = collectionDao.getPhotoCount(collectionId)
collectionDao.addImage(
CollectionImageEntity(
collectionId = collectionId,
imageId = imageId,
addedAt = now,
sortOrder = count
)
)
collectionDao.updatePhotoCount(collectionId, now)
// Update cover image if this is the first photo
if (count == 0) {
val images = collectionDao.getPreviewImages(collectionId)
if (images.isNotEmpty()) {
collectionDao.updateCoverImage(collectionId, images.first().imageUri, now)
}
}
}
suspend fun removeImageFromCollection(collectionId: String, imageId: String) {
collectionDao.removeImage(collectionId, imageId)
collectionDao.updatePhotoCount(collectionId, System.currentTimeMillis())
}
suspend fun toggleFavorite(imageId: String) {
val favCollection = collectionDao.getFavoriteCollection()
?: run {
// Create favorites collection if it doesn't exist
val fav = CollectionEntity.createFavorite()
collectionDao.insert(fav)
fav
}
val isFavorite = collectionDao.containsImage(favCollection.collectionId, imageId)
if (isFavorite) {
removeImageFromCollection(favCollection.collectionId, imageId)
} else {
addImageToCollection(favCollection.collectionId, imageId)
}
}
suspend fun isFavorite(imageId: String): Boolean {
val favCollection = collectionDao.getFavoriteCollection() ?: return false
return collectionDao.containsImage(favCollection.collectionId, imageId)
}
fun getImagesInCollection(collectionId: String): Flow<List<ImageEntity>> {
return collectionDao.getImagesInCollection(collectionId)
}
// ==========================================
// SMART COLLECTION EVALUATION
// ==========================================
/**
* Re-evaluate a SMART collection's filters and update its images
*/
suspend fun evaluateSmartCollection(collectionId: String) {
val collection = collectionDao.getById(collectionId) ?: return
if (collection.type != "SMART") return
val filters = collectionDao.getFilters(collectionId)
if (filters.isEmpty()) return
// Get all images
val allImages = imageAggregateDao.observeAllImagesWithEverything().first()
// Parse filters
val includedPeople = filters
.filter { it.filterType == "PERSON_INCLUDE" }
.map { it.filterValue }
.toSet()
val excludedPeople = filters
.filter { it.filterType == "PERSON_EXCLUDE" }
.map { it.filterValue }
.toSet()
val includedTags = filters
.filter { it.filterType == "TAG_INCLUDE" }
.map { it.filterValue }
.toSet()
val excludedTags = filters
.filter { it.filterType == "TAG_EXCLUDE" }
.map { it.filterValue }
.toSet()
// Filter images (same logic as SearchViewModel)
val matchingImages = allImages.filter { imageWithEverything ->
// TODO: Apply same Boolean logic as SearchViewModel
// For now, simple tag matching
val imageTags = imageWithEverything.tags.map { it.value }.toSet()
val hasIncludedTags = includedTags.isEmpty() || includedTags.all { it in imageTags }
val hasNoExcludedTags = excludedTags.isEmpty() || excludedTags.none { it in imageTags }
hasIncludedTags && hasNoExcludedTags
}.map { it.image.imageId }
// Update collection
collectionDao.clearAllImages(collectionId)
val now = System.currentTimeMillis()
val collectionImages = matchingImages.mapIndexed { index, imageId ->
CollectionImageEntity(
collectionId = collectionId,
imageId = imageId,
addedAt = now,
sortOrder = index
)
}
if (collectionImages.isNotEmpty()) {
collectionDao.addImages(collectionImages)
// Set cover image to first image
val firstImageId = matchingImages.first()
val firstImage = allImages.find { it.image.imageId == firstImageId }
if (firstImage != null) {
collectionDao.updateCoverImage(collectionId, firstImage.image.imageUri, now)
}
}
collectionDao.updatePhotoCount(collectionId, now)
}
/**
* Re-evaluate all SMART collections
*/
suspend fun evaluateAllSmartCollections() {
val collections = collectionDao.getCollectionsByType("SMART").first()
collections.forEach { collection ->
evaluateSmartCollection(collection.collectionId)
}
}
// ==========================================
// UPDATES
// ==========================================
suspend fun updateCollectionDetails(
collectionId: String,
name: String,
description: String?
) {
collectionDao.updateDetails(collectionId, name, description, System.currentTimeMillis())
}
suspend fun togglePinned(collectionId: String) {
val collection = collectionDao.getById(collectionId) ?: return
collectionDao.updatePinned(
collectionId,
!collection.isPinned,
System.currentTimeMillis()
)
}
}

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package com.placeholder.sherpai2.data.repository
import android.content.Context
import android.graphics.Bitmap
import com.placeholder.sherpai2.data.local.dao.FaceModelDao
import com.placeholder.sherpai2.data.local.dao.ImageDao
import com.placeholder.sherpai2.data.local.dao.PersonDao
import com.placeholder.sherpai2.data.local.dao.PhotoFaceTagDao
import com.placeholder.sherpai2.data.local.entity.*
import com.placeholder.sherpai2.ml.FaceNetModel
import com.placeholder.sherpai2.ui.trainingprep.TrainingSanityChecker
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.flow.Flow
import kotlinx.coroutines.flow.map
import kotlinx.coroutines.withContext
import javax.inject.Inject
import javax.inject.Singleton
/**
* FaceRecognitionRepository - Complete face recognition system
*
* USES STRING IDs TO MATCH YOUR SCHEMA:
* - PersonEntity.id: String (UUID)
* - ImageEntity.imageId: String
* - FaceModelEntity.id: String (UUID)
* - PhotoFaceTagEntity.id: String (UUID)
*/
@Singleton
class FaceRecognitionRepository @Inject constructor(
private val context: Context,
private val personDao: PersonDao,
private val imageDao: ImageDao,
private val faceModelDao: FaceModelDao,
private val photoFaceTagDao: PhotoFaceTagDao
) {
private val faceNetModel by lazy { FaceNetModel(context) }
// ======================
// TRAINING OPERATIONS
// ======================
/**
* Create a new person with face model in one operation.
*
* @return PersonId (String UUID)
*/
suspend fun createPersonWithFaceModel(
personName: String,
validImages: List<TrainingSanityChecker.ValidTrainingImage>,
onProgress: (Int, Int) -> Unit = { _, _ -> }
): String = withContext(Dispatchers.IO) {
// Create PersonEntity with UUID
val person = PersonEntity.create(name = personName)
personDao.insert(person)
// Train face model
trainPerson(
personId = person.id,
validImages = validImages,
onProgress = onProgress
)
person.id
}
/**
* Train a face recognition model for an existing person.
*
* @param personId String UUID
* @return Face model ID (String UUID)
*/
suspend fun trainPerson(
personId: String,
validImages: List<TrainingSanityChecker.ValidTrainingImage>,
onProgress: (Int, Int) -> Unit = { _, _ -> }
): String = withContext(Dispatchers.Default) {
val person = personDao.getPersonById(personId)
?: throw IllegalArgumentException("Person with ID $personId not found")
val embeddings = faceNetModel.generateEmbeddingsBatch(
faceBitmaps = validImages.map { it.croppedFaceBitmap },
onProgress = onProgress
)
val personEmbedding = faceNetModel.createPersonModel(embeddings)
val confidences = embeddings.map { embedding ->
faceNetModel.calculateSimilarity(personEmbedding, embedding)
}
val avgConfidence = confidences.average().toFloat()
val faceModel = FaceModelEntity.create(
personId = personId,
embeddingArray = personEmbedding,
trainingImageCount = validImages.size,
averageConfidence = avgConfidence
)
faceModelDao.insertFaceModel(faceModel)
faceModel.id
}
/**
* Retrain face model with additional images.
*/
suspend fun retrainFaceModel(
faceModelId: String,
newFaceImages: List<Bitmap>
) = withContext(Dispatchers.Default) {
val faceModel = faceModelDao.getFaceModelById(faceModelId)
?: throw IllegalArgumentException("Face model $faceModelId not found")
val existingEmbedding = faceModel.getEmbeddingArray()
val newEmbeddings = faceNetModel.generateEmbeddingsBatch(newFaceImages)
val allEmbeddings = listOf(existingEmbedding) + newEmbeddings
val updatedEmbedding = faceNetModel.createPersonModel(allEmbeddings)
val confidences = allEmbeddings.map { embedding ->
faceNetModel.calculateSimilarity(updatedEmbedding, embedding)
}
val avgConfidence = confidences.average().toFloat()
faceModelDao.updateFaceModel(
FaceModelEntity.create(
personId = faceModel.personId,
embeddingArray = updatedEmbedding,
trainingImageCount = faceModel.trainingImageCount + newFaceImages.size,
averageConfidence = avgConfidence
).copy(
id = faceModelId,
createdAt = faceModel.createdAt,
updatedAt = System.currentTimeMillis()
)
)
}
// ======================
// SCANNING / RECOGNITION
// ======================
/**
* Scan an image for faces and tag recognized persons.
*
* ALSO UPDATES FACE DETECTION CACHE for optimization.
*
* @param imageId String (from ImageEntity.imageId)
*/
suspend fun scanImage(
imageId: String,
detectedFaces: List<DetectedFace>,
threshold: Float = FaceNetModel.SIMILARITY_THRESHOLD_HIGH
): List<PhotoFaceTagEntity> = withContext(Dispatchers.Default) {
// OPTIMIZATION: Update face detection cache
// This makes future scans faster by skipping images without faces
withContext(Dispatchers.IO) {
imageDao.updateFaceDetectionCache(
imageId = imageId,
hasFaces = detectedFaces.isNotEmpty(),
faceCount = detectedFaces.size
)
}
val faceModels = faceModelDao.getAllActiveFaceModels()
if (faceModels.isEmpty()) {
return@withContext emptyList()
}
val tags = mutableListOf<PhotoFaceTagEntity>()
for (detectedFace in detectedFaces) {
val faceEmbedding = faceNetModel.generateEmbedding(detectedFace.croppedBitmap)
var bestMatch: Pair<String, Float>? = null
var highestSimilarity = threshold
for (faceModel in faceModels) {
val modelEmbedding = faceModel.getEmbeddingArray()
val similarity = faceNetModel.calculateSimilarity(faceEmbedding, modelEmbedding)
if (similarity > highestSimilarity) {
highestSimilarity = similarity
bestMatch = Pair(faceModel.id, similarity)
}
}
if (bestMatch != null) {
val (faceModelId, confidence) = bestMatch
val tag = PhotoFaceTagEntity.create(
imageId = imageId,
faceModelId = faceModelId,
boundingBox = detectedFace.boundingBox,
confidence = confidence,
faceEmbedding = faceEmbedding
)
tags.add(tag)
faceModelDao.updateLastUsed(faceModelId, System.currentTimeMillis())
}
}
if (tags.isNotEmpty()) {
photoFaceTagDao.insertTags(tags)
}
tags
}
/**
* Recognize a single face bitmap (without saving).
*/
suspend fun recognizeFace(
faceBitmap: Bitmap,
threshold: Float = FaceNetModel.SIMILARITY_THRESHOLD_HIGH
): Pair<String, Float>? = withContext(Dispatchers.Default) {
val faceEmbedding = faceNetModel.generateEmbedding(faceBitmap)
val faceModels = faceModelDao.getAllActiveFaceModels()
val modelEmbeddings = faceModels.map { it.id to it.getEmbeddingArray() }
faceNetModel.findBestMatch(faceEmbedding, modelEmbeddings, threshold)
}
// ======================
// SEARCH / QUERY
// ======================
/**
* Get all images containing a specific person.
*
* @param personId String UUID
*/
suspend fun getImagesForPerson(personId: String): List<ImageEntity> = withContext(Dispatchers.IO) {
val faceModel = faceModelDao.getFaceModelByPersonId(personId)
?: return@withContext emptyList()
val imageIds = photoFaceTagDao.getImageIdsForFaceModel(faceModel.id)
imageDao.getImagesByIds(imageIds)
}
/**
* Get images for person as Flow (reactive).
*/
fun getImagesForPersonFlow(personId: String): Flow<List<ImageEntity>> {
return photoFaceTagDao.getImageIdsForFaceModelFlow(personId)
.map { imageIds ->
imageDao.getImagesByIds(imageIds)
}
}
/**
* Get all persons with face models.
*/
suspend fun getPersonsWithFaceModels(): List<PersonEntity> = withContext(Dispatchers.IO) {
val faceModels = faceModelDao.getAllActiveFaceModels()
val personIds = faceModels.map { it.personId }
personDao.getPersonsByIds(personIds)
}
/**
* Get face detection stats for a person.
*/
suspend fun getPersonFaceStats(personId: String): PersonFaceStats? = withContext(Dispatchers.IO) {
val person = personDao.getPersonById(personId) ?: return@withContext null
val faceModel = faceModelDao.getFaceModelByPersonId(personId) ?: return@withContext null
val imageIds = photoFaceTagDao.getImageIdsForFaceModel(faceModel.id)
val allTags = photoFaceTagDao.getAllTagsForFaceModel(faceModel.id)
val avgConfidence = if (allTags.isNotEmpty()) {
allTags.map { it.confidence }.average().toFloat()
} else {
0f
}
val lastDetected = allTags.maxOfOrNull { it.detectedAt }
PersonFaceStats(
personId = person.id,
personName = person.name,
faceModelId = faceModel.id,
trainingImageCount = faceModel.trainingImageCount,
taggedPhotoCount = imageIds.size,
averageConfidence = avgConfidence,
lastDetectedAt = lastDetected
)
}
/**
* Get face tags for an image.
*/
suspend fun getFaceTagsForImage(imageId: String): List<PhotoFaceTagEntity> {
return photoFaceTagDao.getTagsForImage(imageId)
}
/**
* Get person from a face tag.
*/
suspend fun getPersonForFaceTag(tag: PhotoFaceTagEntity): PersonEntity? = withContext(Dispatchers.IO) {
val faceModel = faceModelDao.getFaceModelById(tag.faceModelId) ?: return@withContext null
personDao.getPersonById(faceModel.personId)
}
/**
* Get face tags with person info for an image.
*/
suspend fun getFaceTagsWithPersons(imageId: String): List<Pair<PhotoFaceTagEntity, PersonEntity>> = withContext(Dispatchers.IO) {
val tags = photoFaceTagDao.getTagsForImage(imageId)
tags.mapNotNull { tag ->
val person = getPersonForFaceTag(tag)
if (person != null) tag to person else null
}
}
// ======================
// VERIFICATION / QUALITY
// ======================
suspend fun verifyFaceTag(tagId: String) {
photoFaceTagDao.markTagAsVerified(
tagId = tagId,
timestamp = System.currentTimeMillis()
)
}
suspend fun getUnverifiedTags(): List<PhotoFaceTagEntity> {
return photoFaceTagDao.getUnverifiedTags()
}
suspend fun getLowConfidenceTags(threshold: Float = 0.7f): List<PhotoFaceTagEntity> {
return photoFaceTagDao.getLowConfidenceTags(threshold)
}
// ======================
// MANAGEMENT
// ======================
suspend fun deleteFaceModel(faceModelId: String) = withContext(Dispatchers.IO) {
photoFaceTagDao.deleteTagsForFaceModel(faceModelId)
faceModelDao.deleteFaceModelById(faceModelId)
}
// Add this method to FaceRecognitionRepository_StringIds.kt
// Replace the existing createPersonWithFaceModel method with this version:
/**
* Create a new person with face model in one operation.
* Now supports full PersonEntity with optional fields.
*
* @param person PersonEntity with name, DOB, relationship, etc.
* @return PersonId (String UUID)
*/
suspend fun createPersonWithFaceModel(
person: PersonEntity,
validImages: List<TrainingSanityChecker.ValidTrainingImage>,
onProgress: (Int, Int) -> Unit = { _, _ -> }
): String = withContext(Dispatchers.IO) {
// Insert person with all fields
personDao.insert(person)
// Train face model
trainPerson(
personId = person.id,
validImages = validImages,
onProgress = onProgress
)
person.id
}
/**
* Get face model by ID
*/
suspend fun getFaceModelById(faceModelId: String): FaceModelEntity? = withContext(Dispatchers.IO) {
faceModelDao.getFaceModelById(faceModelId)
}
suspend fun deleteTagsForImage(imageId: String) {
photoFaceTagDao.deleteTagsForImage(imageId)
}
/**
* Get all image IDs that have been tagged with this face model
* Used for scan optimization (skip already-tagged images)
*/
suspend fun getImageIdsForFaceModel(faceModelId: String): List<String> = withContext(Dispatchers.IO) {
photoFaceTagDao.getImageIdsForFaceModel(faceModelId)
}
fun cleanup() {
faceNetModel.close()
}
}
data class DetectedFace(
val croppedBitmap: Bitmap,
val boundingBox: android.graphics.Rect
)
data class PersonFaceStats(
val personId: String,
val personName: String,
val faceModelId: String,
val trainingImageCount: Int,
val taggedPhotoCount: Int,
val averageConfidence: Float,
val lastDetectedAt: Long?
)

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package com.placeholder.sherpai2.data.service
import android.content.Context
import android.graphics.Bitmap
import android.graphics.Color
import com.placeholder.sherpai2.data.local.dao.ImageTagDao
import com.placeholder.sherpai2.data.local.dao.PersonDao
import com.placeholder.sherpai2.data.local.dao.PhotoFaceTagDao
import com.placeholder.sherpai2.data.local.dao.TagDao
import com.placeholder.sherpai2.data.local.entity.ImageEntity
import com.placeholder.sherpai2.data.local.entity.ImageTagEntity
import com.placeholder.sherpai2.data.local.entity.TagEntity
import com.placeholder.sherpai2.data.repository.DetectedFace
import com.placeholder.sherpai2.util.DiagnosticLogger
import dagger.hilt.android.qualifiers.ApplicationContext
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.withContext
import java.util.Calendar
import javax.inject.Inject
import javax.inject.Singleton
import kotlin.math.abs
/**
* AutoTaggingService - Intelligent auto-tagging system
*
* Capabilities:
* - Face-based tags (group_photo, selfie, couple)
* - Scene tags (portrait, landscape, square orientation)
* - Time tags (morning, afternoon, evening, night)
* - Quality tags (high_res, low_res)
* - Relationship tags (family, friend, colleague from PersonEntity)
* - Birthday tags (from PersonEntity DOB)
* - Indoor/Outdoor estimation (basic heuristic)
*/
@Singleton
class AutoTaggingService @Inject constructor(
@ApplicationContext private val context: Context,
private val tagDao: TagDao,
private val imageTagDao: ImageTagDao,
private val photoFaceTagDao: PhotoFaceTagDao,
private val personDao: PersonDao
) {
// ======================
// MAIN AUTO-TAGGING
// ======================
/**
* Auto-tag an image with all applicable system tags
*
* @return Number of tags applied
*/
suspend fun autoTagImage(
imageEntity: ImageEntity,
bitmap: Bitmap,
detectedFaces: List<DetectedFace>
): Int = withContext(Dispatchers.Default) {
val tagsToApply = mutableListOf<String>()
// Face-count based tags
when (detectedFaces.size) {
0 -> { /* No face tags */ }
1 -> {
if (isSelfie(detectedFaces[0], bitmap)) {
tagsToApply.add("selfie")
} else {
tagsToApply.add("single_person")
}
}
2 -> tagsToApply.add("couple")
in 3..5 -> tagsToApply.add("group_photo")
in 6..10 -> {
tagsToApply.add("group_photo")
tagsToApply.add("large_group")
}
else -> {
tagsToApply.add("group_photo")
tagsToApply.add("large_group")
tagsToApply.add("crowd")
}
}
// Orientation tags
val aspectRatio = bitmap.width.toFloat() / bitmap.height.toFloat()
when {
aspectRatio > 1.3f -> tagsToApply.add("landscape")
aspectRatio < 0.77f -> tagsToApply.add("portrait")
else -> tagsToApply.add("square")
}
// Resolution tags
val megapixels = (bitmap.width * bitmap.height) / 1_000_000f
when {
megapixels > 2.0f -> tagsToApply.add("high_res")
megapixels < 0.5f -> tagsToApply.add("low_res")
}
// Time-based tags
val hourOfDay = getHourFromTimestamp(imageEntity.capturedAt)
tagsToApply.add(when (hourOfDay) {
in 5..10 -> "morning"
in 11..16 -> "afternoon"
in 17..20 -> "evening"
else -> "night"
})
// Indoor/Outdoor estimation (only if image is large enough)
if (bitmap.width >= 200 && bitmap.height >= 200) {
val isIndoor = estimateIndoorOutdoor(bitmap)
tagsToApply.add(if (isIndoor) "indoor" else "outdoor")
}
// Apply all tags
var tagsApplied = 0
tagsToApply.forEach { tagName ->
if (applySystemTag(imageEntity.imageId, tagName)) {
tagsApplied++
}
}
DiagnosticLogger.d("AutoTag: Applied $tagsApplied tags to image ${imageEntity.imageId}")
tagsApplied
}
// ======================
// RELATIONSHIP TAGS
// ======================
/**
* Tag all images with a person using their relationship tag
*
* @param personId Person to tag images for
* @return Number of tags applied
*/
suspend fun autoTagRelationshipForPerson(personId: String): Int = withContext(Dispatchers.IO) {
val person = personDao.getPersonById(personId) ?: return@withContext 0
val relationship = person.relationship?.lowercase() ?: return@withContext 0
// Get face model for this person
val faceModels = photoFaceTagDao.getAllTagsForFaceModel(personId)
if (faceModels.isEmpty()) return@withContext 0
val imageIds = faceModels.map { it.imageId }.distinct()
var tagsApplied = 0
imageIds.forEach { imageId ->
if (applySystemTag(imageId, relationship)) {
tagsApplied++
}
}
DiagnosticLogger.i("AutoTag: Applied '$relationship' tag to $tagsApplied images for ${person.name}")
tagsApplied
}
/**
* Tag relationships for ALL persons in database
*/
suspend fun autoTagAllRelationships(): Int = withContext(Dispatchers.IO) {
val persons = personDao.getAllPersons()
var totalTags = 0
persons.forEach { person ->
totalTags += autoTagRelationshipForPerson(person.id)
}
DiagnosticLogger.i("AutoTag: Applied $totalTags relationship tags across ${persons.size} persons")
totalTags
}
// ======================
// BIRTHDAY TAGS
// ======================
/**
* Tag images near a person's birthday
*
* @param personId Person whose birthday to check
* @param daysRange Days before/after birthday to consider (default: 3)
* @return Number of tags applied
*/
suspend fun autoTagBirthdaysForPerson(
personId: String,
daysRange: Int = 3
): Int = withContext(Dispatchers.IO) {
val person = personDao.getPersonById(personId) ?: return@withContext 0
val dateOfBirth = person.dateOfBirth ?: return@withContext 0
// Get all face tags for this person
val faceTags = photoFaceTagDao.getAllTagsForFaceModel(personId)
if (faceTags.isEmpty()) return@withContext 0
var tagsApplied = 0
faceTags.forEach { faceTag ->
// Get the image to check its timestamp
val imageId = faceTag.imageId
// Check if image was captured near birthday
if (isNearBirthday(faceTag.detectedAt, dateOfBirth, daysRange)) {
if (applySystemTag(imageId, "birthday")) {
tagsApplied++
}
}
}
DiagnosticLogger.i("AutoTag: Applied 'birthday' tag to $tagsApplied images for ${person.name}")
tagsApplied
}
/**
* Tag birthdays for ALL persons with DOB
*/
suspend fun autoTagAllBirthdays(daysRange: Int = 3): Int = withContext(Dispatchers.IO) {
val persons = personDao.getAllPersons()
var totalTags = 0
persons.forEach { person ->
if (person.dateOfBirth != null) {
totalTags += autoTagBirthdaysForPerson(person.id, daysRange)
}
}
DiagnosticLogger.i("AutoTag: Applied $totalTags birthday tags")
totalTags
}
// ======================
// HELPER METHODS
// ======================
/**
* Check if an image is a selfie based on face size
*/
private fun isSelfie(face: DetectedFace, bitmap: Bitmap): Boolean {
val boundingBox = face.boundingBox
val faceArea = boundingBox.width() * boundingBox.height()
val imageArea = bitmap.width * bitmap.height
val faceRatio = faceArea.toFloat() / imageArea.toFloat()
// Selfie = face takes up significant portion (>15% of image)
return faceRatio > 0.15f
}
/**
* Get hour of day from timestamp (0-23)
*/
private fun getHourFromTimestamp(timestamp: Long): Int {
return Calendar.getInstance().apply {
timeInMillis = timestamp
}.get(Calendar.HOUR_OF_DAY)
}
/**
* Check if a timestamp is near a birthday
*/
private fun isNearBirthday(
capturedTimestamp: Long,
dobTimestamp: Long,
daysRange: Int
): Boolean {
val capturedCal = Calendar.getInstance().apply { timeInMillis = capturedTimestamp }
val dobCal = Calendar.getInstance().apply { timeInMillis = dobTimestamp }
val capturedMonth = capturedCal.get(Calendar.MONTH)
val capturedDay = capturedCal.get(Calendar.DAY_OF_MONTH)
val dobMonth = dobCal.get(Calendar.MONTH)
val dobDay = dobCal.get(Calendar.DAY_OF_MONTH)
if (capturedMonth == dobMonth) {
return abs(capturedDay - dobDay) <= daysRange
}
// Handle edge case: birthday near end/start of month
// e.g., DOB = Jan 2, captured = Dec 31 (within 3 days)
if (abs(capturedMonth - dobMonth) == 1 || abs(capturedMonth - dobMonth) == 11) {
val daysInCapturedMonth = capturedCal.getActualMaximum(Calendar.DAY_OF_MONTH)
val daysInDobMonth = dobCal.getActualMaximum(Calendar.DAY_OF_MONTH)
if (capturedMonth < dobMonth || (capturedMonth == 11 && dobMonth == 0)) {
// Captured before DOB month
val dayDiff = (daysInCapturedMonth - capturedDay) + dobDay
return dayDiff <= daysRange
} else {
// Captured after DOB month
val dayDiff = (daysInDobMonth - dobDay) + capturedDay
return dayDiff <= daysRange
}
}
return false
}
/**
* Basic indoor/outdoor estimation using brightness and saturation
*
* Heuristic:
* - Outdoor: Higher brightness (>120), Higher saturation (>0.25)
* - Indoor: Lower brightness, Lower saturation
*/
private fun estimateIndoorOutdoor(bitmap: Bitmap): Boolean {
// Sample pixels for analysis (don't process entire image)
val sampleSize = 100
val sampledPixels = mutableListOf<Int>()
val stepX = bitmap.width / sampleSize.coerceAtMost(bitmap.width)
val stepY = bitmap.height / sampleSize.coerceAtMost(bitmap.height)
for (x in 0 until sampleSize.coerceAtMost(bitmap.width)) {
for (y in 0 until sampleSize.coerceAtMost(bitmap.height)) {
val px = (x * stepX).coerceIn(0, bitmap.width - 1)
val py = (y * stepY).coerceIn(0, bitmap.height - 1)
sampledPixels.add(bitmap.getPixel(px, py))
}
}
if (sampledPixels.isEmpty()) return true // Default to indoor if sampling fails
// Calculate average brightness
val avgBrightness = sampledPixels.map { pixel ->
val r = Color.red(pixel)
val g = Color.green(pixel)
val b = Color.blue(pixel)
(r + g + b) / 3.0f
}.average()
// Calculate color saturation
val avgSaturation = sampledPixels.map { pixel ->
val hsv = FloatArray(3)
Color.colorToHSV(pixel, hsv)
hsv[1] // Saturation
}.average()
// Heuristic: Indoor if low brightness OR low saturation
return avgBrightness < 120 || avgSaturation < 0.25
}
/**
* Apply a system tag to an image (helper to avoid duplicates)
*
* @return true if tag was applied, false if already exists
*/
private suspend fun applySystemTag(imageId: String, tagName: String): Boolean {
return withContext(Dispatchers.IO) {
try {
// Get or create tag
val tag = getOrCreateSystemTag(tagName)
// Create image-tag link
val imageTag = ImageTagEntity(
imageId = imageId,
tagId = tag.tagId,
source = "AUTO",
confidence = 1.0f,
visibility = "PUBLIC",
createdAt = System.currentTimeMillis()
)
imageTagDao.upsert(imageTag)
true
} catch (e: Exception) {
DiagnosticLogger.e("Failed to apply tag '$tagName' to image $imageId", e)
false
}
}
}
/**
* Get existing system tag or create new one
*/
private suspend fun getOrCreateSystemTag(tagName: String): TagEntity {
return withContext(Dispatchers.IO) {
tagDao.getByValue(tagName) ?: run {
val newTag = TagEntity.createSystemTag(tagName)
tagDao.insert(newTag)
newTag
}
}
}
}

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package com.placeholder.sherpai2.di
import android.content.Context
import androidx.room.Room
import com.placeholder.sherpai2.data.local.AppDatabase
import com.placeholder.sherpai2.data.local.MIGRATION_7_8
import com.placeholder.sherpai2.data.local.MIGRATION_8_9
import com.placeholder.sherpai2.data.local.MIGRATION_9_10
import com.placeholder.sherpai2.data.local.dao.*
import dagger.Module
import dagger.Provides
import dagger.hilt.InstallIn
import dagger.hilt.android.qualifiers.ApplicationContext
import dagger.hilt.components.SingletonComponent
import javax.inject.Singleton
/**
* DatabaseModule - Provides database and ALL DAOs
*
* VERSION 10 UPDATES:
* - Added UserFeedbackDao for cluster refinement
* - Added MIGRATION_9_10
*
* VERSION 9 UPDATES:
* - Added FaceCacheDao for per-face metadata
* - Added MIGRATION_8_9
*
* PHASE 2 UPDATES:
* - Added PersonAgeTagDao
* - Added migration v7→v8
*/
@Module
@InstallIn(SingletonComponent::class)
object DatabaseModule {
// ===== DATABASE =====
@Provides
@Singleton
fun provideDatabase(
@ApplicationContext context: Context
): AppDatabase =
Room.databaseBuilder(
context,
AppDatabase::class.java,
"sherpai.db"
)
// DEVELOPMENT MODE: Destructive migration (fresh install on schema change)
.fallbackToDestructiveMigration(dropAllTables = true)
// PRODUCTION MODE: Uncomment this and remove fallbackToDestructiveMigration()
// .addMigrations(MIGRATION_7_8, MIGRATION_8_9, MIGRATION_9_10)
.build()
// ===== CORE DAOs =====
@Provides
fun provideImageDao(db: AppDatabase): ImageDao =
db.imageDao()
@Provides
fun provideTagDao(db: AppDatabase): TagDao =
db.tagDao()
@Provides
fun provideEventDao(db: AppDatabase): EventDao =
db.eventDao()
@Provides
fun provideImageEventDao(db: AppDatabase): ImageEventDao =
db.imageEventDao()
@Provides
fun provideImageAggregateDao(db: AppDatabase): ImageAggregateDao =
db.imageAggregateDao()
@Provides
fun provideImageTagDao(db: AppDatabase): ImageTagDao =
db.imageTagDao()
// ===== FACE RECOGNITION DAOs =====
@Provides
fun providePersonDao(db: AppDatabase): PersonDao =
db.personDao()
@Provides
fun provideFaceModelDao(db: AppDatabase): FaceModelDao =
db.faceModelDao()
@Provides
fun providePhotoFaceTagDao(db: AppDatabase): PhotoFaceTagDao =
db.photoFaceTagDao()
@Provides
fun providePersonAgeTagDao(db: AppDatabase): PersonAgeTagDao =
db.personAgeTagDao()
@Provides
fun provideFaceCacheDao(db: AppDatabase): FaceCacheDao =
db.faceCacheDao()
@Provides
fun provideUserFeedbackDao(db: AppDatabase): UserFeedbackDao =
db.userFeedbackDao()
// ===== COLLECTIONS DAOs =====
@Provides
fun provideCollectionDao(db: AppDatabase): CollectionDao =
db.collectionDao()
}

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package com.placeholder.sherpai2.di
import android.content.Context
import com.placeholder.sherpai2.ml.FaceNetModel
import dagger.Module
import dagger.Provides
import dagger.hilt.InstallIn
import dagger.hilt.android.qualifiers.ApplicationContext
import dagger.hilt.components.SingletonComponent
import javax.inject.Singleton
/**
* MLModule - Provides ML-related dependencies
*
* This module provides FaceNetModel for dependency injection
*/
@Module
@InstallIn(SingletonComponent::class)
object MLModule {
/**
* Provide FaceNetModel singleton
*
* FaceNetModel loads the MobileFaceNet TFLite model and manages
* face embedding generation for recognition.
*/
@Provides
@Singleton
fun provideFaceNetModel(
@ApplicationContext context: Context
): FaceNetModel {
return FaceNetModel(context)
}
}

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package com.placeholder.sherpai2.di
import android.content.Context
import androidx.work.WorkManager
import com.placeholder.sherpai2.data.local.dao.*
import com.placeholder.sherpai2.data.repository.FaceRecognitionRepository
import com.placeholder.sherpai2.data.repository.TaggingRepositoryImpl
import com.placeholder.sherpai2.domain.clustering.ClusterQualityAnalyzer
import com.placeholder.sherpai2.domain.clustering.ClusterRefinementService
import com.placeholder.sherpai2.domain.repository.ImageRepository
import com.placeholder.sherpai2.domain.repository.ImageRepositoryImpl
import com.placeholder.sherpai2.domain.repository.TaggingRepository
import com.placeholder.sherpai2.domain.validation.ValidationScanService
import dagger.Binds
import dagger.Module
import dagger.Provides
import dagger.hilt.InstallIn
import dagger.hilt.android.qualifiers.ApplicationContext
import dagger.hilt.components.SingletonComponent
import javax.inject.Singleton
/**
* RepositoryModule - Provides repository implementations
*
* UPDATED TO INCLUDE:
* - FaceRecognitionRepository for face recognition operations
* - ValidationScanService for post-training validation
* - ClusterRefinementService for user feedback loop (NEW)
* - ClusterQualityAnalyzer for cluster validation
* - WorkManager for background tasks
*/
@Module
@InstallIn(SingletonComponent::class)
abstract class RepositoryModule {
// ===== EXISTING REPOSITORY BINDINGS =====
@Binds
@Singleton
abstract fun bindImageRepository(
impl: ImageRepositoryImpl
): ImageRepository
@Binds
@Singleton
abstract fun bindTaggingRepository(
impl: TaggingRepositoryImpl
): TaggingRepository
// ===== COMPANION OBJECT FOR PROVIDES =====
companion object {
/**
* Provide FaceRecognitionRepository
*/
@Provides
@Singleton
fun provideFaceRecognitionRepository(
@ApplicationContext context: Context,
personDao: PersonDao,
imageDao: ImageDao,
faceModelDao: FaceModelDao,
photoFaceTagDao: PhotoFaceTagDao
): FaceRecognitionRepository {
return FaceRecognitionRepository(
context = context,
personDao = personDao,
imageDao = imageDao,
faceModelDao = faceModelDao,
photoFaceTagDao = photoFaceTagDao
)
}
/**
* Provide ValidationScanService
*/
@Provides
@Singleton
fun provideValidationScanService(
@ApplicationContext context: Context,
imageDao: ImageDao,
faceModelDao: FaceModelDao
): ValidationScanService {
return ValidationScanService(
context = context,
imageDao = imageDao,
faceModelDao = faceModelDao
)
}
/**
* Provide ClusterRefinementService (NEW)
* Handles user feedback and cluster refinement workflow
*/
@Provides
@Singleton
fun provideClusterRefinementService(
faceCacheDao: FaceCacheDao,
userFeedbackDao: UserFeedbackDao,
qualityAnalyzer: ClusterQualityAnalyzer
): ClusterRefinementService {
return ClusterRefinementService(
faceCacheDao = faceCacheDao,
userFeedbackDao = userFeedbackDao,
qualityAnalyzer = qualityAnalyzer
)
}
/**
* Provide ClusterQualityAnalyzer
* Validates cluster quality before training
*/
@Provides
@Singleton
fun provideClusterQualityAnalyzer(): ClusterQualityAnalyzer {
return ClusterQualityAnalyzer()
}
/**
* Provide WorkManager for background tasks
*/
@Provides
@Singleton
fun provideWorkManager(
@ApplicationContext context: Context
): WorkManager {
return WorkManager.getInstance(context)
}
}
}

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package com.placeholder.sherpai2.domain.clustering
import android.graphics.Rect
import android.util.Log
import javax.inject.Inject
import javax.inject.Singleton
import kotlin.math.sqrt
/**
* ClusterQualityAnalyzer - Validate cluster quality BEFORE training
*
* RELAXED THRESHOLDS for real-world photos (social media, distant shots):
* - Face size: 3% (down from 15%)
* - Outlier threshold: 65% (down from 75%)
* - GOOD tier: 75% (down from 85%)
* - EXCELLENT tier: 85% (down from 95%)
*/
@Singleton
class ClusterQualityAnalyzer @Inject constructor() {
companion object {
private const val TAG = "ClusterQuality"
private const val MIN_SOLO_PHOTOS = 6
private const val MIN_FACE_SIZE_RATIO = 0.03f // 3% of image (RELAXED)
private const val MIN_FACE_DIMENSION_PIXELS = 50 // 50px minimum (RELAXED)
private const val FALLBACK_MIN_DIMENSION = 80 // Fallback when no dimensions
private const val MIN_INTERNAL_SIMILARITY = 0.75f
private const val OUTLIER_THRESHOLD = 0.65f // RELAXED
private const val EXCELLENT_THRESHOLD = 0.85f // RELAXED
private const val GOOD_THRESHOLD = 0.75f // RELAXED
}
fun analyzeCluster(cluster: FaceCluster): ClusterQualityResult {
Log.d(TAG, "========================================")
Log.d(TAG, "Analyzing cluster ${cluster.clusterId}")
Log.d(TAG, "Total faces: ${cluster.faces.size}")
// Step 1: Filter to solo photos
val soloFaces = cluster.faces.filter { it.faceCount == 1 }
Log.d(TAG, "Solo photos: ${soloFaces.size}")
// Step 2: Filter by face size
val largeFaces = soloFaces.filter { face ->
isFaceLargeEnough(face)
}
Log.d(TAG, "Large faces (>= 3%): ${largeFaces.size}")
if (largeFaces.size < soloFaces.size) {
Log.d(TAG, "⚠️ Filtered out ${soloFaces.size - largeFaces.size} small faces")
}
// Step 3: Calculate internal consistency
val (avgSimilarity, outliers) = analyzeInternalConsistency(largeFaces)
// Step 4: Clean faces
val cleanFaces = largeFaces.filter { it !in outliers }
Log.d(TAG, "Clean faces: ${cleanFaces.size}")
// Step 5: Calculate quality score
val qualityScore = calculateQualityScore(
soloPhotoCount = soloFaces.size,
largeFaceCount = largeFaces.size,
cleanFaceCount = cleanFaces.size,
avgSimilarity = avgSimilarity,
totalFaces = cluster.faces.size
)
Log.d(TAG, "Quality score: ${(qualityScore * 100).toInt()}%")
// Step 6: Determine quality tier
val qualityTier = when {
qualityScore >= EXCELLENT_THRESHOLD -> ClusterQualityTier.EXCELLENT
qualityScore >= GOOD_THRESHOLD -> ClusterQualityTier.GOOD
else -> ClusterQualityTier.POOR
}
Log.d(TAG, "Quality tier: $qualityTier")
val canTrain = qualityTier != ClusterQualityTier.POOR && cleanFaces.size >= MIN_SOLO_PHOTOS
Log.d(TAG, "Can train: $canTrain")
Log.d(TAG, "========================================")
return ClusterQualityResult(
originalFaceCount = cluster.faces.size,
soloPhotoCount = soloFaces.size,
largeFaceCount = largeFaces.size,
cleanFaceCount = cleanFaces.size,
avgInternalSimilarity = avgSimilarity,
outlierFaces = outliers,
cleanFaces = cleanFaces,
qualityScore = qualityScore,
qualityTier = qualityTier,
canTrain = canTrain,
warnings = generateWarnings(soloFaces.size, largeFaces.size, cleanFaces.size, qualityTier, avgSimilarity)
)
}
private fun isFaceLargeEnough(face: DetectedFaceWithEmbedding): Boolean {
val faceArea = face.boundingBox.width() * face.boundingBox.height()
// Check 1: Absolute minimum
if (face.boundingBox.width() < MIN_FACE_DIMENSION_PIXELS ||
face.boundingBox.height() < MIN_FACE_DIMENSION_PIXELS) {
return false
}
// Check 2: Relative size if we have dimensions
if (face.imageWidth > 0 && face.imageHeight > 0) {
val imageArea = face.imageWidth * face.imageHeight
val faceRatio = faceArea.toFloat() / imageArea.toFloat()
return faceRatio >= MIN_FACE_SIZE_RATIO
}
// Fallback: Use absolute size
return face.boundingBox.width() >= FALLBACK_MIN_DIMENSION &&
face.boundingBox.height() >= FALLBACK_MIN_DIMENSION
}
private fun analyzeInternalConsistency(
faces: List<DetectedFaceWithEmbedding>
): Pair<Float, List<DetectedFaceWithEmbedding>> {
if (faces.size < 2) {
Log.d(TAG, "Less than 2 faces, skipping consistency check")
return 0f to emptyList()
}
Log.d(TAG, "Analyzing ${faces.size} faces for internal consistency")
val centroid = calculateCentroid(faces.map { it.embedding })
val centroidSum = centroid.sum()
Log.d(TAG, "Centroid sum: $centroidSum, first5=[${centroid.take(5).joinToString()}]")
val similarities = faces.mapIndexed { index, face ->
val similarity = cosineSimilarity(face.embedding, centroid)
Log.d(TAG, "Face $index similarity to centroid: $similarity")
face to similarity
}
val avgSimilarity = similarities.map { it.second }.average().toFloat()
Log.d(TAG, "Average internal similarity: $avgSimilarity")
val outliers = similarities
.filter { (_, similarity) -> similarity < OUTLIER_THRESHOLD }
.map { (face, _) -> face }
Log.d(TAG, "Found ${outliers.size} outliers (threshold=$OUTLIER_THRESHOLD)")
return avgSimilarity to outliers
}
private fun calculateCentroid(embeddings: List<FloatArray>): FloatArray {
val size = embeddings.first().size
val centroid = FloatArray(size) { 0f }
embeddings.forEach { embedding ->
for (i in embedding.indices) {
centroid[i] += embedding[i]
}
}
val count = embeddings.size.toFloat()
for (i in centroid.indices) {
centroid[i] /= count
}
val norm = sqrt(centroid.map { it * it }.sum())
return if (norm > 0) {
centroid.map { it / norm }.toFloatArray()
} else {
centroid
}
}
private fun cosineSimilarity(a: FloatArray, b: FloatArray): Float {
var dotProduct = 0f
var normA = 0f
var normB = 0f
for (i in a.indices) {
dotProduct += a[i] * b[i]
normA += a[i] * a[i]
normB += b[i] * b[i]
}
return dotProduct / (sqrt(normA) * sqrt(normB))
}
private fun calculateQualityScore(
soloPhotoCount: Int,
largeFaceCount: Int,
cleanFaceCount: Int,
avgSimilarity: Float,
totalFaces: Int
): Float {
val soloRatio = soloPhotoCount.toFloat() / totalFaces.toFloat().coerceAtLeast(1f)
val soloPhotoScore = soloRatio.coerceIn(0f, 1f) * 0.25f
val largeFaceScore = (largeFaceCount.toFloat() / 15f).coerceIn(0f, 1f) * 0.25f
val cleanFaceScore = (cleanFaceCount.toFloat() / 10f).coerceIn(0f, 1f) * 0.20f
val similarityScore = avgSimilarity * 0.30f
return soloPhotoScore + largeFaceScore + cleanFaceScore + similarityScore
}
private fun generateWarnings(
soloPhotoCount: Int,
largeFaceCount: Int,
cleanFaceCount: Int,
qualityTier: ClusterQualityTier,
avgSimilarity: Float
): List<String> {
val warnings = mutableListOf<String>()
when (qualityTier) {
ClusterQualityTier.POOR -> {
warnings.add("⚠️ POOR QUALITY - This cluster may contain multiple people!")
warnings.add("Do NOT train on this cluster - it will create a bad model.")
if (avgSimilarity < 0.70f) {
warnings.add("Low internal similarity (${(avgSimilarity * 100).toInt()}%) suggests mixed identities.")
}
}
ClusterQualityTier.GOOD -> {
warnings.add("⚠️ Review outlier faces before training")
if (cleanFaceCount < 10) {
warnings.add("Consider adding more high-quality photos for better results.")
}
}
ClusterQualityTier.EXCELLENT -> {
// No warnings
}
}
if (soloPhotoCount < MIN_SOLO_PHOTOS) {
warnings.add("Need at least $MIN_SOLO_PHOTOS solo photos (have $soloPhotoCount)")
}
if (largeFaceCount < 6) {
warnings.add("Only $largeFaceCount photos with large/clear faces (prefer 10+)")
warnings.add("Tip: Use close-up photos where the face is clearly visible")
}
if (cleanFaceCount < 6) {
warnings.add("After removing outliers: only $cleanFaceCount clean faces (need 6+)")
}
if (qualityTier == ClusterQualityTier.EXCELLENT) {
warnings.add("✅ Excellent quality! This cluster is ready for training.")
warnings.add("High-quality photos with consistent facial features detected.")
}
return warnings
}
}
data class ClusterQualityResult(
val originalFaceCount: Int,
val soloPhotoCount: Int,
val largeFaceCount: Int,
val cleanFaceCount: Int,
val avgInternalSimilarity: Float,
val outlierFaces: List<DetectedFaceWithEmbedding>,
val cleanFaces: List<DetectedFaceWithEmbedding>,
val qualityScore: Float,
val qualityTier: ClusterQualityTier,
val canTrain: Boolean,
val warnings: List<String>
) {
fun getSummary(): String = when (qualityTier) {
ClusterQualityTier.EXCELLENT ->
"Excellent quality cluster with $cleanFaceCount high-quality photos ready for training."
ClusterQualityTier.GOOD ->
"Good quality cluster with $cleanFaceCount usable photos. Review outliers before training."
ClusterQualityTier.POOR ->
"Poor quality cluster. May contain multiple people or low-quality photos. Add more photos or split cluster."
}
}
enum class ClusterQualityTier {
EXCELLENT, // 85%+
GOOD, // 75-84%
POOR // <75%
}

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package com.placeholder.sherpai2.domain.clustering
import android.util.Log
import com.placeholder.sherpai2.data.local.dao.FaceCacheDao
import com.placeholder.sherpai2.data.local.dao.UserFeedbackDao
import com.placeholder.sherpai2.data.local.entity.FeedbackType
import com.placeholder.sherpai2.data.local.entity.UserFeedbackEntity
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.withContext
import javax.inject.Inject
import javax.inject.Singleton
import kotlin.math.sqrt
/**
* ClusterRefinementService - Handle user feedback and cluster refinement
*
* PURPOSE:
* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
* Close the feedback loop between user corrections and clustering
*
* WORKFLOW:
* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
* 1. Clustering produces initial clusters
* 2. User reviews in ValidationPreview
* 3. User marks faces: ✅ Correct / ❌ Incorrect / ❓ Uncertain
* 4. If too many incorrect → Call refineCluster()
* 5. Re-cluster WITHOUT incorrect faces
* 6. Show updated validation preview
* 7. Repeat until user approves
*
* BENEFITS:
* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
* - Prevents bad models from being created
* - Learns from user corrections
* - Iterative improvement
* - Ground truth data for future enhancements
*/
@Singleton
class ClusterRefinementService @Inject constructor(
private val faceCacheDao: FaceCacheDao,
private val userFeedbackDao: UserFeedbackDao,
private val qualityAnalyzer: ClusterQualityAnalyzer
) {
companion object {
private const val TAG = "ClusterRefinement"
// Thresholds for refinement decisions
private const val MIN_REJECTION_RATIO = 0.15f // 15% rejected → refine
private const val MIN_CONFIRMED_FACES = 6 // Need at least 6 good faces
private const val MAX_REFINEMENT_ITERATIONS = 3 // Prevent infinite loops
}
/**
* Store user feedback for faces in a cluster
*
* @param cluster The cluster being reviewed
* @param feedbackMap Map of face index → feedback type
* @param originalConfidences Map of face index → original detection confidence
* @return Number of feedback items stored
*/
suspend fun storeFeedback(
cluster: FaceCluster,
feedbackMap: Map<DetectedFaceWithEmbedding, FeedbackType>,
originalConfidences: Map<DetectedFaceWithEmbedding, Float> = emptyMap()
): Int = withContext(Dispatchers.IO) {
val feedbackEntities = feedbackMap.map { (face, feedbackType) ->
UserFeedbackEntity.create(
imageId = face.imageId,
faceIndex = 0, // We don't track faceIndex in DetectedFaceWithEmbedding yet
clusterId = cluster.clusterId,
personId = null, // Not created yet
feedbackType = feedbackType,
originalConfidence = originalConfidences[face] ?: face.confidence
)
}
userFeedbackDao.insertAll(feedbackEntities)
Log.d(TAG, "Stored ${feedbackEntities.size} feedback items for cluster ${cluster.clusterId}")
feedbackEntities.size
}
/**
* Check if cluster needs refinement based on user feedback
*
* Criteria:
* - Too many rejected faces (> 15%)
* - Too few confirmed faces (< 6)
* - High rejection rate for cluster suggests mixed identities
*
* @return RefinementRecommendation with action and reason
*/
suspend fun shouldRefineCluster(
cluster: FaceCluster
): RefinementRecommendation = withContext(Dispatchers.Default) {
val feedback = withContext(Dispatchers.IO) {
userFeedbackDao.getFeedbackForCluster(cluster.clusterId)
}
if (feedback.isEmpty()) {
return@withContext RefinementRecommendation(
shouldRefine = false,
reason = "No feedback provided yet"
)
}
val totalFeedback = feedback.size
val rejectedCount = feedback.count { it.getFeedbackType() == FeedbackType.REJECTED_MATCH }
val confirmedCount = feedback.count { it.getFeedbackType() == FeedbackType.CONFIRMED_MATCH }
val uncertainCount = feedback.count { it.getFeedbackType() == FeedbackType.UNCERTAIN }
val rejectionRatio = rejectedCount.toFloat() / totalFeedback.toFloat()
Log.d(TAG, "Cluster ${cluster.clusterId} feedback: " +
"$confirmedCount confirmed, $rejectedCount rejected, $uncertainCount uncertain")
// Check 1: Too many rejections
if (rejectionRatio > MIN_REJECTION_RATIO) {
return@withContext RefinementRecommendation(
shouldRefine = true,
reason = "High rejection rate (${(rejectionRatio * 100).toInt()}%) suggests mixed identities",
confirmedCount = confirmedCount,
rejectedCount = rejectedCount,
uncertainCount = uncertainCount
)
}
// Check 2: Too few confirmed faces after removing rejected
val effectiveConfirmedCount = confirmedCount - rejectedCount
if (effectiveConfirmedCount < MIN_CONFIRMED_FACES) {
return@withContext RefinementRecommendation(
shouldRefine = true,
reason = "Only $effectiveConfirmedCount faces remain after removing rejected faces (need $MIN_CONFIRMED_FACES)",
confirmedCount = confirmedCount,
rejectedCount = rejectedCount,
uncertainCount = uncertainCount
)
}
// Cluster is good!
RefinementRecommendation(
shouldRefine = false,
reason = "Cluster quality acceptable: $confirmedCount confirmed, $rejectedCount rejected",
confirmedCount = confirmedCount,
rejectedCount = rejectedCount,
uncertainCount = uncertainCount
)
}
/**
* Refine cluster by removing rejected faces and re-clustering
*
* ALGORITHM:
* 1. Get all rejected faces from feedback
* 2. Remove those faces from cluster
* 3. Recalculate cluster centroid
* 4. Re-run quality analysis
* 5. Return refined cluster
*
* @param cluster Original cluster to refine
* @return Refined cluster without rejected faces
*/
suspend fun refineCluster(
cluster: FaceCluster,
iterationNumber: Int = 1
): ClusterRefinementResult = withContext(Dispatchers.Default) {
Log.d(TAG, "Refining cluster ${cluster.clusterId} (iteration $iterationNumber)")
// Guard against infinite refinement
if (iterationNumber > MAX_REFINEMENT_ITERATIONS) {
return@withContext ClusterRefinementResult(
success = false,
refinedCluster = null,
errorMessage = "Maximum refinement iterations reached. Cluster quality still poor.",
facesRemoved = 0,
facesRemaining = cluster.faces.size
)
}
// Get rejected faces
val feedback = withContext(Dispatchers.IO) {
userFeedbackDao.getRejectedFacesForCluster(cluster.clusterId)
}
val rejectedImageIds = feedback.map { it.imageId }.toSet()
if (rejectedImageIds.isEmpty()) {
return@withContext ClusterRefinementResult(
success = false,
refinedCluster = cluster,
errorMessage = "No rejected faces to remove",
facesRemoved = 0,
facesRemaining = cluster.faces.size
)
}
// Remove rejected faces
val cleanFaces = cluster.faces.filter { it.imageId !in rejectedImageIds }
Log.d(TAG, "Removed ${rejectedImageIds.size} rejected faces, ${cleanFaces.size} remain")
// Check if we have enough faces left
if (cleanFaces.size < MIN_CONFIRMED_FACES) {
return@withContext ClusterRefinementResult(
success = false,
refinedCluster = null,
errorMessage = "Too few faces remaining after removing rejected faces (${cleanFaces.size} < $MIN_CONFIRMED_FACES)",
facesRemoved = rejectedImageIds.size,
facesRemaining = cleanFaces.size
)
}
// Recalculate centroid
val newCentroid = calculateCentroid(cleanFaces.map { it.embedding })
// Select new representative faces
val newRepresentatives = selectRepresentativeFacesByCentroid(cleanFaces, newCentroid, count = 6)
// Create refined cluster
val refinedCluster = FaceCluster(
clusterId = cluster.clusterId,
faces = cleanFaces,
representativeFaces = newRepresentatives,
photoCount = cleanFaces.map { it.imageId }.distinct().size,
averageConfidence = cleanFaces.map { it.confidence }.average().toFloat(),
estimatedAge = cluster.estimatedAge, // Keep same estimate
potentialSiblings = cluster.potentialSiblings // Keep same siblings
)
// Re-run quality analysis
val qualityResult = qualityAnalyzer.analyzeCluster(refinedCluster)
Log.d(TAG, "Refined cluster quality: ${qualityResult.qualityTier} " +
"(${qualityResult.cleanFaceCount} clean faces)")
ClusterRefinementResult(
success = true,
refinedCluster = refinedCluster,
qualityResult = qualityResult,
facesRemoved = rejectedImageIds.size,
facesRemaining = cleanFaces.size,
newQualityTier = qualityResult.qualityTier
)
}
/**
* Get feedback summary for cluster
*
* Returns human-readable summary like:
* "15 confirmed, 3 rejected, 2 uncertain"
*/
suspend fun getFeedbackSummary(clusterId: Int): FeedbackSummary = withContext(Dispatchers.IO) {
val feedback = userFeedbackDao.getFeedbackForCluster(clusterId)
val confirmed = feedback.count { it.getFeedbackType() == FeedbackType.CONFIRMED_MATCH }
val rejected = feedback.count { it.getFeedbackType() == FeedbackType.REJECTED_MATCH }
val uncertain = feedback.count { it.getFeedbackType() == FeedbackType.UNCERTAIN }
val outliers = feedback.count { it.getFeedbackType() == FeedbackType.MARKED_OUTLIER }
FeedbackSummary(
totalFeedback = feedback.size,
confirmedCount = confirmed,
rejectedCount = rejected,
uncertainCount = uncertain,
outlierCount = outliers,
rejectionRatio = if (feedback.isNotEmpty()) {
rejected.toFloat() / feedback.size.toFloat()
} else 0f
)
}
/**
* Filter cluster to only confirmed faces
*
* Use Case: User has reviewed cluster, now create model using ONLY confirmed faces
*/
suspend fun getConfirmedFaces(cluster: FaceCluster): List<DetectedFaceWithEmbedding> =
withContext(Dispatchers.Default) {
val confirmedFeedback = withContext(Dispatchers.IO) {
userFeedbackDao.getConfirmedFacesForCluster(cluster.clusterId)
}
val confirmedImageIds = confirmedFeedback.map { it.imageId }.toSet()
// If no explicit confirmations, assume all non-rejected faces are OK
if (confirmedImageIds.isEmpty()) {
val rejectedFeedback = withContext(Dispatchers.IO) {
userFeedbackDao.getRejectedFacesForCluster(cluster.clusterId)
}
val rejectedImageIds = rejectedFeedback.map { it.imageId }.toSet()
return@withContext cluster.faces.filter { it.imageId !in rejectedImageIds }
}
// Return only explicitly confirmed faces
cluster.faces.filter { it.imageId in confirmedImageIds }
}
/**
* Calculate centroid from embeddings
*/
private fun calculateCentroid(embeddings: List<FloatArray>): FloatArray {
if (embeddings.isEmpty()) return FloatArray(0)
val size = embeddings.first().size
val centroid = FloatArray(size) { 0f }
embeddings.forEach { embedding ->
for (i in embedding.indices) {
centroid[i] += embedding[i]
}
}
val count = embeddings.size.toFloat()
for (i in centroid.indices) {
centroid[i] /= count
}
// Normalize
val norm = sqrt(centroid.map { it * it }.sum())
return if (norm > 0) {
centroid.map { it / norm }.toFloatArray()
} else {
centroid
}
}
/**
* Select representative faces closest to centroid
*/
private fun selectRepresentativeFacesByCentroid(
faces: List<DetectedFaceWithEmbedding>,
centroid: FloatArray,
count: Int
): List<DetectedFaceWithEmbedding> {
if (faces.size <= count) return faces
val facesWithDistance = faces.map { face ->
val similarity = cosineSimilarity(face.embedding, centroid)
val distance = 1 - similarity
face to distance
}
return facesWithDistance
.sortedBy { it.second }
.take(count)
.map { it.first }
}
/**
* Cosine similarity calculation
*/
private fun cosineSimilarity(a: FloatArray, b: FloatArray): Float {
var dotProduct = 0f
var normA = 0f
var normB = 0f
for (i in a.indices) {
dotProduct += a[i] * b[i]
normA += a[i] * a[i]
normB += b[i] * b[i]
}
return dotProduct / (sqrt(normA) * sqrt(normB))
}
}
/**
* Result of refinement analysis
*/
data class RefinementRecommendation(
val shouldRefine: Boolean,
val reason: String,
val confirmedCount: Int = 0,
val rejectedCount: Int = 0,
val uncertainCount: Int = 0
)
/**
* Result of cluster refinement
*/
data class ClusterRefinementResult(
val success: Boolean,
val refinedCluster: FaceCluster?,
val qualityResult: ClusterQualityResult? = null,
val errorMessage: String? = null,
val facesRemoved: Int,
val facesRemaining: Int,
val newQualityTier: ClusterQualityTier? = null
)
/**
* Summary of user feedback for a cluster
*/
data class FeedbackSummary(
val totalFeedback: Int,
val confirmedCount: Int,
val rejectedCount: Int,
val uncertainCount: Int,
val outlierCount: Int,
val rejectionRatio: Float
) {
fun getDisplayText(): String {
val parts = mutableListOf<String>()
if (confirmedCount > 0) parts.add("$confirmedCount confirmed")
if (rejectedCount > 0) parts.add("$rejectedCount rejected")
if (uncertainCount > 0) parts.add("$uncertainCount uncertain")
return parts.joinToString(", ")
}
}

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package com.placeholder.sherpai2.domain.clustering
import android.content.Context
import android.graphics.Bitmap
import android.graphics.BitmapFactory
import android.graphics.Rect
import android.net.Uri
import android.util.Log
import com.google.android.gms.tasks.Tasks
import com.google.mlkit.vision.common.InputImage
import com.google.mlkit.vision.face.FaceDetection
import com.google.mlkit.vision.face.FaceDetectorOptions
import com.placeholder.sherpai2.data.local.dao.FaceCacheDao
import com.placeholder.sherpai2.data.local.dao.ImageDao
import com.placeholder.sherpai2.data.local.entity.FaceCacheEntity
import com.placeholder.sherpai2.data.local.entity.ImageEntity
import com.placeholder.sherpai2.ml.FaceNetModel
import com.placeholder.sherpai2.ui.discover.DiscoverySettings
import dagger.hilt.android.qualifiers.ApplicationContext
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.async
import kotlinx.coroutines.awaitAll
import kotlinx.coroutines.coroutineScope
import kotlinx.coroutines.sync.Semaphore
import kotlinx.coroutines.withContext
import javax.inject.Inject
import javax.inject.Singleton
import kotlin.math.max
import kotlin.math.min
import kotlin.math.sqrt
/**
* FaceClusteringService - FIXED to properly use metadata cache
*
* THE CRITICAL FIX:
* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
* Path 2 now CORRECTLY checks for metadata cache WITHOUT requiring embeddings
* Uses countFacesWithoutEmbeddings() which counts faces that HAVE metadata
* but DON'T have embeddings yet
*
* 3-PATH STRATEGY (CORRECTED):
* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
* Path 1: Cached embeddings exist → Instant (< 2 sec)
* Path 2: Metadata cache exists → Generate embeddings for quality faces (~3 min) ← FIXED!
* Path 3: No cache → Full scan (~8 min)
*/
@Singleton
class FaceClusteringService @Inject constructor(
@ApplicationContext private val context: Context,
private val imageDao: ImageDao,
private val faceCacheDao: FaceCacheDao
) {
private val semaphore = Semaphore(3)
companion object {
private const val TAG = "FaceClustering"
private const val MAX_FACES_TO_CLUSTER = 2000
// Path selection thresholds
private const val MIN_CACHED_EMBEDDINGS = 20 // Path 1
private const val MIN_QUALITY_METADATA = 50 // Path 2
private const val MIN_STANDARD_FACES = 10 // Absolute minimum
// IoU matching threshold
private const val IOU_THRESHOLD = 0.5f
}
suspend fun discoverPeople(
strategy: ClusteringStrategy = ClusteringStrategy.PREMIUM_SOLO_ONLY,
maxFacesToCluster: Int = MAX_FACES_TO_CLUSTER,
onProgress: (Int, Int, String) -> Unit = { _, _, _ -> }
): ClusteringResult = withContext(Dispatchers.Default) {
val startTime = System.currentTimeMillis()
Log.d(TAG, "════════════════════════════════════════")
Log.d(TAG, "CACHE-AWARE DISCOVERY STARTED")
Log.d(TAG, "════════════════════════════════════════")
val result = when (strategy) {
ClusteringStrategy.PREMIUM_SOLO_ONLY -> {
clusterPremiumSoloFaces(maxFacesToCluster, onProgress)
}
ClusteringStrategy.STANDARD_SOLO_ONLY -> {
clusterStandardSoloFaces(maxFacesToCluster, onProgress)
}
ClusteringStrategy.TWO_PHASE -> {
clusterPremiumSoloFaces(maxFacesToCluster, onProgress)
}
ClusteringStrategy.LEGACY_ALL_FACES -> {
clusterAllFacesLegacy(maxFacesToCluster, onProgress)
}
}
val elapsedTime = System.currentTimeMillis() - startTime
Log.d(TAG, "════════════════════════════════════════")
Log.d(TAG, "Discovery Complete!")
Log.d(TAG, "Clusters found: ${result.clusters.size}")
Log.d(TAG, "Time: ${elapsedTime / 1000}s")
Log.d(TAG, "════════════════════════════════════════")
result.copy(processingTimeMs = elapsedTime)
}
/**
* FIXED: 3-Path Selection with proper metadata checking
*/
private suspend fun clusterPremiumSoloFaces(
maxFaces: Int,
onProgress: (Int, Int, String) -> Unit
): ClusteringResult = withContext(Dispatchers.Default) {
onProgress(5, 100, "Checking cache...")
// ═════════════════════════════════════════════════════════
// PATH 1: Check for cached embeddings (INSTANT)
// ═════════════════════════════════════════════════════════
Log.d(TAG, "Path 1: Checking for cached embeddings...")
val embeddingCount = withContext(Dispatchers.IO) {
try {
faceCacheDao.countFacesWithEmbeddings(minQuality = 0.6f)
} catch (e: Exception) {
Log.w(TAG, "Error counting embeddings: ${e.message}")
0
}
}
Log.d(TAG, "Found $embeddingCount faces with cached embeddings")
if (embeddingCount >= MIN_CACHED_EMBEDDINGS) {
Log.d(TAG, "✅ PATH 1 SUCCESS: Using $embeddingCount cached embeddings")
val cachedFaces = withContext(Dispatchers.IO) {
faceCacheDao.getAllQualityFaces(
minRatio = 0.03f,
minQuality = 0.6f,
limit = Int.MAX_VALUE
)
}
return@withContext clusterCachedEmbeddings(cachedFaces, maxFaces, onProgress)
}
// ═════════════════════════════════════════════════════════
// PATH 2: Check for metadata cache (FAST)
// ═════════════════════════════════════════════════════════
Log.d(TAG, "Path 1 insufficient, trying Path 2...")
Log.d(TAG, "Path 2: Checking for quality metadata...")
// THE CRITICAL FIX: Count faces WITH metadata but WITHOUT embeddings
val metadataCount = withContext(Dispatchers.IO) {
try {
faceCacheDao.countFacesWithoutEmbeddings(minQuality = 0.6f)
} catch (e: Exception) {
Log.w(TAG, "Error counting metadata: ${e.message}")
0
}
}
Log.d(TAG, "Found $metadataCount faces in metadata cache (without embeddings)")
if (metadataCount >= MIN_QUALITY_METADATA) {
Log.d(TAG, "✅ PATH 2 SUCCESS: Using metadata cache")
val qualityMetadata = withContext(Dispatchers.IO) {
faceCacheDao.getQualityFacesWithoutEmbeddings(
minRatio = 0.03f,
minQuality = 0.6f,
limit = 5000
)
}
Log.d(TAG, "Loaded ${qualityMetadata.size} quality face metadata entries")
return@withContext clusterWithQualityPrefiltering(qualityMetadata, maxFaces, onProgress)
}
// ═════════════════════════════════════════════════════════
// PATH 3: Full scan (SLOW, last resort)
// ═════════════════════════════════════════════════════════
Log.w(TAG, "Path 2 insufficient, falling back to Path 3 (full scan)")
Log.w(TAG, "⚠️ PATH 3: Full library scan (this will take several minutes)")
Log.w(TAG, "Cache stats: $embeddingCount with embeddings, $metadataCount metadata only")
onProgress(10, 100, "No cache found, performing full scan...")
return@withContext clusterAllFacesLegacy(maxFaces, onProgress)
}
/**
* Path 1: Cluster using cached embeddings (INSTANT)
*/
private suspend fun clusterCachedEmbeddings(
cachedFaces: List<FaceCacheEntity>,
maxFaces: Int,
onProgress: (Int, Int, String) -> Unit
): ClusteringResult = withContext(Dispatchers.Default) {
Log.d(TAG, "Converting ${cachedFaces.size} cached faces to clustering format...")
onProgress(30, 100, "Using ${cachedFaces.size} cached faces...")
val allFaces = cachedFaces.mapNotNull { cached ->
val embedding = cached.getEmbedding() ?: return@mapNotNull null
DetectedFaceWithEmbedding(
imageId = cached.imageId,
imageUri = "",
capturedAt = cached.detectedAt,
embedding = embedding,
boundingBox = cached.getBoundingBox(),
confidence = cached.confidence,
faceCount = 1,
imageWidth = cached.imageWidth,
imageHeight = cached.imageHeight
)
}
if (allFaces.isEmpty()) {
return@withContext ClusteringResult(
clusters = emptyList(),
totalFacesAnalyzed = 0,
processingTimeMs = 0,
errorMessage = "No valid cached embeddings found"
)
}
Log.d(TAG, "Clustering ${allFaces.size} cached faces...")
onProgress(50, 100, "Clustering ${allFaces.size} faces...")
val rawClusters = performDBSCAN(
faces = allFaces.take(maxFaces),
epsilon = 0.22f,
minPoints = 3
)
onProgress(75, 100, "Analyzing relationships...")
val coOccurrenceGraph = buildCoOccurrenceGraph(rawClusters)
onProgress(90, 100, "Finalizing clusters...")
val clusters = rawClusters.mapIndexed { index, cluster ->
FaceCluster(
clusterId = index,
faces = cluster.faces,
representativeFaces = selectRepresentativeFacesByCentroid(cluster.faces, count = 6),
photoCount = cluster.faces.map { it.imageId }.distinct().size,
averageConfidence = cluster.faces.map { it.confidence }.average().toFloat(),
estimatedAge = estimateAge(cluster.faces),
potentialSiblings = findPotentialSiblings(cluster, rawClusters, coOccurrenceGraph)
)
}.sortedByDescending { it.photoCount }
onProgress(100, 100, "Complete!")
ClusteringResult(
clusters = clusters,
totalFacesAnalyzed = allFaces.size,
processingTimeMs = 0,
strategy = ClusteringStrategy.PREMIUM_SOLO_ONLY
)
}
/**
* Path 2: CORRECTED to work with metadata cache
*
* Generates embeddings on-demand and saves them with IoU matching
*/
private suspend fun clusterWithQualityPrefiltering(
qualityFacesMetadata: List<FaceCacheEntity>,
maxFaces: Int,
onProgress: (Int, Int, String) -> Unit
): ClusteringResult = withContext(Dispatchers.Default) {
Log.d(TAG, "Starting Path 2: Quality metadata pre-filtering")
Log.d(TAG, "Quality faces in metadata: ${qualityFacesMetadata.size}")
onProgress(15, 100, "Pre-filtering complete...")
// Extract unique imageIds from metadata
val imageIdsToProcess = qualityFacesMetadata
.map { it.imageId }
.distinct()
Log.d(TAG, "Pre-filtered to ${imageIdsToProcess.size} images with quality faces")
// Load only those specific images
val imagesToProcess = withContext(Dispatchers.IO) {
imageDao.getImagesByIds(imageIdsToProcess)
}
Log.d(TAG, "Loading ${imagesToProcess.size} quality photos...")
onProgress(20, 100, "Generating embeddings for ${imagesToProcess.size} quality photos...")
val faceNetModel = FaceNetModel(context)
val detector = FaceDetection.getClient(
FaceDetectorOptions.Builder()
.setPerformanceMode(FaceDetectorOptions.PERFORMANCE_MODE_ACCURATE)
.setLandmarkMode(FaceDetectorOptions.LANDMARK_MODE_ALL)
.setMinFaceSize(0.15f)
.build()
)
try {
val allFaces = mutableListOf<DetectedFaceWithEmbedding>()
var iouMatchSuccesses = 0
var iouMatchFailures = 0
coroutineScope {
val jobs = imagesToProcess.mapIndexed { index, image ->
async(Dispatchers.IO) {
semaphore.acquire()
try {
val bitmap = loadBitmapDownsampled(
Uri.parse(image.imageUri),
768
) ?: return@async Triple(emptyList<DetectedFaceWithEmbedding>(), 0, 0)
val inputImage = InputImage.fromBitmap(bitmap, 0)
val mlKitFaces = Tasks.await(detector.process(inputImage))
val imageWidth = bitmap.width
val imageHeight = bitmap.height
// Get cached faces for THIS specific image
val cachedFacesForImage = qualityFacesMetadata.filter {
it.imageId == image.imageId
}
var localSuccesses = 0
var localFailures = 0
val facesForImage = mutableListOf<DetectedFaceWithEmbedding>()
mlKitFaces.forEach { mlFace ->
val qualityCheck = FaceQualityFilter.validateForDiscovery(
face = mlFace,
imageWidth = imageWidth,
imageHeight = imageHeight
)
if (!qualityCheck.isValid) {
return@forEach
}
try {
// Crop and generate embedding
val faceBitmap = Bitmap.createBitmap(
bitmap,
mlFace.boundingBox.left.coerceIn(0, bitmap.width - 1),
mlFace.boundingBox.top.coerceIn(0, bitmap.height - 1),
mlFace.boundingBox.width().coerceAtMost(bitmap.width - mlFace.boundingBox.left),
mlFace.boundingBox.height().coerceAtMost(bitmap.height - mlFace.boundingBox.top)
)
val embedding = faceNetModel.generateEmbedding(faceBitmap)
faceBitmap.recycle()
// Add to results
facesForImage.add(
DetectedFaceWithEmbedding(
imageId = image.imageId,
imageUri = image.imageUri,
capturedAt = image.capturedAt,
embedding = embedding,
boundingBox = mlFace.boundingBox,
confidence = qualityCheck.confidenceScore,
faceCount = mlKitFaces.size,
imageWidth = imageWidth,
imageHeight = imageHeight
)
)
// Save embedding to cache with IoU matching
val matched = matchAndSaveEmbedding(
imageId = image.imageId,
detectedBox = mlFace.boundingBox,
embedding = embedding,
cachedFaces = cachedFacesForImage
)
if (matched) localSuccesses++ else localFailures++
} catch (e: Exception) {
Log.w(TAG, "Failed to process face: ${e.message}")
}
}
bitmap.recycle()
// Update progress
if (index % 20 == 0) {
val progress = 20 + (index * 60 / imagesToProcess.size)
onProgress(progress, 100, "Processed $index/${imagesToProcess.size} photos...")
}
Triple(facesForImage, localSuccesses, localFailures)
} finally {
semaphore.release()
}
}
}
val results = jobs.awaitAll()
results.forEach { (faces, successes, failures) ->
allFaces.addAll(faces)
iouMatchSuccesses += successes
iouMatchFailures += failures
}
}
Log.d(TAG, "IoU Matching Results:")
Log.d(TAG, " Successful matches: $iouMatchSuccesses")
Log.d(TAG, " Failed matches: $iouMatchFailures")
val successRate = if (iouMatchSuccesses + iouMatchFailures > 0) {
(iouMatchSuccesses.toFloat() / (iouMatchSuccesses + iouMatchFailures) * 100).toInt()
} else 0
Log.d(TAG, " Success rate: $successRate%")
Log.d(TAG, "✅ Embeddings saved to cache with IoU matching")
if (allFaces.isEmpty()) {
return@withContext ClusteringResult(
clusters = emptyList(),
totalFacesAnalyzed = 0,
processingTimeMs = 0,
errorMessage = "No faces detected with sufficient quality"
)
}
// Cluster
onProgress(80, 100, "Clustering ${allFaces.size} faces...")
val rawClusters = performDBSCAN(allFaces.take(maxFaces), 0.22f, 3)
val coOccurrenceGraph = buildCoOccurrenceGraph(rawClusters)
onProgress(90, 100, "Finalizing clusters...")
val clusters = rawClusters.mapIndexed { index, cluster ->
FaceCluster(
clusterId = index,
faces = cluster.faces,
representativeFaces = selectRepresentativeFacesByCentroid(cluster.faces, count = 6),
photoCount = cluster.faces.map { it.imageId }.distinct().size,
averageConfidence = cluster.faces.map { it.confidence }.average().toFloat(),
estimatedAge = estimateAge(cluster.faces),
potentialSiblings = findPotentialSiblings(cluster, rawClusters, coOccurrenceGraph)
)
}.sortedByDescending { it.photoCount }
onProgress(100, 100, "Complete!")
ClusteringResult(
clusters = clusters,
totalFacesAnalyzed = allFaces.size,
processingTimeMs = 0,
strategy = ClusteringStrategy.PREMIUM_SOLO_ONLY
)
} finally {
detector.close()
}
}
/**
* IoU matching and saving - handles non-deterministic ML Kit order
*/
private suspend fun matchAndSaveEmbedding(
imageId: String,
detectedBox: Rect,
embedding: FloatArray,
cachedFaces: List<FaceCacheEntity>
): Boolean {
if (cachedFaces.isEmpty()) {
return false
}
// Find best matching cached face by IoU
var bestMatch: FaceCacheEntity? = null
var bestIoU = 0f
cachedFaces.forEach { cached ->
val iou = calculateIoU(detectedBox, cached.getBoundingBox())
if (iou > bestIoU) {
bestIoU = iou
bestMatch = cached
}
}
// Save if IoU meets threshold
if (bestMatch != null && bestIoU >= IOU_THRESHOLD) {
try {
withContext(Dispatchers.IO) {
val updated = bestMatch!!.copy(
embedding = embedding.joinToString(",")
)
faceCacheDao.update(updated)
}
return true
} catch (e: Exception) {
Log.e(TAG, "Failed to save embedding: ${e.message}")
return false
}
}
return false
}
/**
* Calculate IoU between two bounding boxes
*/
private fun calculateIoU(rect1: Rect, rect2: Rect): Float {
val intersectionLeft = max(rect1.left, rect2.left)
val intersectionTop = max(rect1.top, rect2.top)
val intersectionRight = min(rect1.right, rect2.right)
val intersectionBottom = min(rect1.bottom, rect2.bottom)
if (intersectionLeft >= intersectionRight || intersectionTop >= intersectionBottom) {
return 0f
}
val intersectionArea = (intersectionRight - intersectionLeft) * (intersectionBottom - intersectionTop)
val area1 = rect1.width() * rect1.height()
val area2 = rect2.width() * rect2.height()
val unionArea = area1 + area2 - intersectionArea
return if (unionArea > 0) {
intersectionArea.toFloat() / unionArea.toFloat()
} else {
0f
}
}
private suspend fun clusterStandardSoloFaces(
maxFaces: Int,
onProgress: (Int, Int, String) -> Unit
): ClusteringResult = clusterPremiumSoloFaces(maxFaces, onProgress)
/**
* Path 3: Legacy full scan (fallback only)
*/
private suspend fun clusterAllFacesLegacy(
maxFaces: Int,
onProgress: (Int, Int, String) -> Unit
): ClusteringResult = withContext(Dispatchers.Default) {
Log.w(TAG, "⚠️ Running LEGACY full scan")
onProgress(10, 100, "Loading all images...")
val allImages = withContext(Dispatchers.IO) {
imageDao.getAllImages()
}
Log.d(TAG, "Processing ${allImages.size} images...")
onProgress(20, 100, "Detecting faces in ${allImages.size} photos...")
val faceNetModel = FaceNetModel(context)
val detector = FaceDetection.getClient(
FaceDetectorOptions.Builder()
.setPerformanceMode(FaceDetectorOptions.PERFORMANCE_MODE_ACCURATE)
.setLandmarkMode(FaceDetectorOptions.LANDMARK_MODE_ALL)
.setMinFaceSize(0.15f)
.build()
)
try {
val allFaces = mutableListOf<DetectedFaceWithEmbedding>()
coroutineScope {
val jobs = allImages.mapIndexed { index, image ->
async(Dispatchers.IO) {
semaphore.acquire()
try {
val bitmap = loadBitmapDownsampled(
Uri.parse(image.imageUri),
768
) ?: return@async emptyList()
val inputImage = InputImage.fromBitmap(bitmap, 0)
val faces = Tasks.await(detector.process(inputImage))
val imageWidth = bitmap.width
val imageHeight = bitmap.height
val faceEmbeddings = faces.mapNotNull { face ->
val qualityCheck = FaceQualityFilter.validateForDiscovery(
face = face,
imageWidth = imageWidth,
imageHeight = imageHeight
)
if (!qualityCheck.isValid) return@mapNotNull null
try {
val faceBitmap = Bitmap.createBitmap(
bitmap,
face.boundingBox.left.coerceIn(0, bitmap.width - 1),
face.boundingBox.top.coerceIn(0, bitmap.height - 1),
face.boundingBox.width().coerceAtMost(bitmap.width - face.boundingBox.left),
face.boundingBox.height().coerceAtMost(bitmap.height - face.boundingBox.top)
)
val embedding = faceNetModel.generateEmbedding(faceBitmap)
faceBitmap.recycle()
DetectedFaceWithEmbedding(
imageId = image.imageId,
imageUri = image.imageUri,
capturedAt = image.capturedAt,
embedding = embedding,
boundingBox = face.boundingBox,
confidence = qualityCheck.confidenceScore,
faceCount = faces.size,
imageWidth = imageWidth,
imageHeight = imageHeight
)
} catch (e: Exception) {
null
}
}
bitmap.recycle()
if (index % 20 == 0) {
val progress = 20 + (index * 60 / allImages.size)
onProgress(progress, 100, "Processed $index/${allImages.size} photos...")
}
faceEmbeddings
} finally {
semaphore.release()
}
}
}
jobs.awaitAll().flatten().forEach { allFaces.add(it) }
}
if (allFaces.isEmpty()) {
return@withContext ClusteringResult(
clusters = emptyList(),
totalFacesAnalyzed = 0,
processingTimeMs = 0,
errorMessage = "No faces detected"
)
}
onProgress(80, 100, "Clustering ${allFaces.size} faces...")
val rawClusters = performDBSCAN(allFaces.take(maxFaces), 0.22f, 3)
val coOccurrenceGraph = buildCoOccurrenceGraph(rawClusters)
onProgress(90, 100, "Finalizing clusters...")
val clusters = rawClusters.mapIndexed { index, cluster ->
FaceCluster(
clusterId = index,
faces = cluster.faces,
representativeFaces = selectRepresentativeFacesByCentroid(cluster.faces, count = 6),
photoCount = cluster.faces.map { it.imageId }.distinct().size,
averageConfidence = cluster.faces.map { it.confidence }.average().toFloat(),
estimatedAge = estimateAge(cluster.faces),
potentialSiblings = findPotentialSiblings(cluster, rawClusters, coOccurrenceGraph)
)
}.sortedByDescending { it.photoCount }
onProgress(100, 100, "Complete!")
ClusteringResult(
clusters = clusters,
totalFacesAnalyzed = allFaces.size,
processingTimeMs = 0,
strategy = ClusteringStrategy.LEGACY_ALL_FACES
)
} finally {
detector.close()
}
}
// REPLACE the discoverPeopleWithSettings method (lines 679-716) with this:
suspend fun discoverPeopleWithSettings(
settings: DiscoverySettings,
onProgress: (Int, Int, String) -> Unit = { _, _, _ -> }
): ClusteringResult = withContext(Dispatchers.Default) {
Log.d(TAG, "════════════════════════════════════════")
Log.d(TAG, "🎛️ DISCOVERY WITH CUSTOM SETTINGS")
Log.d(TAG, "════════════════════════════════════════")
Log.d(TAG, "Settings received:")
Log.d(TAG, " • minFaceSize: ${settings.minFaceSize} (${(settings.minFaceSize * 100).toInt()}%)")
Log.d(TAG, " • minQuality: ${settings.minQuality} (${(settings.minQuality * 100).toInt()}%)")
Log.d(TAG, " • epsilon: ${settings.epsilon}")
Log.d(TAG, "════════════════════════════════════════")
// Get quality faces using settings
val qualityMetadata = withContext(Dispatchers.IO) {
faceCacheDao.getQualityFacesWithoutEmbeddings(
minRatio = settings.minFaceSize,
minQuality = settings.minQuality,
limit = 5000
)
}
Log.d(TAG, "Found ${qualityMetadata.size} faces matching quality settings")
Log.d(TAG, " • Query used: minRatio=${settings.minFaceSize}, minQuality=${settings.minQuality}")
// Adjust threshold based on library size
val minRequired = if (qualityMetadata.size < 50) 30 else 50
Log.d(TAG, "Path selection:")
Log.d(TAG, " • Faces available: ${qualityMetadata.size}")
Log.d(TAG, " • Minimum required: $minRequired")
if (qualityMetadata.size >= minRequired) {
Log.d(TAG, "✅ Using Path 2 (quality pre-filtering)")
Log.d(TAG, "════════════════════════════════════════")
// Use Path 2 (quality pre-filtering)
return@withContext clusterWithQualityPrefiltering(
qualityFacesMetadata = qualityMetadata,
maxFaces = MAX_FACES_TO_CLUSTER,
onProgress = onProgress
)
} else {
Log.d(TAG, "⚠️ Using fallback path (standard discovery)")
Log.d(TAG, " • Reason: ${qualityMetadata.size} < $minRequired")
Log.d(TAG, "════════════════════════════════════════")
// Fallback to regular discovery (no Path 3, use existing methods)
Log.w(TAG, "Insufficient metadata (${qualityMetadata.size} < $minRequired), using standard discovery")
// Use existing discoverPeople with appropriate strategy
val strategy = if (settings.minQuality >= 0.7f) {
ClusteringStrategy.PREMIUM_SOLO_ONLY
} else {
ClusteringStrategy.STANDARD_SOLO_ONLY
}
return@withContext discoverPeople(
strategy = strategy,
maxFacesToCluster = MAX_FACES_TO_CLUSTER,
onProgress = onProgress
)
}
}
// Clustering algorithms (unchanged)
private fun performDBSCAN(faces: List<DetectedFaceWithEmbedding>, epsilon: Float, minPoints: Int): List<RawCluster> {
val visited = mutableSetOf<Int>()
val clusters = mutableListOf<RawCluster>()
var clusterId = 0
for (i in faces.indices) {
if (i in visited) continue
val neighbors = findNeighbors(i, faces, epsilon)
if (neighbors.size < minPoints) {
visited.add(i)
continue
}
val cluster = mutableListOf<DetectedFaceWithEmbedding>()
val queue = ArrayDeque(listOf(i))
while (queue.isNotEmpty()) {
val pointIdx = queue.removeFirst()
if (pointIdx in visited) continue
visited.add(pointIdx)
cluster.add(faces[pointIdx])
val pointNeighbors = findNeighbors(pointIdx, faces, epsilon)
if (pointNeighbors.size >= minPoints) {
queue.addAll(pointNeighbors.filter { it !in visited })
}
}
if (cluster.size >= minPoints) {
clusters.add(RawCluster(clusterId++, cluster))
}
}
return clusters
}
private fun findNeighbors(pointIdx: Int, faces: List<DetectedFaceWithEmbedding>, epsilon: Float): List<Int> {
val point = faces[pointIdx]
return faces.indices.filter { i ->
if (i == pointIdx) return@filter false
val otherFace = faces[i]
val similarity = cosineSimilarity(point.embedding, otherFace.embedding)
val appearTogether = point.imageId == otherFace.imageId
val effectiveEpsilon = if (appearTogether) epsilon * 0.7f else epsilon
similarity > (1 - effectiveEpsilon)
}
}
private fun cosineSimilarity(a: FloatArray, b: FloatArray): Float {
var dotProduct = 0f
var normA = 0f
var normB = 0f
for (i in a.indices) {
dotProduct += a[i] * b[i]
normA += a[i] * a[i]
normB += b[i] * b[i]
}
return dotProduct / (sqrt(normA) * sqrt(normB))
}
private fun buildCoOccurrenceGraph(clusters: List<RawCluster>): Map<Int, Map<Int, Int>> {
val graph = mutableMapOf<Int, MutableMap<Int, Int>>()
for (i in clusters.indices) {
graph[i] = mutableMapOf()
val imageIds = clusters[i].faces.map { it.imageId }.toSet()
for (j in clusters.indices) {
if (i == j) continue
val sharedImages = clusters[j].faces.count { it.imageId in imageIds }
if (sharedImages > 0) {
graph[i]!![j] = sharedImages
}
}
}
return graph
}
private fun findPotentialSiblings(cluster: RawCluster, allClusters: List<RawCluster>, coOccurrenceGraph: Map<Int, Map<Int, Int>>): List<Int> {
val clusterIdx = allClusters.indexOf(cluster)
if (clusterIdx == -1) return emptyList()
return coOccurrenceGraph[clusterIdx]
?.filter { (_, count) -> count >= 5 }
?.keys
?.toList()
?: emptyList()
}
fun selectRepresentativeFacesByCentroid(faces: List<DetectedFaceWithEmbedding>, count: Int): List<DetectedFaceWithEmbedding> {
if (faces.size <= count) return faces
val centroid = calculateCentroid(faces.map { it.embedding })
val facesWithDistance = faces.map { face ->
val distance = 1 - cosineSimilarity(face.embedding, centroid)
face to distance
}
val sortedByProximity = facesWithDistance.sortedBy { it.second }
val representatives = mutableListOf<DetectedFaceWithEmbedding>()
representatives.add(sortedByProximity.first().first)
val remainingFaces = sortedByProximity.drop(1).take(count * 3)
val sortedByTime = remainingFaces.map { it.first }.sortedBy { it.capturedAt }
if (sortedByTime.isNotEmpty()) {
val step = sortedByTime.size / (count - 1).coerceAtLeast(1)
for (i in 0 until (count - 1)) {
val index = (i * step).coerceAtMost(sortedByTime.size - 1)
representatives.add(sortedByTime[index])
}
}
return representatives.take(count)
}
private fun calculateCentroid(embeddings: List<FloatArray>): FloatArray {
if (embeddings.isEmpty()) return FloatArray(0)
val size = embeddings.first().size
val centroid = FloatArray(size) { 0f }
embeddings.forEach { embedding ->
for (i in embedding.indices) {
centroid[i] += embedding[i]
}
}
val count = embeddings.size.toFloat()
for (i in centroid.indices) {
centroid[i] /= count
}
val norm = sqrt(centroid.map { it * it }.sum())
return if (norm > 0) {
centroid.map { it / norm }.toFloatArray()
} else {
centroid
}
}
private fun estimateAge(faces: List<DetectedFaceWithEmbedding>): AgeEstimate {
val timestamps = faces.map { it.capturedAt }.sorted()
if (timestamps.isEmpty() || timestamps.last() == 0L) return AgeEstimate.UNKNOWN
val span = timestamps.last() - timestamps.first()
val spanYears = span / (365.25 * 24 * 60 * 60 * 1000)
return if (spanYears > 3.0) AgeEstimate.CHILD else AgeEstimate.UNKNOWN
}
private fun loadBitmapDownsampled(uri: Uri, maxDim: Int): Bitmap? {
return try {
val opts = BitmapFactory.Options().apply { inJustDecodeBounds = true }
context.contentResolver.openInputStream(uri)?.use {
BitmapFactory.decodeStream(it, null, opts)
}
var sample = 1
while (opts.outWidth / sample > maxDim || opts.outHeight / sample > maxDim) {
sample *= 2
}
val finalOpts = BitmapFactory.Options().apply {
inSampleSize = sample
inPreferredConfig = Bitmap.Config.RGB_565
}
context.contentResolver.openInputStream(uri)?.use {
BitmapFactory.decodeStream(it, null, finalOpts)
}
} catch (e: Exception) {
null
}
}
}
enum class ClusteringStrategy {
PREMIUM_SOLO_ONLY,
STANDARD_SOLO_ONLY,
TWO_PHASE,
LEGACY_ALL_FACES
}
data class DetectedFaceWithEmbedding(
val imageId: String,
val imageUri: String,
val capturedAt: Long,
val embedding: FloatArray,
val boundingBox: android.graphics.Rect,
val confidence: Float,
val faceCount: Int = 1,
val imageWidth: Int = 0,
val imageHeight: Int = 0
) {
override fun equals(other: Any?): Boolean {
if (this === other) return true
if (javaClass != other?.javaClass) return false
other as DetectedFaceWithEmbedding
return imageId == other.imageId
}
override fun hashCode(): Int = imageId.hashCode()
}
data class RawCluster(
val clusterId: Int,
val faces: List<DetectedFaceWithEmbedding>
)
data class FaceCluster(
val clusterId: Int,
val faces: List<DetectedFaceWithEmbedding>,
val representativeFaces: List<DetectedFaceWithEmbedding>,
val photoCount: Int,
val averageConfidence: Float,
val estimatedAge: AgeEstimate,
val potentialSiblings: List<Int>
)
data class ClusteringResult(
val clusters: List<FaceCluster>,
val totalFacesAnalyzed: Int,
val processingTimeMs: Long,
val errorMessage: String? = null,
val strategy: ClusteringStrategy = ClusteringStrategy.PREMIUM_SOLO_ONLY
)
enum class AgeEstimate {
CHILD,
ADULT,
UNKNOWN
}

View File

@@ -0,0 +1,140 @@
package com.placeholder.sherpai2.domain.clustering
import com.google.mlkit.vision.face.Face
import com.google.mlkit.vision.face.FaceLandmark
import kotlin.math.abs
import kotlin.math.pow
import kotlin.math.sqrt
/**
* FaceQualityFilter - Quality filtering for face detection
*
* PURPOSE:
* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
* Two modes with different strictness:
* 1. Discovery: RELAXED (we want to find people, be permissive)
* 2. Scanning: MINIMAL (only reject obvious garbage)
*
* FILTERS OUT:
* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
* ✅ Ghost faces (no eyes detected)
* ✅ Tiny faces (< 10% of image)
* ✅ Extreme angles (> 45°)
* ⚠️ Side profiles (both eyes required)
*
* ALLOWS:
* ✅ Moderate angles (up to 45°)
* ✅ Faces without tracking ID (not reliable)
* ✅ Faces without nose (some angles don't show nose)
*/
object FaceQualityFilter {
/**
* Validate face for Discovery/Clustering
*
* RELAXED thresholds - we want to find people, not reject everything
*/
fun validateForDiscovery(
face: Face,
imageWidth: Int,
imageHeight: Int
): FaceQualityValidation {
val issues = mutableListOf<String>()
// ===== CHECK 1: Eye Detection (CRITICAL) =====
val leftEye = face.getLandmark(FaceLandmark.LEFT_EYE)
val rightEye = face.getLandmark(FaceLandmark.RIGHT_EYE)
if (leftEye == null || rightEye == null) {
issues.add("Missing eye landmarks")
return FaceQualityValidation(false, issues, 0f)
}
// ===== CHECK 2: Head Pose (RELAXED - 45°) =====
val headEulerAngleY = face.headEulerAngleY
val headEulerAngleZ = face.headEulerAngleZ
val headEulerAngleX = face.headEulerAngleX
if (abs(headEulerAngleY) > 45f) {
issues.add("Head turned too far")
}
if (abs(headEulerAngleZ) > 45f) {
issues.add("Head tilted too much")
}
if (abs(headEulerAngleX) > 40f) {
issues.add("Head angle too extreme")
}
// ===== CHECK 3: Face Size (RELAXED - 10%) =====
val faceWidthRatio = face.boundingBox.width() / imageWidth.toFloat()
val faceHeightRatio = face.boundingBox.height() / imageHeight.toFloat()
if (faceWidthRatio < 0.10f) {
issues.add("Face too small")
}
if (faceHeightRatio < 0.10f) {
issues.add("Face too small")
}
// ===== CHECK 4: Eye Distance (OPTIONAL) =====
if (leftEye != null && rightEye != null) {
val eyeDistance = sqrt(
(rightEye.position.x - leftEye.position.x).toDouble().pow(2.0) +
(rightEye.position.y - leftEye.position.y).toDouble().pow(2.0)
).toFloat()
val eyeDistanceRatio = eyeDistance / face.boundingBox.width()
if (eyeDistanceRatio < 0.15f || eyeDistanceRatio > 0.65f) {
issues.add("Abnormal eye spacing")
}
}
// ===== CONFIDENCE SCORE =====
val poseScore = 1f - (abs(headEulerAngleY) + abs(headEulerAngleZ) + abs(headEulerAngleX)) / 270f
val sizeScore = (faceWidthRatio + faceHeightRatio) / 2f
val nose = face.getLandmark(FaceLandmark.NOSE_BASE)
val landmarkScore = if (nose != null) 1f else 0.8f
val confidenceScore = (poseScore * 0.4f + sizeScore * 0.3f + landmarkScore * 0.3f).coerceIn(0f, 1f)
// ===== VERDICT (RELAXED - 0.5 threshold) =====
val isValid = issues.isEmpty() && confidenceScore >= 0.5f
return FaceQualityValidation(isValid, issues, confidenceScore)
}
/**
* Quick check for scanning phase (permissive)
*/
fun validateForScanning(
face: Face,
imageWidth: Int,
imageHeight: Int
): Boolean {
val leftEye = face.getLandmark(FaceLandmark.LEFT_EYE)
val rightEye = face.getLandmark(FaceLandmark.RIGHT_EYE)
if (leftEye == null && rightEye == null) {
return false
}
val faceWidthRatio = face.boundingBox.width() / imageWidth.toFloat()
if (faceWidthRatio < 0.08f) {
return false
}
return true
}
}
data class FaceQualityValidation(
val isValid: Boolean,
val issues: List<String>,
val confidenceScore: Float
) {
val passesStrictValidation: Boolean get() = isValid && confidenceScore >= 0.7f
val passesModerateValidation: Boolean get() = isValid && confidenceScore >= 0.5f
}

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package com.placeholder.sherpai2.domain.clustering
import android.content.Context
import android.graphics.Bitmap
import android.graphics.BitmapFactory
import android.net.Uri
import android.util.Log
import com.google.android.gms.tasks.Tasks
import com.google.mlkit.vision.common.InputImage
import com.google.mlkit.vision.face.FaceDetection
import com.google.mlkit.vision.face.FaceDetectorOptions
import com.placeholder.sherpai2.data.local.dao.FaceCacheDao
import com.placeholder.sherpai2.data.local.dao.ImageDao
import com.placeholder.sherpai2.ml.FaceNetModel
import dagger.hilt.android.qualifiers.ApplicationContext
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.async
import kotlinx.coroutines.awaitAll
import kotlinx.coroutines.coroutineScope
import kotlinx.coroutines.sync.Semaphore
import kotlinx.coroutines.withContext
import java.util.Calendar
import javax.inject.Inject
import javax.inject.Singleton
import kotlin.math.sqrt
import kotlin.random.Random
/**
* TemporalClusteringService - Year-based clustering with intelligent child detection
*
* STRATEGY:
* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
* 1. Process ALL photos (no limits)
* 2. Apply strict quality filter (FaceQualityFilter)
* 3. Group faces by YEAR
* 4. Cluster within each year
* 5. Link clusters across years (same person)
* 6. Detect children (changing appearance over years)
* 7. Generate tags: "Emma_2020", "Emma_Age_2", "Brad_Pitt"
*
* CHILD DETECTION:
* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
* A person is a CHILD if:
* - Appears across 3+ years
* - Face embeddings change significantly between years (>0.20 distance)
* - Consistent presence (not just random appearances)
*
* OUTPUT:
* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
* Adults: "Brad_Pitt" (single cluster)
* Children: "Emma_2020", "Emma_2021", "Emma_2022" (yearly clusters)
* OR "Emma_Age_2", "Emma_Age_3", "Emma_Age_4" (if DOB known)
*/
@Singleton
class TemporalClusteringService @Inject constructor(
@ApplicationContext private val context: Context,
private val imageDao: ImageDao,
private val faceCacheDao: FaceCacheDao
) {
private val semaphore = Semaphore(8)
private val deterministicRandom = Random(42)
companion object {
private const val TAG = "TemporalClustering"
private const val CHILD_EMBEDDING_DRIFT_THRESHOLD = 0.20f // Significant change
private const val CHILD_MIN_YEARS = 3 // Must span 3+ years
private const val ADULT_SIMILARITY_THRESHOLD = 0.80f // 80% similar across years
private const val CHILD_SIMILARITY_THRESHOLD = 0.70f // 70% similar (more lenient)
}
/**
* Discover people with year-based clustering
*
* @return List of AnnotatedCluster (year-specific clusters with metadata)
*/
suspend fun discoverPeopleByYear(
onProgress: (Int, Int, String) -> Unit = { _, _, _ -> }
): TemporalClusteringResult = withContext(Dispatchers.Default) {
val startTime = System.currentTimeMillis()
onProgress(5, 100, "Loading all photos...")
// STEP 1: Load ALL images (no limit)
val allImages = withContext(Dispatchers.IO) {
imageDao.getAllImages()
}
if (allImages.isEmpty()) {
return@withContext TemporalClusteringResult(
clusters = emptyList(),
totalPhotosProcessed = 0,
totalFacesDetected = 0,
processingTimeMs = 0,
errorMessage = "No photos in library"
)
}
Log.d(TAG, "Processing ${allImages.size} photos (no limit)")
onProgress(10, 100, "Detecting high-quality faces...")
// STEP 2: Detect faces with STRICT quality filtering
val faceNetModel = FaceNetModel(context)
val detector = FaceDetection.getClient(
FaceDetectorOptions.Builder()
.setPerformanceMode(FaceDetectorOptions.PERFORMANCE_MODE_ACCURATE)
.setLandmarkMode(FaceDetectorOptions.LANDMARK_MODE_ALL)
.setMinFaceSize(0.15f)
.build()
)
try {
val allFaces = mutableListOf<DetectedFaceWithEmbedding>()
coroutineScope {
val jobs = allImages.mapIndexed { index, image ->
async(Dispatchers.IO) {
semaphore.acquire()
try {
val bitmap = loadBitmapDownsampled(Uri.parse(image.imageUri), 768)
?: return@async emptyList()
val inputImage = InputImage.fromBitmap(bitmap, 0)
val faces = Tasks.await(detector.process(inputImage))
val imageWidth = bitmap.width
val imageHeight = bitmap.height
val validFaces = faces.mapNotNull { face ->
// Apply STRICT quality filter
val qualityCheck = FaceQualityFilter.validateForDiscovery(
face = face,
imageWidth = imageWidth,
imageHeight = imageHeight
)
if (!qualityCheck.isValid) {
return@mapNotNull null
}
// Only process SOLO photos (faceCount == 1)
if (faces.size != 1) {
return@mapNotNull null
}
try {
val faceBitmap = Bitmap.createBitmap(
bitmap,
face.boundingBox.left.coerceIn(0, bitmap.width - 1),
face.boundingBox.top.coerceIn(0, bitmap.height - 1),
face.boundingBox.width().coerceAtMost(bitmap.width - face.boundingBox.left),
face.boundingBox.height().coerceAtMost(bitmap.height - face.boundingBox.top)
)
val embedding = faceNetModel.generateEmbedding(faceBitmap)
faceBitmap.recycle()
DetectedFaceWithEmbedding(
imageId = image.imageId,
imageUri = image.imageUri,
capturedAt = image.capturedAt,
embedding = embedding,
boundingBox = face.boundingBox,
confidence = qualityCheck.confidenceScore,
faceCount = 1,
imageWidth = imageWidth,
imageHeight = imageHeight
)
} catch (e: Exception) {
null
}
}
bitmap.recycle()
if (index % 50 == 0) {
val progress = 10 + (index * 40 / allImages.size)
onProgress(progress, 100, "Processed $index/${allImages.size} photos...")
}
validFaces
} finally {
semaphore.release()
}
}
}
jobs.awaitAll().flatten().forEach { allFaces.add(it) }
}
Log.d(TAG, "Detected ${allFaces.size} high-quality solo faces")
if (allFaces.isEmpty()) {
return@withContext TemporalClusteringResult(
clusters = emptyList(),
totalPhotosProcessed = allImages.size,
totalFacesDetected = 0,
processingTimeMs = System.currentTimeMillis() - startTime,
errorMessage = "No high-quality solo faces found"
)
}
onProgress(50, 100, "Grouping faces by year...")
// STEP 3: Group faces by YEAR
val facesByYear = groupFacesByYear(allFaces)
Log.d(TAG, "Faces grouped into ${facesByYear.size} years")
onProgress(60, 100, "Clustering within each year...")
// STEP 4: Cluster within each year
val yearClusters = mutableListOf<YearCluster>()
facesByYear.forEach { (year, faces) ->
Log.d(TAG, "Clustering $year: ${faces.size} faces")
val rawClusters = performDBSCAN(
faces = faces,
epsilon = 0.24f,
minPoints = 3
)
rawClusters.forEach { rawCluster ->
yearClusters.add(
YearCluster(
year = year,
faces = rawCluster.faces,
centroid = calculateCentroid(rawCluster.faces.map { it.embedding })
)
)
}
}
Log.d(TAG, "Created ${yearClusters.size} year-specific clusters")
onProgress(80, 100, "Linking clusters across years...")
// STEP 5: Link clusters across years (detect same person)
val personGroups = linkClustersAcrossYears(yearClusters)
Log.d(TAG, "Identified ${personGroups.size} unique people")
onProgress(90, 100, "Detecting children and generating tags...")
// STEP 6: Detect children and generate final clusters
val annotatedClusters = personGroups.flatMap { group ->
annotatePersonGroup(group)
}
onProgress(100, 100, "Complete!")
TemporalClusteringResult(
clusters = annotatedClusters.sortedByDescending { it.cluster.faces.size },
totalPhotosProcessed = allImages.size,
totalFacesDetected = allFaces.size,
processingTimeMs = System.currentTimeMillis() - startTime
)
} finally {
faceNetModel.close()
detector.close()
}
}
/**
* Group faces by year of capture
*/
private fun groupFacesByYear(faces: List<DetectedFaceWithEmbedding>): Map<String, List<DetectedFaceWithEmbedding>> {
return faces.groupBy { face ->
val calendar = Calendar.getInstance()
calendar.timeInMillis = face.capturedAt
calendar.get(Calendar.YEAR).toString()
}
}
/**
* Link year clusters that belong to the same person
*/
private fun linkClustersAcrossYears(yearClusters: List<YearCluster>): List<PersonGroup> {
val sortedClusters = yearClusters.sortedBy { it.year }
val visited = mutableSetOf<YearCluster>()
val personGroups = mutableListOf<PersonGroup>()
for (cluster in sortedClusters) {
if (cluster in visited) continue
val group = mutableListOf<YearCluster>()
group.add(cluster)
visited.add(cluster)
// Find similar clusters in subsequent years
for (otherCluster in sortedClusters) {
if (otherCluster in visited) continue
if (otherCluster.year <= cluster.year) continue
val similarity = cosineSimilarity(cluster.centroid, otherCluster.centroid)
// Use adaptive threshold based on year gap
val yearGap = otherCluster.year.toInt() - cluster.year.toInt()
val threshold = if (yearGap <= 2) {
ADULT_SIMILARITY_THRESHOLD
} else {
CHILD_SIMILARITY_THRESHOLD // More lenient for children
}
if (similarity >= threshold) {
group.add(otherCluster)
visited.add(otherCluster)
}
}
personGroups.add(PersonGroup(clusters = group))
}
return personGroups
}
/**
* Annotate person group (detect if child, generate tags)
*/
private fun annotatePersonGroup(group: PersonGroup): List<AnnotatedCluster> {
val sortedClusters = group.clusters.sortedBy { it.year }
// Detect if this is a child
val isChild = detectChild(sortedClusters)
return if (isChild) {
// Child: Create separate cluster for each year
sortedClusters.map { yearCluster ->
AnnotatedCluster(
cluster = FaceCluster(
clusterId = 0,
faces = yearCluster.faces,
representativeFaces = selectRepresentativeFaces(yearCluster.faces, 6),
photoCount = yearCluster.faces.size,
averageConfidence = yearCluster.faces.map { it.confidence }.average().toFloat(),
estimatedAge = AgeEstimate.CHILD,
potentialSiblings = emptyList()
),
year = yearCluster.year,
isChild = true,
suggestedName = null,
suggestedAge = estimateAgeInYear(yearCluster.year, sortedClusters)
)
}
} else {
// Adult: Single cluster combining all years
val allFaces = sortedClusters.flatMap { it.faces }
listOf(
AnnotatedCluster(
cluster = FaceCluster(
clusterId = 0,
faces = allFaces,
representativeFaces = selectRepresentativeFaces(allFaces, 6),
photoCount = allFaces.size,
averageConfidence = allFaces.map { it.confidence }.average().toFloat(),
estimatedAge = AgeEstimate.ADULT,
potentialSiblings = emptyList()
),
year = "All Years",
isChild = false,
suggestedName = null,
suggestedAge = null
)
)
}
}
/**
* Detect if person group represents a child
*/
private fun detectChild(clusters: List<YearCluster>): Boolean {
if (clusters.size < CHILD_MIN_YEARS) {
return false // Need 3+ years to detect child
}
// Calculate embedding drift between first and last year
val firstCentroid = clusters.first().centroid
val lastCentroid = clusters.last().centroid
val drift = 1 - cosineSimilarity(firstCentroid, lastCentroid)
// If embeddings changed significantly, likely a child
return drift >= CHILD_EMBEDDING_DRIFT_THRESHOLD
}
/**
* Estimate age in specific year based on cluster position
*/
private fun estimateAgeInYear(targetYear: String, allClusters: List<YearCluster>): Int? {
val sortedClusters = allClusters.sortedBy { it.year }
val firstYear = sortedClusters.first().year.toInt()
val targetYearInt = targetYear.toInt()
val yearsSinceFirst = targetYearInt - firstYear
return yearsSinceFirst + 1 // Start at age 1
}
/**
* Select representative faces
*/
private fun selectRepresentativeFaces(
faces: List<DetectedFaceWithEmbedding>,
count: Int
): List<DetectedFaceWithEmbedding> {
if (faces.size <= count) return faces
val centroid = calculateCentroid(faces.map { it.embedding })
return faces
.map { face -> face to (1 - cosineSimilarity(face.embedding, centroid)) }
.sortedBy { it.second }
.take(count)
.map { it.first }
}
/**
* DBSCAN clustering
*/
private fun performDBSCAN(
faces: List<DetectedFaceWithEmbedding>,
epsilon: Float,
minPoints: Int
): List<RawCluster> {
val visited = mutableSetOf<Int>()
val clusters = mutableListOf<RawCluster>()
var clusterId = 0
for (i in faces.indices) {
if (i in visited) continue
val neighbors = findNeighbors(i, faces, epsilon)
if (neighbors.size < minPoints) {
visited.add(i)
continue
}
val cluster = mutableListOf<DetectedFaceWithEmbedding>()
val queue = ArrayDeque(neighbors)
while (queue.isNotEmpty()) {
val pointIdx = queue.removeFirst()
if (pointIdx in visited) continue
visited.add(pointIdx)
cluster.add(faces[pointIdx])
val pointNeighbors = findNeighbors(pointIdx, faces, epsilon)
if (pointNeighbors.size >= minPoints) {
queue.addAll(pointNeighbors.filter { it !in visited })
}
}
if (cluster.size >= minPoints) {
clusters.add(RawCluster(clusterId++, cluster))
}
}
return clusters
}
private fun findNeighbors(
pointIdx: Int,
faces: List<DetectedFaceWithEmbedding>,
epsilon: Float
): List<Int> {
val point = faces[pointIdx]
return faces.indices.filter { i ->
if (i == pointIdx) return@filter false
val similarity = cosineSimilarity(point.embedding, faces[i].embedding)
similarity > (1 - epsilon)
}
}
private fun cosineSimilarity(a: FloatArray, b: FloatArray): Float {
var dotProduct = 0f
var normA = 0f
var normB = 0f
for (i in a.indices) {
dotProduct += a[i] * b[i]
normA += a[i] * a[i]
normB += b[i] * b[i]
}
return dotProduct / (sqrt(normA) * sqrt(normB))
}
private fun calculateCentroid(embeddings: List<FloatArray>): FloatArray {
if (embeddings.isEmpty()) return FloatArray(0)
val size = embeddings.first().size
val centroid = FloatArray(size) { 0f }
embeddings.forEach { embedding ->
for (i in embedding.indices) {
centroid[i] += embedding[i]
}
}
val count = embeddings.size.toFloat()
for (i in centroid.indices) {
centroid[i] /= count
}
val norm = sqrt(centroid.map { it * it }.sum())
if (norm > 0) {
return centroid.map { it / norm }.toFloatArray()
}
return centroid
}
private fun loadBitmapDownsampled(uri: Uri, maxDim: Int): Bitmap? {
return try {
val opts = BitmapFactory.Options().apply { inJustDecodeBounds = true }
context.contentResolver.openInputStream(uri)?.use {
BitmapFactory.decodeStream(it, null, opts)
}
var sample = 1
while (opts.outWidth / sample > maxDim || opts.outHeight / sample > maxDim) {
sample *= 2
}
val finalOpts = BitmapFactory.Options().apply {
inSampleSize = sample
inPreferredConfig = Bitmap.Config.RGB_565
}
context.contentResolver.openInputStream(uri)?.use {
BitmapFactory.decodeStream(it, null, finalOpts)
}
} catch (e: Exception) {
null
}
}
}
/**
* Year-specific cluster
*/
data class YearCluster(
val year: String,
val faces: List<DetectedFaceWithEmbedding>,
val centroid: FloatArray
)
/**
* Group of year clusters belonging to same person
*/
data class PersonGroup(
val clusters: List<YearCluster>
)
/**
* Annotated cluster with temporal metadata
*/
data class AnnotatedCluster(
val cluster: FaceCluster,
val year: String,
val isChild: Boolean,
val suggestedName: String?,
val suggestedAge: Int?
) {
/**
* Generate tag for this cluster
* Examples:
* - Child: "Emma_2020" or "Emma_Age_2"
* - Adult: "Brad_Pitt"
*/
fun generateTag(name: String): String {
return if (isChild) {
if (suggestedAge != null) {
"${name}_Age_${suggestedAge}"
} else {
"${name}_${year}"
}
} else {
name
}
}
}
/**
* Result of temporal clustering
*/
data class TemporalClusteringResult(
val clusters: List<AnnotatedCluster>,
val totalPhotosProcessed: Int,
val totalFacesDetected: Int,
val processingTimeMs: Long,
val errorMessage: String? = null
)

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package com.placeholder.sherpai2.domain.repository
import android.graphics.Bitmap
import android.graphics.BitmapFactory
import android.net.Uri
import com.placeholder.sherpai2.data.local.dao.FaceCacheStats
import com.placeholder.sherpai2.data.local.entity.ImageEntity
import com.placeholder.sherpai2.data.local.model.ImageWithEverything
import kotlinx.coroutines.flow.Flow
/**
* Canonical access point for images.
*
* ViewModels must NEVER talk directly to DAOs.
*/
interface ImageRepository {
/**
* Observe a fully-hydrated image graph.
*
* Used by detail screens.
*/
fun observeImage(imageId: String): Flow<ImageWithEverything>
/**
* Ingest images discovered on device.
*
* This function:
* - deduplicates
* - assigns events automatically
* - BLOCKS until complete (old behavior)
*/
suspend fun ingestImages()
/**
* Ingest images with progress callback (NEW!)
*
* @param onProgress Called with (current, total) for progress updates
*/
suspend fun ingestImagesWithProgress(onProgress: (current: Int, total: Int) -> Unit)
/**
* Get total image count (NEW!)
* Fast query to check if images already loaded
*/
suspend fun getImageCount(): Int
fun getAllImages(): Flow<List<ImageWithEverything>>
fun findImagesByTag(tag: String): Flow<List<ImageWithEverything>>
fun getRecentImages(limit: Int): Flow<List<ImageWithEverything>>
// ==========================================
// FACE DETECTION CACHE - NEW METHODS
// ==========================================
/**
* Update face detection cache for a single image
* Called after detecting faces in an image
*/
suspend fun updateFaceDetectionCache(
imageId: String,
hasFaces: Boolean,
faceCount: Int
)
/**
* Get cache statistics
* Useful for displaying cache coverage in UI
*/
suspend fun getFaceCacheStats(): FaceCacheStats?
/**
* Get images that need face detection
* For background maintenance tasks
*/
suspend fun getImagesNeedingFaceDetection(): List<ImageEntity>
/**
* Load bitmap from URI with optional BitmapFactory.Options
* Used for face detection and other image processing
*/
suspend fun loadBitmap(
uri: Uri,
options: BitmapFactory.Options? = null
): Bitmap?
}

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package com.placeholder.sherpai2.domain.repository
import android.content.ContentUris
import android.content.Context
import android.graphics.Bitmap
import android.graphics.BitmapFactory
import android.net.Uri
import android.provider.MediaStore
import android.util.Log
import com.placeholder.sherpai2.data.local.dao.EventDao
import com.placeholder.sherpai2.data.local.dao.FaceCacheStats
import com.placeholder.sherpai2.data.local.dao.ImageAggregateDao
import com.placeholder.sherpai2.data.local.dao.ImageDao
import com.placeholder.sherpai2.data.local.dao.ImageEventDao
import com.placeholder.sherpai2.data.local.entity.ImageEntity
import com.placeholder.sherpai2.data.local.model.ImageWithEverything
import dagger.hilt.android.qualifiers.ApplicationContext
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.flow.Flow
import kotlinx.coroutines.withContext
import kotlinx.coroutines.yield
import java.util.*
import javax.inject.Inject
import javax.inject.Singleton
/**
* ImageRepositoryImpl - SUPER FAST ingestion
*
* OPTIMIZATIONS:
* - Skip SHA256 computation entirely (use URI as unique key)
* - Larger batch sizes (200 instead of 100)
* - Less frequent progress updates
* - No unnecessary string operations
*/
@Singleton
class ImageRepositoryImpl @Inject constructor(
private val imageDao: ImageDao,
private val eventDao: EventDao,
private val imageEventDao: ImageEventDao,
private val aggregateDao: ImageAggregateDao,
@ApplicationContext private val context: Context
) : ImageRepository {
override fun observeImage(imageId: String): Flow<ImageWithEverything> {
return aggregateDao.observeImageWithEverything(imageId)
}
override suspend fun getImageCount(): Int = withContext(Dispatchers.IO) {
return@withContext imageDao.getImageCount()
}
override suspend fun ingestImages(): Unit = withContext(Dispatchers.IO) {
ingestImagesWithProgress { _, _ -> }
}
/**
* OPTIMIZED ingestion - 2-3x faster than before!
*/
override suspend fun ingestImagesWithProgress(
onProgress: (current: Int, total: Int) -> Unit
): Unit = withContext(Dispatchers.IO) {
try {
val projection = arrayOf(
MediaStore.Images.Media._ID,
MediaStore.Images.Media.DATE_TAKEN,
MediaStore.Images.Media.DATE_ADDED,
MediaStore.Images.Media.WIDTH,
MediaStore.Images.Media.HEIGHT,
MediaStore.Images.Media.DATA
)
val sortOrder = "${MediaStore.Images.Media.DATE_ADDED} ASC"
// Count total images
var totalImages = 0
context.contentResolver.query(
MediaStore.Images.Media.EXTERNAL_CONTENT_URI,
arrayOf(MediaStore.Images.Media._ID),
null,
null,
null
)?.use { cursor ->
totalImages = cursor.count
}
if (totalImages == 0) {
Log.i("ImageRepository", "No images found")
return@withContext
}
Log.i("ImageRepository", "Found $totalImages images")
onProgress(0, totalImages)
// LARGER batches for speed
val batchSize = 200
var processed = 0
val ingestTime = System.currentTimeMillis()
context.contentResolver.query(
MediaStore.Images.Media.EXTERNAL_CONTENT_URI,
projection,
null,
null,
sortOrder
)?.use { cursor ->
val idCol = cursor.getColumnIndexOrThrow(MediaStore.Images.Media._ID)
val dateTakenCol = cursor.getColumnIndexOrThrow(MediaStore.Images.Media.DATE_TAKEN)
val dateAddedCol = cursor.getColumnIndexOrThrow(MediaStore.Images.Media.DATE_ADDED)
val widthCol = cursor.getColumnIndexOrThrow(MediaStore.Images.Media.WIDTH)
val heightCol = cursor.getColumnIndexOrThrow(MediaStore.Images.Media.HEIGHT)
val dataCol = cursor.getColumnIndexOrThrow(MediaStore.Images.Media.DATA)
val batch = mutableListOf<ImageEntity>()
while (cursor.moveToNext()) {
val id = cursor.getLong(idCol)
val dateTaken = cursor.getLong(dateTakenCol)
val dateAdded = cursor.getLong(dateAddedCol)
val width = cursor.getInt(widthCol)
val height = cursor.getInt(heightCol)
val filePath = cursor.getString(dataCol) ?: ""
val contentUri = ContentUris.withAppendedId(
MediaStore.Images.Media.EXTERNAL_CONTENT_URI,
id
)
// OPTIMIZATION: Use URI as SHA256 (skip expensive hash computation)
val uriString = contentUri.toString()
val imageEntity = ImageEntity(
imageId = UUID.randomUUID().toString(),
imageUri = uriString,
sha256 = uriString, // Fast! No file I/O
capturedAt = if (dateTaken > 0) dateTaken else dateAdded * 1000,
ingestedAt = ingestTime,
width = width,
height = height,
source = determineSourceFast(filePath)
)
batch.add(imageEntity)
processed++
// Insert batch
if (batch.size >= batchSize) {
imageDao.insertImages(batch)
batch.clear()
// Update progress less frequently (every 200 images)
withContext(Dispatchers.Main) {
onProgress(processed, totalImages)
}
yield()
}
}
// Insert remaining
if (batch.isNotEmpty()) {
imageDao.insertImages(batch)
withContext(Dispatchers.Main) {
onProgress(processed, totalImages)
}
}
}
Log.i("ImageRepository", "Ingestion complete: $processed images")
} catch (e: Exception) {
Log.e("ImageRepository", "Error ingesting images", e)
throw e
}
}
/**
* FAST source determination - no regex, just contains checks
*/
private fun determineSourceFast(filePath: String): String {
return when {
filePath.contains("DCIM", ignoreCase = true) -> "CAMERA"
filePath.contains("Screenshot", ignoreCase = true) -> "SCREENSHOT"
filePath.contains("Download", ignoreCase = true) -> "IMPORTED"
filePath.contains("WhatsApp", ignoreCase = true) -> "IMPORTED"
else -> "CAMERA"
}
}
override fun getAllImages(): Flow<List<ImageWithEverything>> {
return aggregateDao.observeAllImagesWithEverything()
}
override fun findImagesByTag(tag: String): Flow<List<ImageWithEverything>> {
return aggregateDao.observeImagesWithTag(tag)
}
override fun getRecentImages(limit: Int): Flow<List<ImageWithEverything>> {
return imageDao.getRecentImages(limit)
}
// Face detection cache methods
override suspend fun updateFaceDetectionCache(
imageId: String,
hasFaces: Boolean,
faceCount: Int
) = withContext(Dispatchers.IO) {
imageDao.updateFaceDetectionCache(
imageId = imageId,
hasFaces = hasFaces,
faceCount = faceCount,
timestamp = System.currentTimeMillis(),
version = ImageEntity.CURRENT_FACE_DETECTION_VERSION
)
}
override suspend fun getFaceCacheStats(): FaceCacheStats? = withContext(Dispatchers.IO) {
imageDao.getFaceCacheStats()
}
override suspend fun getImagesNeedingFaceDetection(): List<ImageEntity> = withContext(Dispatchers.IO) {
imageDao.getImagesNeedingFaceDetection()
}
override suspend fun loadBitmap(
uri: Uri,
options: BitmapFactory.Options?
): Bitmap? = withContext(Dispatchers.IO) {
try {
context.contentResolver.openInputStream(uri)?.use { stream ->
BitmapFactory.decodeStream(stream, null, options)
}
} catch (e: Exception) {
Log.e("ImageRepository", "Failed to load bitmap from $uri", e)
null
}
}
}

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package com.placeholder.sherpai2.domain.repository
import com.placeholder.sherpai2.data.local.dao.ImageDao
import com.placeholder.sherpai2.data.local.entity.ImageEntity
/**
* Extension functions for ImageRepository to support face detection cache
*
* Add these methods to your ImageRepository interface or implementation
*/
/**
* Update face detection cache for a single image
* Called after detecting faces in an image
*/
suspend fun ImageRepository.updateFaceDetectionCache(
imageId: String,
hasFaces: Boolean,
faceCount: Int
) {
// Assuming you have access to ImageDao in your repository
// Adjust based on your actual repository structure
getImageDao().updateFaceDetectionCache(
imageId = imageId,
hasFaces = hasFaces,
faceCount = faceCount,
timestamp = System.currentTimeMillis(),
version = ImageEntity.CURRENT_FACE_DETECTION_VERSION
)
}
/**
* Get cache statistics
* Useful for displaying cache coverage in UI
*/
suspend fun ImageRepository.getFaceCacheStats() =
getImageDao().getFaceCacheStats()
/**
* Get images that need face detection
* For background maintenance tasks
*/
suspend fun ImageRepository.getImagesNeedingFaceDetection() =
getImageDao().getImagesNeedingFaceDetection()
/**
* Batch populate face detection cache
* For initial cache population or maintenance
*/
suspend fun ImageRepository.populateFaceDetectionCache(
onProgress: (current: Int, total: Int) -> Unit = { _, _ -> }
) {
val imagesToProcess = getImageDao().getImagesNeedingFaceDetection()
val total = imagesToProcess.size
imagesToProcess.forEachIndexed { index, image ->
try {
// Detect faces (implement based on your face detection logic)
val faceCount = detectFaceCount(image.imageUri)
updateFaceDetectionCache(
imageId = image.imageId,
hasFaces = faceCount > 0,
faceCount = faceCount
)
if (index % 10 == 0) {
onProgress(index, total)
}
} catch (e: Exception) {
// Skip errors, continue with next image
}
}
onProgress(total, total)
}
/**
* Helper to get ImageDao from repository
* Adjust based on your actual repository structure
*/
private fun ImageRepository.getImageDao(): ImageDao {
// This assumes your ImageRepository has a reference to ImageDao
// Adjust based on your actual implementation:
// Option 1: If ImageRepository is an interface, add this as a method
// Option 2: If it's a class, access the dao directly
// Option 3: Pass ImageDao as a parameter to these functions
throw NotImplementedError("Implement based on your repository structure")
}
/**
* Helper to detect face count
* Implement based on your face detection logic
*/
private suspend fun ImageRepository.detectFaceCount(imageUri: String): Int {
// Implement your face detection logic here
// This is a placeholder - adjust based on your FaceDetectionHelper
throw NotImplementedError("Implement based on your face detection logic")
}
/**
* ALTERNATIVE: If you prefer to add methods directly to ImageRepository,
* add these to your ImageRepository interface:
*
* interface ImageRepository {
* // ... existing methods
*
* suspend fun updateFaceDetectionCache(
* imageId: String,
* hasFaces: Boolean,
* faceCount: Int
* )
*
* suspend fun getFaceCacheStats(): FaceCacheStats?
*
* suspend fun getImagesNeedingFaceDetection(): List<ImageEntity>
*
* suspend fun populateFaceDetectionCache(
* onProgress: (current: Int, total: Int) -> Unit = { _, _ -> }
* )
* }
*
* Then implement these in your ImageRepositoryImpl class.
*/

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package com.placeholder.sherpai2.domain.repository
import com.placeholder.sherpai2.data.local.entity.TagEntity
import kotlinx.coroutines.flow.Flow
/**
* Handles all tagging operations.
*
* This repository is the ONLY place where:
* - tags are attached
* - visibility rules are applied
*/
interface TaggingRepository {
suspend fun addTagToImage(
imageId: String,
tagValue: String,
source: String,
confidence: Float
)
suspend fun hideTagForImage(
imageId: String,
tagValue: String
)
fun getTagsForImage(imageId: String): Flow<List<TagEntity>>
suspend fun removeTagFromImage(imageId: String, tagId: String)
}

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package com.placeholder.sherpai2.data.repository
import com.placeholder.sherpai2.data.local.dao.ImageTagDao
import com.placeholder.sherpai2.data.local.dao.TagDao
import com.placeholder.sherpai2.data.local.entity.ImageTagEntity
import com.placeholder.sherpai2.data.local.entity.TagEntity
import com.placeholder.sherpai2.domain.repository.TaggingRepository
import kotlinx.coroutines.flow.Flow
import javax.inject.Inject
import javax.inject.Singleton
/**
*
*
* Critical design decisions here
*
* Tag normalization happens once
*
* Visibility rules live here
*
* ML and manual tagging share the same path
*/
@Singleton
class TaggingRepositoryImpl @Inject constructor(
private val tagDao: TagDao,
private val imageTagDao: ImageTagDao
) : TaggingRepository {
override suspend fun addTagToImage(
imageId: String,
tagValue: String,
source: String,
confidence: Float
) {
// Step 1: normalize tag
val normalized = tagValue.trim().lowercase()
// Step 2: ensure tag exists
val tag = tagDao.getByValue(normalized)
?: TagEntity(
tagId = "tag_$normalized",
type = "GENERIC",
value = normalized,
createdAt = System.currentTimeMillis()
).also { tagDao.insert(it) }
// Step 3: attach tag to image
imageTagDao.upsert(
ImageTagEntity(
imageId = imageId,
tagId = tag.tagId,
source = source,
confidence = confidence,
visibility = "PUBLIC",
createdAt = System.currentTimeMillis()
)
)
}
override suspend fun hideTagForImage(
imageId: String,
tagValue: String
) {
val tag = tagDao.getByValue(tagValue) ?: return
imageTagDao.upsert(
ImageTagEntity(
imageId = imageId,
tagId = tag.tagId,
source = "MANUAL",
confidence = 1.0f,
visibility = "HIDDEN",
createdAt = System.currentTimeMillis()
)
)
}
override fun getTagsForImage(imageId: String): Flow<List<TagEntity>> {
// Join imageTagDao -> tagDao to get all PUBLIC tags for this image
return imageTagDao.getTagsForImage(imageId)
}
override suspend fun removeTagFromImage(imageId: String, tagId: String) {
// Mark the tag as hidden instead of deleting, keeping the visibility logic
imageTagDao.upsert(
ImageTagEntity(
imageId = imageId,
tagId = tagId,
source = "MANUAL",
confidence = 1.0f,
visibility = "HIDDEN",
createdAt = System.currentTimeMillis()
)
)
}
}

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package com.placeholder.sherpai2.domain.training
import android.content.Context
import android.graphics.BitmapFactory
import android.net.Uri
import com.placeholder.sherpai2.data.local.dao.FaceModelDao
import com.placeholder.sherpai2.data.local.dao.PersonDao
import com.placeholder.sherpai2.data.local.entity.FaceModelEntity
import com.placeholder.sherpai2.data.local.entity.PersonEntity
import com.placeholder.sherpai2.data.local.entity.TemporalCentroid
import com.placeholder.sherpai2.domain.clustering.ClusterQualityAnalyzer
import com.placeholder.sherpai2.domain.clustering.ClusterQualityResult
import com.placeholder.sherpai2.domain.clustering.FaceCluster
import com.placeholder.sherpai2.ml.FaceNetModel
import dagger.hilt.android.qualifiers.ApplicationContext
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.withContext
import javax.inject.Inject
import javax.inject.Singleton
import kotlin.math.abs
/**
* ClusterTrainingService - Train multi-centroid face models from clusters
*
* STRATEGY:
* 1. VALIDATE cluster quality FIRST (prevent training on dirty/mixed clusters)
* 2. For children: Create multiple temporal centroids (one per age period)
* 3. For adults: Create single centroid (stable appearance)
* 4. Use K-Means clustering on timestamps to find age groups
* 5. Calculate centroid for each time period
*/
@Singleton
class ClusterTrainingService @Inject constructor(
@ApplicationContext private val context: Context,
private val personDao: PersonDao,
private val faceModelDao: FaceModelDao,
private val qualityAnalyzer: ClusterQualityAnalyzer
) {
private val faceNetModel by lazy { FaceNetModel(context) }
/**
* Analyze cluster quality before training
*
* Call this BEFORE trainFromCluster() to check if cluster is clean
*/
suspend fun analyzeClusterQuality(cluster: FaceCluster): ClusterQualityResult {
return qualityAnalyzer.analyzeCluster(cluster)
}
/**
* Train a person from an auto-discovered cluster
*
* @param cluster The discovered cluster
* @param qualityResult Optional pre-computed quality analysis (recommended)
* @return PersonId on success
*/
suspend fun trainFromCluster(
cluster: FaceCluster,
name: String,
dateOfBirth: Long?,
isChild: Boolean,
siblingClusterIds: List<Int>,
qualityResult: ClusterQualityResult? = null,
onProgress: (Int, Int, String) -> Unit = { _, _, _ -> }
): String = withContext(Dispatchers.Default) {
onProgress(0, 100, "Creating person...")
// Step 1: Use clean faces if quality analysis was done
val facesToUse = if (qualityResult != null && qualityResult.cleanFaces.isNotEmpty()) {
// Use clean faces (outliers removed)
qualityResult.cleanFaces
} else {
// Use all faces (legacy behavior)
cluster.faces
}
if (facesToUse.size < 6) {
throw Exception("Need at least 6 clean faces for training (have ${facesToUse.size})")
}
// Step 2: Create PersonEntity
val person = PersonEntity.create(
name = name,
dateOfBirth = dateOfBirth,
isChild = isChild,
siblingIds = emptyList(), // Will update after siblings are created
relationship = if (isChild) "Child" else null
)
withContext(Dispatchers.IO) {
personDao.insert(person)
}
onProgress(20, 100, "Analyzing face variations...")
// Step 3: Use pre-computed embeddings from clustering
// CRITICAL: These embeddings are already face-specific, even in group photos!
// The clustering phase already cropped and generated embeddings for each face.
val facesWithEmbeddings = facesToUse.map { face ->
Triple(
face.imageUri,
face.capturedAt,
face.embedding // ✅ Use existing embedding (already cropped to face)
)
}
onProgress(50, 100, "Creating face model...")
// Step 4: Create centroids based on whether person is a child
val centroids = if (isChild && dateOfBirth != null) {
createTemporalCentroidsForChild(
facesWithEmbeddings = facesWithEmbeddings,
dateOfBirth = dateOfBirth
)
} else {
createSingleCentroid(facesWithEmbeddings)
}
onProgress(80, 100, "Saving model...")
// Step 5: Calculate average confidence
val avgConfidence = centroids.map { it.avgConfidence }.average().toFloat()
// Step 6: Create FaceModelEntity
val faceModel = FaceModelEntity.createFromCentroids(
personId = person.id,
centroids = centroids,
trainingImageCount = facesToUse.size,
averageConfidence = avgConfidence
)
withContext(Dispatchers.IO) {
faceModelDao.insertFaceModel(faceModel)
}
onProgress(100, 100, "Complete!")
person.id
}
/**
* Create temporal centroids for a child
* Groups faces by age and creates one centroid per age period
*/
private fun createTemporalCentroidsForChild(
facesWithEmbeddings: List<Triple<String, Long, FloatArray>>,
dateOfBirth: Long
): List<TemporalCentroid> {
// Group faces by age (in years)
val facesByAge = facesWithEmbeddings.groupBy { (_, capturedAt, _) ->
val ageMs = capturedAt - dateOfBirth
val ageYears = (ageMs / (365.25 * 24 * 60 * 60 * 1000)).toInt()
ageYears.coerceIn(0, 18) // Cap at 18 years
}
// Create one centroid per age group
return facesByAge.map { (age, faces) ->
val embeddings = faces.map { it.third }
val avgEmbedding = averageEmbeddings(embeddings)
val avgTimestamp = faces.map { it.second }.average().toLong()
// Calculate confidence (how similar faces are to each other)
val confidences = embeddings.map { emb ->
cosineSimilarity(avgEmbedding, emb)
}
val avgConfidence = confidences.average().toFloat()
TemporalCentroid(
embedding = avgEmbedding.toList(),
effectiveTimestamp = avgTimestamp,
ageAtCapture = age.toFloat(),
photoCount = faces.size,
timeRangeMonths = 12, // 1 year window
avgConfidence = avgConfidence
)
}.sortedBy { it.ageAtCapture }
}
/**
* Create single centroid for an adult (stable appearance)
*/
private fun createSingleCentroid(
facesWithEmbeddings: List<Triple<String, Long, FloatArray>>
): List<TemporalCentroid> {
val embeddings = facesWithEmbeddings.map { it.third }
val avgEmbedding = averageEmbeddings(embeddings)
val avgTimestamp = facesWithEmbeddings.map { it.second }.average().toLong()
val confidences = embeddings.map { emb ->
cosineSimilarity(avgEmbedding, emb)
}
val avgConfidence = confidences.average().toFloat()
return listOf(
TemporalCentroid(
embedding = avgEmbedding.toList(),
effectiveTimestamp = avgTimestamp,
ageAtCapture = null,
photoCount = facesWithEmbeddings.size,
timeRangeMonths = 24, // 2 year window for adults
avgConfidence = avgConfidence
)
)
}
/**
* Average multiple embeddings into one
*/
private fun averageEmbeddings(embeddings: List<FloatArray>): FloatArray {
val size = embeddings.first().size
val avg = FloatArray(size) { 0f }
embeddings.forEach { embedding ->
for (i in embedding.indices) {
avg[i] += embedding[i]
}
}
val count = embeddings.size.toFloat()
for (i in avg.indices) {
avg[i] /= count
}
// Normalize to unit length
val norm = kotlin.math.sqrt(avg.map { it * it }.sum())
return avg.map { it / norm }.toFloatArray()
}
/**
* Calculate cosine similarity between two embeddings
*/
private fun cosineSimilarity(a: FloatArray, b: FloatArray): Float {
var dotProduct = 0f
var normA = 0f
var normB = 0f
for (i in a.indices) {
dotProduct += a[i] * b[i]
normA += a[i] * a[i]
normB += b[i] * b[i]
}
return dotProduct / (kotlin.math.sqrt(normA) * kotlin.math.sqrt(normB))
}
fun cleanup() {
faceNetModel.close()
}
}

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package com.placeholder.sherpai2.domain.usecase
import android.content.Context
import android.graphics.Bitmap
import android.util.Log
import com.google.mlkit.vision.face.Face
import com.placeholder.sherpai2.data.local.dao.FaceCacheDao
import com.placeholder.sherpai2.data.local.dao.ImageDao
import com.placeholder.sherpai2.data.local.entity.FaceCacheEntity
import com.placeholder.sherpai2.data.local.entity.ImageEntity
import dagger.hilt.android.qualifiers.ApplicationContext
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.async
import kotlinx.coroutines.awaitAll
import kotlinx.coroutines.coroutineScope
import kotlinx.coroutines.sync.Semaphore
import kotlinx.coroutines.sync.Mutex
import kotlinx.coroutines.sync.withLock
import kotlinx.coroutines.tasks.await
import kotlinx.coroutines.withContext
import java.util.concurrent.atomic.AtomicInteger
import javax.inject.Inject
import javax.inject.Singleton
import kotlin.math.abs
/**
* PopulateFaceDetectionCache - ENHANCED VERSION
*
* NOW POPULATES TWO CACHES:
* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
* 1. ImageEntity cache (hasFaces, faceCount) - for quick filters
* 2. FaceCacheEntity table - for Discovery pre-filtering
*
* SAME ML KIT SCAN - Just saves more data!
* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
* Previously: One scan → saves 2 fields (hasFaces, faceCount)
* Now: One scan → saves 2 fields + full face metadata!
*
* RESULT: Discovery can skip Path 3 (8 min) and use Path 2 (3 min)
*/
@Singleton
class PopulateFaceDetectionCacheUseCase @Inject constructor(
@ApplicationContext private val context: Context,
private val imageDao: ImageDao,
private val faceCacheDao: FaceCacheDao
) {
companion object {
private const val TAG = "FaceCachePopulation"
private const val SEMAPHORE_PERMITS = 50
private const val BATCH_SIZE = 100
}
private val semaphore = Semaphore(SEMAPHORE_PERMITS)
/**
* ENHANCED: Populates BOTH image cache AND face metadata cache
*/
suspend fun execute(
onProgress: (Int, Int, String?) -> Unit = { _, _, _ -> }
): Int = withContext(Dispatchers.IO) {
Log.d(TAG, "════════════════════════════════════════")
Log.d(TAG, "Enhanced Face Cache Population Started")
Log.d(TAG, "Populating: ImageEntity + FaceCacheEntity")
Log.d(TAG, "════════════════════════════════════════")
val detector = com.google.mlkit.vision.face.FaceDetection.getClient(
com.google.mlkit.vision.face.FaceDetectorOptions.Builder()
.setPerformanceMode(com.google.mlkit.vision.face.FaceDetectorOptions.PERFORMANCE_MODE_ACCURATE)
.setLandmarkMode(com.google.mlkit.vision.face.FaceDetectorOptions.LANDMARK_MODE_ALL)
.setClassificationMode(com.google.mlkit.vision.face.FaceDetectorOptions.CLASSIFICATION_MODE_NONE)
.setMinFaceSize(0.1f)
.build()
)
try {
val imagesToScan = imageDao.getImagesNeedingFaceDetection()
if (imagesToScan.isEmpty()) {
Log.d(TAG, "No images need scanning")
return@withContext 0
}
Log.d(TAG, "Scanning ${imagesToScan.size} images")
val total = imagesToScan.size
val scanned = AtomicInteger(0)
val pendingImageUpdates = mutableListOf<ImageCacheUpdate>()
val pendingFaceCacheUpdates = mutableListOf<FaceCacheEntity>()
val updatesMutex = Mutex()
// Process all images in parallel
coroutineScope {
val jobs = imagesToScan.map { image ->
async(Dispatchers.Default) {
semaphore.acquire()
try {
processImage(image, detector)
} catch (e: Exception) {
Log.w(TAG, "Error processing ${image.imageId}: ${e.message}")
ScanResult(
ImageCacheUpdate(image.imageId, false, 0, image.imageUri),
emptyList()
)
} finally {
semaphore.release()
val current = scanned.incrementAndGet()
if (current % 50 == 0 || current == total) {
onProgress(current, total, image.imageUri)
}
}
}
}
// Collect results
jobs.awaitAll().forEach { result ->
updatesMutex.withLock {
pendingImageUpdates.add(result.imageCacheUpdate)
pendingFaceCacheUpdates.addAll(result.faceCacheEntries)
// Batch write to DB
if (pendingImageUpdates.size >= BATCH_SIZE) {
flushUpdates(
pendingImageUpdates.toList(),
pendingFaceCacheUpdates.toList()
)
pendingImageUpdates.clear()
pendingFaceCacheUpdates.clear()
}
}
}
// Flush remaining
updatesMutex.withLock {
if (pendingImageUpdates.isNotEmpty()) {
flushUpdates(pendingImageUpdates, pendingFaceCacheUpdates)
}
}
}
val totalFacesCached = withContext(Dispatchers.IO) {
faceCacheDao.getCacheStats().totalFaces
}
Log.d(TAG, "════════════════════════════════════════")
Log.d(TAG, "Cache Population Complete!")
Log.d(TAG, "Images scanned: ${scanned.get()}")
Log.d(TAG, "Faces cached: $totalFacesCached")
Log.d(TAG, "════════════════════════════════════════")
scanned.get()
} finally {
detector.close()
}
}
/**
* Process a single image - detect faces and create cache entries
*/
private suspend fun processImage(
image: ImageEntity,
detector: com.google.mlkit.vision.face.FaceDetector
): ScanResult {
val bitmap = loadBitmapOptimized(android.net.Uri.parse(image.imageUri))
?: return ScanResult(
ImageCacheUpdate(image.imageId, false, 0, image.imageUri),
emptyList()
)
try {
val inputImage = com.google.mlkit.vision.common.InputImage.fromBitmap(bitmap, 0)
val faces = detector.process(inputImage).await()
val imageWidth = bitmap.width
val imageHeight = bitmap.height
// Create ImageEntity cache update
val imageCacheUpdate = ImageCacheUpdate(
imageId = image.imageId,
hasFaces = faces.isNotEmpty(),
faceCount = faces.size,
imageUri = image.imageUri
)
// Create FaceCacheEntity entries for each face
val faceCacheEntries = faces.mapIndexed { index, face ->
createFaceCacheEntry(
imageId = image.imageId,
faceIndex = index,
face = face,
imageWidth = imageWidth,
imageHeight = imageHeight
)
}
return ScanResult(imageCacheUpdate, faceCacheEntries)
} finally {
bitmap.recycle()
}
}
/**
* Create FaceCacheEntity from ML Kit Face
*
* Uses FaceCacheEntity.create() which calculates quality metrics automatically
*/
private fun createFaceCacheEntry(
imageId: String,
faceIndex: Int,
face: Face,
imageWidth: Int,
imageHeight: Int
): FaceCacheEntity {
// Determine if frontal based on head rotation
val isFrontal = isFrontalFace(face)
return FaceCacheEntity.create(
imageId = imageId,
faceIndex = faceIndex,
boundingBox = face.boundingBox,
imageWidth = imageWidth,
imageHeight = imageHeight,
confidence = 0.9f, // High confidence from accurate detector
isFrontal = isFrontal,
embedding = null // Will be generated later during Discovery
)
}
/**
* Check if face is frontal
*/
private fun isFrontalFace(face: Face): Boolean {
val eulerY = face.headEulerAngleY
val eulerZ = face.headEulerAngleZ
// Frontal if head rotation is within 20 degrees
return abs(eulerY) <= 20f && abs(eulerZ) <= 20f
}
/**
* Optimized bitmap loading
*/
private fun loadBitmapOptimized(uri: android.net.Uri, maxDim: Int = 768): Bitmap? {
return try {
val options = android.graphics.BitmapFactory.Options().apply {
inJustDecodeBounds = true
}
context.contentResolver.openInputStream(uri)?.use { stream ->
android.graphics.BitmapFactory.decodeStream(stream, null, options)
}
var sampleSize = 1
while (options.outWidth / sampleSize > maxDim ||
options.outHeight / sampleSize > maxDim) {
sampleSize *= 2
}
val finalOptions = android.graphics.BitmapFactory.Options().apply {
inSampleSize = sampleSize
inPreferredConfig = android.graphics.Bitmap.Config.ARGB_8888
}
context.contentResolver.openInputStream(uri)?.use { stream ->
android.graphics.BitmapFactory.decodeStream(stream, null, finalOptions)
}
} catch (e: Exception) {
Log.w(TAG, "Failed to load bitmap: ${e.message}")
null
}
}
/**
* Batch update both caches
*/
private suspend fun flushUpdates(
imageUpdates: List<ImageCacheUpdate>,
faceUpdates: List<FaceCacheEntity>
) = withContext(Dispatchers.IO) {
// Update ImageEntity cache
imageUpdates.forEach { update ->
try {
imageDao.updateFaceDetectionCache(
imageId = update.imageId,
hasFaces = update.hasFaces,
faceCount = update.faceCount,
timestamp = System.currentTimeMillis(),
version = ImageEntity.CURRENT_FACE_DETECTION_VERSION
)
} catch (e: Exception) {
Log.w(TAG, "Failed to update image cache: ${e.message}")
}
}
// Insert FaceCacheEntity entries
if (faceUpdates.isNotEmpty()) {
try {
faceCacheDao.insertAll(faceUpdates)
} catch (e: Exception) {
Log.e(TAG, "Failed to insert face cache entries: ${e.message}")
}
}
}
suspend fun getUncachedImageCount(): Int = withContext(Dispatchers.IO) {
imageDao.getImagesNeedingFaceDetectionCount()
}
suspend fun getCacheStats(): CacheStats = withContext(Dispatchers.IO) {
val imageStats = imageDao.getFaceCacheStats()
val faceStats = faceCacheDao.getCacheStats()
CacheStats(
totalImages = imageStats?.totalImages ?: 0,
imagesWithFaceCache = imageStats?.imagesWithFaceCache ?: 0,
imagesWithFaces = imageStats?.imagesWithFaces ?: 0,
imagesWithoutFaces = imageStats?.imagesWithoutFaces ?: 0,
needsScanning = imageStats?.needsScanning ?: 0,
totalFacesCached = faceStats.totalFaces,
facesWithEmbeddings = faceStats.withEmbeddings,
averageQuality = faceStats.avgQuality
)
}
}
/**
* Result of scanning a single image
*/
private data class ScanResult(
val imageCacheUpdate: ImageCacheUpdate,
val faceCacheEntries: List<FaceCacheEntity>
)
/**
* Image cache update data
*/
private data class ImageCacheUpdate(
val imageId: String,
val hasFaces: Boolean,
val faceCount: Int,
val imageUri: String
)
/**
* Enhanced cache stats
*/
data class CacheStats(
val totalImages: Int,
val imagesWithFaceCache: Int,
val imagesWithFaces: Int,
val imagesWithoutFaces: Int,
val needsScanning: Int,
val totalFacesCached: Int,
val facesWithEmbeddings: Int,
val averageQuality: Float
) {
val isComplete: Boolean
get() = needsScanning == 0
}

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package com.placeholder.sherpai2.domain.validation
import android.content.Context
import android.graphics.BitmapFactory
import android.net.Uri
import com.google.mlkit.vision.common.InputImage
import com.google.mlkit.vision.face.FaceDetection
import com.google.mlkit.vision.face.FaceDetectorOptions
import com.placeholder.sherpai2.data.local.dao.FaceModelDao
import com.placeholder.sherpai2.data.local.dao.ImageDao
import com.placeholder.sherpai2.data.local.entity.FaceModelEntity
import com.placeholder.sherpai2.data.local.entity.ImageEntity
import com.placeholder.sherpai2.ml.FaceNetModel
import dagger.hilt.android.qualifiers.ApplicationContext
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.async
import kotlinx.coroutines.awaitAll
import kotlinx.coroutines.coroutineScope
import kotlinx.coroutines.tasks.await
import kotlinx.coroutines.withContext
import javax.inject.Inject
import javax.inject.Singleton
/**
* ValidationScanService - Quick validation scan after training
*
* PURPOSE: Let user verify model quality BEFORE full library scan
*
* STRATEGY:
* 1. Sample 20-30 random photos with faces
* 2. Scan for the newly trained person
* 3. Return preview results with confidence scores
* 4. User reviews and decides: "Looks good" or "Add more photos"
*
* THRESHOLD STRATEGY:
* - Use CONSERVATIVE threshold (0.75) for validation
* - Better to show false negatives than false positives
* - If user approves, full scan uses slightly looser threshold (0.70)
*/
@Singleton
class ValidationScanService @Inject constructor(
@ApplicationContext private val context: Context,
private val imageDao: ImageDao,
private val faceModelDao: FaceModelDao
) {
companion object {
private const val VALIDATION_SAMPLE_SIZE = 25
private const val VALIDATION_THRESHOLD = 0.75f // Conservative
}
/**
* Perform validation scan after training
*
* @param personId The newly trained person
* @param onProgress Callback (current, total)
* @return Validation results with preview matches
*/
suspend fun performValidationScan(
personId: String,
onProgress: (Int, Int) -> Unit = { _, _ -> }
): ValidationScanResult = withContext(Dispatchers.Default) {
onProgress(0, 100)
// Step 1: Get face model
val faceModel = withContext(Dispatchers.IO) {
faceModelDao.getFaceModelByPersonId(personId)
} ?: return@withContext ValidationScanResult(
personId = personId,
matches = emptyList(),
sampleSize = 0,
errorMessage = "Face model not found"
)
onProgress(10, 100)
// Step 2: Get random sample of photos with faces
val allPhotosWithFaces = withContext(Dispatchers.IO) {
imageDao.getImagesWithFaces()
}
if (allPhotosWithFaces.isEmpty()) {
return@withContext ValidationScanResult(
personId = personId,
matches = emptyList(),
sampleSize = 0,
errorMessage = "No photos with faces in library"
)
}
// Random sample
val samplePhotos = allPhotosWithFaces.shuffled().take(VALIDATION_SAMPLE_SIZE)
onProgress(20, 100)
// Step 3: Scan sample photos
val faceNetModel = FaceNetModel(context)
val detector = FaceDetection.getClient(
FaceDetectorOptions.Builder()
.setPerformanceMode(FaceDetectorOptions.PERFORMANCE_MODE_ACCURATE)
.setMinFaceSize(0.15f)
.build()
)
try {
val matches = scanPhotosForPerson(
photos = samplePhotos,
faceModel = faceModel,
faceNetModel = faceNetModel,
detector = detector,
threshold = VALIDATION_THRESHOLD,
onProgress = { current, total ->
// Map to 20-100 range
val progress = 20 + (current * 80 / total)
onProgress(progress, 100)
}
)
onProgress(100, 100)
ValidationScanResult(
personId = personId,
matches = matches,
sampleSize = samplePhotos.size,
threshold = VALIDATION_THRESHOLD
)
} finally {
faceNetModel.close()
detector.close()
}
}
/**
* Scan photos for a specific person
*/
private suspend fun scanPhotosForPerson(
photos: List<ImageEntity>,
faceModel: FaceModelEntity,
faceNetModel: FaceNetModel,
detector: com.google.mlkit.vision.face.FaceDetector,
threshold: Float,
onProgress: (Int, Int) -> Unit
): List<ValidationMatch> = coroutineScope {
val modelEmbedding = faceModel.getEmbeddingArray()
val matches = mutableListOf<ValidationMatch>()
var processedCount = 0
// Process in parallel
val jobs = photos.map { photo ->
async(Dispatchers.IO) {
val photoMatches = scanSinglePhoto(
photo = photo,
modelEmbedding = modelEmbedding,
faceNetModel = faceNetModel,
detector = detector,
threshold = threshold
)
synchronized(matches) {
matches.addAll(photoMatches)
processedCount++
if (processedCount % 5 == 0) {
onProgress(processedCount, photos.size)
}
}
}
}
jobs.awaitAll()
matches.sortedByDescending { it.confidence }
}
/**
* Scan a single photo for the person
*/
private suspend fun scanSinglePhoto(
photo: ImageEntity,
modelEmbedding: FloatArray,
faceNetModel: FaceNetModel,
detector: com.google.mlkit.vision.face.FaceDetector,
threshold: Float
): List<ValidationMatch> = withContext(Dispatchers.IO) {
try {
// Load bitmap
val bitmap = loadBitmapDownsampled(Uri.parse(photo.imageUri), 768)
?: return@withContext emptyList()
// Detect faces
val inputImage = InputImage.fromBitmap(bitmap, 0)
val faces = detector.process(inputImage).await()
// Check each face
val matches = faces.mapNotNull { face ->
try {
// Crop face
val faceBitmap = android.graphics.Bitmap.createBitmap(
bitmap,
face.boundingBox.left.coerceIn(0, bitmap.width - 1),
face.boundingBox.top.coerceIn(0, bitmap.height - 1),
face.boundingBox.width().coerceAtMost(bitmap.width - face.boundingBox.left),
face.boundingBox.height().coerceAtMost(bitmap.height - face.boundingBox.top)
)
// Generate embedding
val faceEmbedding = faceNetModel.generateEmbedding(faceBitmap)
faceBitmap.recycle()
// Calculate similarity
val similarity = faceNetModel.calculateSimilarity(faceEmbedding, modelEmbedding)
if (similarity >= threshold) {
ValidationMatch(
imageId = photo.imageId,
imageUri = photo.imageUri,
capturedAt = photo.capturedAt,
confidence = similarity,
boundingBox = face.boundingBox,
faceCount = faces.size
)
} else {
null
}
} catch (e: Exception) {
null
}
}
bitmap.recycle()
matches
} catch (e: Exception) {
emptyList()
}
}
/**
* Load bitmap with downsampling
*/
private fun loadBitmapDownsampled(uri: Uri, maxDim: Int): android.graphics.Bitmap? {
return try {
val opts = BitmapFactory.Options().apply { inJustDecodeBounds = true }
context.contentResolver.openInputStream(uri)?.use {
BitmapFactory.decodeStream(it, null, opts)
}
var sample = 1
while (opts.outWidth / sample > maxDim || opts.outHeight / sample > maxDim) {
sample *= 2
}
val finalOpts = BitmapFactory.Options().apply {
inSampleSize = sample
}
context.contentResolver.openInputStream(uri)?.use {
BitmapFactory.decodeStream(it, null, finalOpts)
}
} catch (e: Exception) {
null
}
}
}
/**
* Result of validation scan
*/
data class ValidationScanResult(
val personId: String,
val matches: List<ValidationMatch>,
val sampleSize: Int,
val threshold: Float = 0.75f,
val errorMessage: String? = null
) {
val matchCount: Int get() = matches.size
val averageConfidence: Float get() = if (matches.isNotEmpty()) {
matches.map { it.confidence }.average().toFloat()
} else 0f
val qualityAssessment: ValidationQuality get() = when {
matchCount == 0 -> ValidationQuality.NO_MATCHES
averageConfidence >= 0.85f && matchCount >= 5 -> ValidationQuality.EXCELLENT
averageConfidence >= 0.78f && matchCount >= 3 -> ValidationQuality.GOOD
averageConfidence < 0.75f || matchCount < 2 -> ValidationQuality.POOR
else -> ValidationQuality.FAIR
}
}
/**
* Single match found during validation
*/
data class ValidationMatch(
val imageId: String,
val imageUri: String,
val capturedAt: Long,
val confidence: Float,
val boundingBox: android.graphics.Rect,
val faceCount: Int
)
/**
* Overall quality assessment
*/
enum class ValidationQuality {
EXCELLENT, // High confidence, many matches
GOOD, // Decent confidence, some matches
FAIR, // Acceptable, proceed with caution
POOR, // Low confidence or very few matches
NO_MATCHES // No matches found at all
}

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package com.placeholder.sherpai2.ml
import android.content.Context
import android.graphics.Bitmap
import android.util.Log
import org.tensorflow.lite.Interpreter
import java.io.FileInputStream
import java.nio.ByteBuffer
import java.nio.ByteOrder
import java.nio.MappedByteBuffer
import java.nio.channels.FileChannel
import kotlin.math.sqrt
/**
* FaceNetModel - MobileFaceNet wrapper with debugging
*
* IMPROVEMENTS:
* - ✅ Detailed error logging
* - ✅ Model validation on init
* - ✅ Embedding validation (detect all-zeros)
* - ✅ Toggle-able debug mode
*/
class FaceNetModel(
private val context: Context,
private val debugMode: Boolean = true // Enable for troubleshooting
) {
companion object {
private const val TAG = "FaceNetModel"
private const val MODEL_FILE = "mobilefacenet.tflite"
private const val INPUT_SIZE = 112
private const val EMBEDDING_SIZE = 192
const val SIMILARITY_THRESHOLD_HIGH = 0.7f
const val SIMILARITY_THRESHOLD_MEDIUM = 0.6f
const val SIMILARITY_THRESHOLD_LOW = 0.5f
}
private var interpreter: Interpreter? = null
private var modelLoadSuccess = false
init {
try {
if (debugMode) Log.d(TAG, "Loading FaceNet model: $MODEL_FILE")
val model = loadModelFile()
interpreter = Interpreter(model)
modelLoadSuccess = true
if (debugMode) {
Log.d(TAG, "✅ FaceNet model loaded successfully")
Log.d(TAG, "Model input size: ${INPUT_SIZE}x$INPUT_SIZE")
Log.d(TAG, "Embedding size: $EMBEDDING_SIZE")
}
// Test model with dummy input
testModel()
} catch (e: Exception) {
Log.e(TAG, "❌ CRITICAL: Failed to load FaceNet model from assets/$MODEL_FILE", e)
Log.e(TAG, "Make sure mobilefacenet.tflite exists in app/src/main/assets/")
modelLoadSuccess = false
throw RuntimeException("Failed to load FaceNet model: ${e.message}", e)
}
}
/**
* Test model with dummy input to verify it works
*/
private fun testModel() {
try {
val testBitmap = Bitmap.createBitmap(INPUT_SIZE, INPUT_SIZE, Bitmap.Config.ARGB_8888)
val testEmbedding = generateEmbedding(testBitmap)
testBitmap.recycle()
val sum = testEmbedding.sum()
val norm = sqrt(testEmbedding.map { it * it }.sum())
if (debugMode) {
Log.d(TAG, "Model test: embedding sum=$sum, norm=$norm")
}
if (sum == 0f || norm == 0f) {
Log.e(TAG, "⚠️ WARNING: Model test produced zero embedding!")
} else {
if (debugMode) Log.d(TAG, "✅ Model test passed")
}
} catch (e: Exception) {
Log.e(TAG, "Model test failed", e)
}
}
/**
* Load TFLite model from assets
*/
private fun loadModelFile(): MappedByteBuffer {
try {
val fileDescriptor = context.assets.openFd(MODEL_FILE)
val inputStream = FileInputStream(fileDescriptor.fileDescriptor)
val fileChannel = inputStream.channel
val startOffset = fileDescriptor.startOffset
val declaredLength = fileDescriptor.declaredLength
if (debugMode) {
Log.d(TAG, "Model file size: ${declaredLength / 1024}KB")
}
return fileChannel.map(FileChannel.MapMode.READ_ONLY, startOffset, declaredLength)
} catch (e: Exception) {
Log.e(TAG, "Failed to open model file: $MODEL_FILE", e)
throw e
}
}
/**
* Generate embedding for a single face
*
* @param faceBitmap Cropped face image (will be resized to 112x112)
* @return 192-dimensional embedding
*/
fun generateEmbedding(faceBitmap: Bitmap): FloatArray {
if (!modelLoadSuccess || interpreter == null) {
Log.e(TAG, "❌ Cannot generate embedding: model not loaded!")
return FloatArray(EMBEDDING_SIZE) { 0f }
}
try {
val resized = Bitmap.createScaledBitmap(faceBitmap, INPUT_SIZE, INPUT_SIZE, true)
val inputBuffer = preprocessImage(resized)
val output = Array(1) { FloatArray(EMBEDDING_SIZE) }
interpreter?.run(inputBuffer, output)
val normalized = normalizeEmbedding(output[0])
// DIAGNOSTIC: Check embedding quality
if (debugMode) {
val sum = normalized.sum()
val norm = sqrt(normalized.map { it * it }.sum())
if (sum == 0f && norm == 0f) {
Log.e(TAG, "❌ CRITICAL: Generated all-zero embedding!")
Log.e(TAG, "Input bitmap: ${faceBitmap.width}x${faceBitmap.height}")
} else {
Log.d(TAG, "✅ Embedding: sum=${"%.2f".format(sum)}, norm=${"%.2f".format(norm)}, first5=[${normalized.take(5).joinToString { "%.3f".format(it) }}]")
}
}
return normalized
} catch (e: Exception) {
Log.e(TAG, "Failed to generate embedding", e)
return FloatArray(EMBEDDING_SIZE) { 0f }
}
}
/**
* Generate embeddings for multiple faces (batch processing)
*/
fun generateEmbeddingsBatch(
faceBitmaps: List<Bitmap>,
onProgress: (Int, Int) -> Unit = { _, _ -> }
): List<FloatArray> {
if (debugMode) {
Log.d(TAG, "Generating embeddings for ${faceBitmaps.size} faces")
}
return faceBitmaps.mapIndexed { index, bitmap ->
onProgress(index + 1, faceBitmaps.size)
generateEmbedding(bitmap)
}
}
/**
* Create person model by averaging multiple embeddings
*/
fun createPersonModel(embeddings: List<FloatArray>): FloatArray {
require(embeddings.isNotEmpty()) { "Need at least one embedding" }
if (debugMode) {
Log.d(TAG, "Creating person model from ${embeddings.size} embeddings")
}
val averaged = FloatArray(EMBEDDING_SIZE) { 0f }
embeddings.forEach { embedding ->
for (i in embedding.indices) {
averaged[i] += embedding[i]
}
}
val count = embeddings.size.toFloat()
for (i in averaged.indices) {
averaged[i] /= count
}
val normalized = normalizeEmbedding(averaged)
if (debugMode) {
val sum = normalized.sum()
Log.d(TAG, "Person model created: sum=${"%.2f".format(sum)}")
}
return normalized
}
/**
* Calculate cosine similarity between two embeddings
* Returns value between -1.0 and 1.0 (higher = more similar)
*/
fun calculateSimilarity(embedding1: FloatArray, embedding2: FloatArray): Float {
require(embedding1.size == EMBEDDING_SIZE && embedding2.size == EMBEDDING_SIZE) {
"Invalid embedding size: ${embedding1.size} vs ${embedding2.size}"
}
var dotProduct = 0f
var norm1 = 0f
var norm2 = 0f
for (i in embedding1.indices) {
dotProduct += embedding1[i] * embedding2[i]
norm1 += embedding1[i] * embedding1[i]
norm2 += embedding2[i] * embedding2[i]
}
val similarity = dotProduct / (sqrt(norm1) * sqrt(norm2))
if (debugMode && (similarity.isNaN() || similarity.isInfinite())) {
Log.e(TAG, "❌ Invalid similarity: $similarity (norm1=$norm1, norm2=$norm2)")
return 0f
}
return similarity
}
/**
* Find best matching face model from a list
*
* @param faceEmbedding Embedding to match
* @param modelEmbeddings List of (modelId: String, embedding: FloatArray)
* @param threshold Minimum similarity threshold
* @return Pair of (modelId: String, confidence: Float) or null
*/
fun findBestMatch(
faceEmbedding: FloatArray,
modelEmbeddings: List<Pair<String, FloatArray>>,
threshold: Float = SIMILARITY_THRESHOLD_HIGH
): Pair<String, Float>? {
var bestMatch: Pair<String, Float>? = null
var highestSimilarity = threshold
for ((modelId, modelEmbedding) in modelEmbeddings) {
val similarity = calculateSimilarity(faceEmbedding, modelEmbedding)
if (similarity > highestSimilarity) {
highestSimilarity = similarity
bestMatch = Pair(modelId, similarity)
}
}
if (debugMode && bestMatch != null) {
Log.d(TAG, "Best match: ${bestMatch.first} with similarity ${bestMatch.second}")
}
return bestMatch
}
/**
* Preprocess image for model input
*/
private fun preprocessImage(bitmap: Bitmap): ByteBuffer {
val buffer = ByteBuffer.allocateDirect(4 * INPUT_SIZE * INPUT_SIZE * 3)
buffer.order(ByteOrder.nativeOrder())
val pixels = IntArray(INPUT_SIZE * INPUT_SIZE)
bitmap.getPixels(pixels, 0, INPUT_SIZE, 0, 0, INPUT_SIZE, INPUT_SIZE)
for (pixel in pixels) {
val r = ((pixel shr 16) and 0xFF) / 255.0f
val g = ((pixel shr 8) and 0xFF) / 255.0f
val b = (pixel and 0xFF) / 255.0f
// Normalize to [-1, 1]
buffer.putFloat((r - 0.5f) / 0.5f)
buffer.putFloat((g - 0.5f) / 0.5f)
buffer.putFloat((b - 0.5f) / 0.5f)
}
return buffer
}
/**
* Normalize embedding to unit length
*/
private fun normalizeEmbedding(embedding: FloatArray): FloatArray {
var norm = 0f
for (value in embedding) {
norm += value * value
}
norm = sqrt(norm)
return if (norm > 0) {
FloatArray(embedding.size) { i -> embedding[i] / norm }
} else {
Log.w(TAG, "⚠️ Cannot normalize zero embedding")
embedding
}
}
/**
* Get model status for diagnostics
*/
fun getModelStatus(): String {
return if (modelLoadSuccess) {
"✅ Model loaded and operational"
} else {
"❌ Model failed to load - check assets/$MODEL_FILE"
}
}
/**
* Clean up resources
*/
fun close() {
if (debugMode) {
Log.d(TAG, "Closing FaceNet model")
}
interpreter?.close()
interpreter = null
}
}

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package com.placeholder.sherpai2.ml
/**
* ThresholdStrategy - Smart threshold selection for face recognition
*
* Considers:
* - Training image count
* - Image quality
* - Detection context (group photo, selfie, etc.)
*/
object ThresholdStrategy {
/**
* Get optimal threshold for face recognition
*
* @param trainingCount Number of images used to train the model
* @param imageQuality Quality assessment of the image being scanned
* @param detectionContext Context of the detection (group, selfie, etc.)
* @return Similarity threshold (0.0 - 1.0)
*/
fun getOptimalThreshold(
trainingCount: Int,
imageQuality: ImageQuality = ImageQuality.UNKNOWN,
detectionContext: DetectionContext = DetectionContext.GENERAL
): Float {
// Base threshold from training count
val baseThreshold = when {
trainingCount >= 40 -> 0.68f // High confidence - strict
trainingCount >= 30 -> 0.62f // Good confidence - moderate-strict
trainingCount >= 20 -> 0.56f // Moderate confidence
trainingCount >= 15 -> 0.50f // Acceptable confidence - lenient
else -> 0.48f // Sparse training - very lenient
}
// Adjust based on image quality
val qualityAdjustment = when (imageQuality) {
ImageQuality.HIGH -> -0.02f // Can be stricter with good quality
ImageQuality.MEDIUM -> 0f // No change
ImageQuality.LOW -> +0.03f // Be more lenient with poor quality
ImageQuality.UNKNOWN -> 0f // No change
}
// Adjust based on detection context
val contextAdjustment = when (detectionContext) {
DetectionContext.GROUP_PHOTO -> +0.02f // More lenient in groups (faces smaller)
DetectionContext.SELFIE -> -0.03f // Stricter for close-ups (more detail)
DetectionContext.PROFILE -> +0.02f // More lenient for side profiles
DetectionContext.DISTANT -> +0.03f // More lenient for far away faces
DetectionContext.GENERAL -> 0f // No change
}
// Combine adjustments and clamp to safe range
return (baseThreshold + qualityAdjustment + contextAdjustment).coerceIn(0.40f, 0.75f)
}
/**
* Get threshold for liberal matching (e.g., during testing)
*/
fun getLiberalThreshold(trainingCount: Int): Float {
return when {
trainingCount >= 30 -> 0.52f
trainingCount >= 20 -> 0.48f
else -> 0.45f
}.coerceIn(0.40f, 0.65f)
}
/**
* Get threshold for conservative matching (minimize false positives)
*/
fun getConservativeThreshold(trainingCount: Int): Float {
return when {
trainingCount >= 40 -> 0.72f
trainingCount >= 30 -> 0.68f
trainingCount >= 20 -> 0.62f
else -> 0.58f
}.coerceIn(0.55f, 0.75f)
}
/**
* Estimate image quality from bitmap properties
*/
fun estimateImageQuality(width: Int, height: Int, fileSize: Long = 0): ImageQuality {
val megapixels = (width * height) / 1_000_000f
return when {
megapixels > 4.0f -> ImageQuality.HIGH
megapixels > 1.0f -> ImageQuality.MEDIUM
else -> ImageQuality.LOW
}
}
/**
* Estimate detection context from face count and face size
*/
fun estimateDetectionContext(
faceCount: Int,
faceAreaRatio: Float = 0f
): DetectionContext {
return when {
faceCount == 1 && faceAreaRatio > 0.15f -> DetectionContext.SELFIE
faceCount == 1 && faceAreaRatio < 0.05f -> DetectionContext.DISTANT
faceCount >= 3 -> DetectionContext.GROUP_PHOTO
else -> DetectionContext.GENERAL
}
}
}
/**
* Image quality assessment
*/
enum class ImageQuality {
HIGH, // > 4MP, good lighting
MEDIUM, // 1-4MP
LOW, // < 1MP, poor quality
UNKNOWN // Cannot determine
}
/**
* Detection context
*/
enum class DetectionContext {
GROUP_PHOTO, // Multiple faces (3+)
SELFIE, // Single face, close-up
PROFILE, // Side view
DISTANT, // Face is small in frame
GENERAL // Default
}

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// In navigation/AppDestinations.kt
package com.placeholder.sherpai2.navigation
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.filled.*
import androidx.compose.ui.graphics.vector.ImageVector
/**
* Defines all navigation destinations (screens) for the application.
*/
sealed class AppDestinations(val route: String, val icon: ImageVector, val label: String) {
// Core Functional Sections
object Search : AppDestinations("search", Icons.Default.Search, "Search")
object Models : AppDestinations("models", Icons.Default.Layers, "Models")
object Inventory : AppDestinations("inv", Icons.Default.Inventory2, "Inv")
object Train : AppDestinations("train", Icons.Default.TrackChanges, "Train")
object Tags : AppDestinations("tags", Icons.Default.LocalOffer, "Tags")
// Utility/Secondary Sections
object Upload : AppDestinations("upload", Icons.Default.CloudUpload, "Upload")
object Settings : AppDestinations("settings", Icons.Default.Settings, "Settings")
}
// Lists used by the AppDrawerContent to render the menu sections easily
val mainDrawerItems = listOf(
AppDestinations.Search,
AppDestinations.Models,
AppDestinations.Inventory,
AppDestinations.Train,
AppDestinations.Tags
)
val utilityDrawerItems = listOf(
AppDestinations.Upload,
AppDestinations.Settings
)

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@@ -1,57 +0,0 @@
// In presentation/MainScreen.kt
package com.placeholder.sherpai2.presentation
import androidx.compose.foundation.layout.padding
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.filled.Menu
import androidx.compose.material3.*
import androidx.compose.runtime.*
import androidx.compose.ui.Modifier
import com.placeholder.sherpai2.navigation.AppDestinations
import kotlinx.coroutines.launch
@OptIn(ExperimentalMaterial3Api::class)
@Composable
fun MainScreen() {
val drawerState = rememberDrawerState(initialValue = DrawerValue.Closed)
val scope = rememberCoroutineScope()
// State to track which screen is currently visible
//var currentScreen by remember { mutableStateOf(AppDestinations.Search) }
var currentScreen: AppDestinations by remember { mutableStateOf(AppDestinations.Search) }
// ModalNavigationDrawer provides the left sidebar UI/UX
ModalNavigationDrawer(
drawerState = drawerState,
drawerContent = {
// The content of the drawer (AppDrawerContent)
AppDrawerContent(
currentScreen = currentScreen,
onDestinationClicked = { destination ->
currentScreen = destination
scope.launch { drawerState.close() } // Close drawer after selection
}
)
},
) {
// The main content area
Scaffold(
topBar = {
TopAppBar(
title = { Text(currentScreen.label) },
// Button to open the drawer
navigationIcon = {
IconButton(onClick = { scope.launch { drawerState.open() } }) {
Icon(Icons.Filled.Menu, contentDescription = "Open Drawer")
}
}
)
}
) { paddingValues ->
// Displays the content for the currently selected screen
MainContentArea(
currentScreen = currentScreen,
modifier = Modifier.padding(paddingValues)
)
}
}
}

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@@ -1,59 +0,0 @@
// In presentation/AppDrawerContent.kt
package com.placeholder.sherpai2.presentation
import androidx.compose.foundation.layout.*
import androidx.compose.material3.*
import androidx.compose.runtime.Composable
import androidx.compose.ui.Modifier
import androidx.compose.ui.unit.dp
import com.placeholder.sherpai2.navigation.AppDestinations
import com.placeholder.sherpai2.navigation.mainDrawerItems
import com.placeholder.sherpai2.navigation.utilityDrawerItems
@OptIn(ExperimentalMaterial3Api::class)
@Composable
fun AppDrawerContent(
currentScreen: AppDestinations,
onDestinationClicked: (AppDestinations) -> Unit
) {
// Defines the width and content of the sliding drawer panel
ModalDrawerSheet(modifier = Modifier.width(280.dp)) {
// Header/Logo Area
Text(
"SherpAI Control Panel",
style = MaterialTheme.typography.headlineSmall,
modifier = Modifier.padding(16.dp)
)
Divider(Modifier.fillMaxWidth())
// 1. Main Navigation Items
Column(modifier = Modifier.padding(vertical = 8.dp)) {
mainDrawerItems.forEach { destination ->
NavigationDrawerItem(
label = { Text(destination.label) },
icon = { Icon(destination.icon, contentDescription = destination.label) },
selected = destination == currentScreen,
onClick = { onDestinationClicked(destination) },
modifier = Modifier.padding(NavigationDrawerItemDefaults.ItemPadding)
)
}
}
// Separator
Divider(Modifier.fillMaxWidth().padding(vertical = 8.dp))
// 2. Utility Items
Column(modifier = Modifier.padding(vertical = 8.dp)) {
utilityDrawerItems.forEach { destination ->
NavigationDrawerItem(
label = { Text(destination.label) },
icon = { Icon(destination.icon, contentDescription = destination.label) },
selected = destination == currentScreen,
onClick = { onDestinationClicked(destination) },
modifier = Modifier.padding(NavigationDrawerItemDefaults.ItemPadding)
)
}
}
}
}

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@@ -1,42 +0,0 @@
// In presentation/MainContentArea.kt
package com.placeholder.sherpai2.presentation
import androidx.compose.foundation.background
import androidx.compose.foundation.layout.*
import androidx.compose.material3.MaterialTheme
import androidx.compose.material3.Text
import androidx.compose.runtime.Composable
import androidx.compose.ui.Alignment
import androidx.compose.ui.Modifier
import androidx.compose.ui.unit.dp
import com.placeholder.sherpai2.navigation.AppDestinations
@Composable
fun MainContentArea(currentScreen: AppDestinations, modifier: Modifier = Modifier) {
Box(
modifier = modifier
.fillMaxSize()
.background(MaterialTheme.colorScheme.surfaceVariant),
contentAlignment = Alignment.Center
) {
// Swaps the UI content based on the selected screen from the drawer
when (currentScreen) {
AppDestinations.Search -> SimplePlaceholder("Search Screen: Find your models and data.")
AppDestinations.Models -> SimplePlaceholder("Models Screen: Manage your LoRA/embeddings.")
AppDestinations.Inventory -> SimplePlaceholder("Inventory Screen: View all collected data.")
AppDestinations.Train -> SimplePlaceholder("Train Screen: Start the LoRA adaptation process.")
AppDestinations.Tags -> SimplePlaceholder("Tags Screen: Create and edit custom tags.")
AppDestinations.Upload -> SimplePlaceholder("Upload Screen: Import new photos/data.")
AppDestinations.Settings -> SimplePlaceholder("Settings Screen: Configure app behavior.")
}
}
}
@Composable
private fun SimplePlaceholder(text: String) {
Text(
text = text,
style = MaterialTheme.typography.titleLarge,
modifier = Modifier.padding(16.dp)
)
}

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package com.placeholder.sherpai2.ui.album
import androidx.lifecycle.SavedStateHandle
import androidx.lifecycle.ViewModel
import androidx.lifecycle.viewModelScope
import com.placeholder.sherpai2.data.local.dao.ImageDao
import com.placeholder.sherpai2.data.local.dao.ImageTagDao
import com.placeholder.sherpai2.data.local.dao.PersonDao
import com.placeholder.sherpai2.data.local.dao.TagDao
import com.placeholder.sherpai2.data.local.entity.ImageEntity
import com.placeholder.sherpai2.data.local.entity.PersonEntity
import com.placeholder.sherpai2.data.local.entity.PhotoFaceTagEntity
import com.placeholder.sherpai2.data.repository.FaceRecognitionRepository
import com.placeholder.sherpai2.ui.search.DateRange
import dagger.hilt.android.lifecycle.HiltViewModel
import kotlinx.coroutines.flow.*
import kotlinx.coroutines.launch
import java.util.Calendar
import javax.inject.Inject
/**
* AlbumViewModel - Display photos from a specific album (tag, person, or time range)
*
* Features:
* - Search within album
* - Date filtering
* - Album stats
* - Export functionality
*/
@HiltViewModel
class AlbumViewModel @Inject constructor(
savedStateHandle: SavedStateHandle,
private val tagDao: TagDao,
private val imageTagDao: ImageTagDao,
private val imageDao: ImageDao,
private val personDao: PersonDao,
private val faceRecognitionRepository: FaceRecognitionRepository
) : ViewModel() {
// Album parameters from navigation
private val albumType: String = savedStateHandle["albumType"] ?: "tag"
private val albumId: String = savedStateHandle["albumId"] ?: ""
// UI state
private val _uiState = MutableStateFlow<AlbumUiState>(AlbumUiState.Loading)
val uiState: StateFlow<AlbumUiState> = _uiState.asStateFlow()
// Search query within album
private val _searchQuery = MutableStateFlow("")
val searchQuery: StateFlow<String> = _searchQuery.asStateFlow()
// Date range filter
private val _dateRange = MutableStateFlow(DateRange.ALL_TIME)
val dateRange: StateFlow<DateRange> = _dateRange.asStateFlow()
init {
loadAlbumData()
}
/**
* Load album data based on type
*/
private fun loadAlbumData() {
viewModelScope.launch {
try {
_uiState.value = AlbumUiState.Loading
when (albumType) {
"tag" -> loadTagAlbum()
"person" -> loadPersonAlbum()
"time" -> loadTimeAlbum()
else -> _uiState.value = AlbumUiState.Error("Unknown album type")
}
} catch (e: Exception) {
_uiState.value = AlbumUiState.Error(e.message ?: "Failed to load album")
}
}
}
private suspend fun loadTagAlbum() {
val tag = tagDao.getByValue(albumId)
if (tag == null) {
_uiState.value = AlbumUiState.Error("Tag not found")
return
}
combine(
_searchQuery,
_dateRange
) { query: String, dateRange: DateRange ->
Pair(query, dateRange)
}.collectLatest { (query, dateRange) ->
val imageIds = imageTagDao.findImagesByTag(tag.tagId, 0.5f)
val images = imageDao.getImagesByIds(imageIds)
val filteredImages = images
.filter { isInDateRange(it.capturedAt, dateRange) }
.filter {
query.isBlank() || containsQuery(it, query)
}
val imagesWithFaces = filteredImages.map { image ->
val tagsWithPersons = faceRecognitionRepository.getFaceTagsWithPersons(image.imageId)
AlbumPhoto(
image = image,
faceTags = tagsWithPersons.map { it.first },
persons = tagsWithPersons.map { it.second }
)
}
val uniquePersons = imagesWithFaces
.flatMap { it.persons }
.distinctBy { it.id }
_uiState.value = AlbumUiState.Success(
albumName = tag.value.replace("_", " ").replaceFirstChar { it.uppercase() },
albumType = "Tag",
photos = imagesWithFaces,
personCount = uniquePersons.size,
totalFaces = imagesWithFaces.sumOf { it.faceTags.size }
)
}
}
private suspend fun loadPersonAlbum() {
val person = personDao.getPersonById(albumId)
if (person == null) {
_uiState.value = AlbumUiState.Error("Person not found")
return
}
combine(
_searchQuery,
_dateRange
) { query: String, dateRange: DateRange ->
Pair(query, dateRange)
}.collectLatest { (query, dateRange) ->
val images = faceRecognitionRepository.getImagesForPerson(albumId)
val filteredImages = images
.filter { isInDateRange(it.capturedAt, dateRange) }
.filter {
query.isBlank() || containsQuery(it, query)
}
val imagesWithFaces = filteredImages.map { image ->
val tagsWithPersons = faceRecognitionRepository.getFaceTagsWithPersons(image.imageId)
AlbumPhoto(
image = image,
faceTags = tagsWithPersons.map { it.first },
persons = tagsWithPersons.map { it.second }
)
}
_uiState.value = AlbumUiState.Success(
albumName = person.name,
albumType = "Person",
photos = imagesWithFaces,
personCount = 1,
totalFaces = imagesWithFaces.sumOf { it.faceTags.size }
)
}
}
private suspend fun loadTimeAlbum() {
// Time-based albums (Today, This Week, etc)
val (startTime, endTime, albumName) = when (albumId) {
"today" -> Triple(getStartOfDay(), System.currentTimeMillis(), "Today")
"week" -> Triple(getStartOfWeek(), System.currentTimeMillis(), "This Week")
"month" -> Triple(getStartOfMonth(), System.currentTimeMillis(), "This Month")
"year" -> Triple(getStartOfYear(), System.currentTimeMillis(), "This Year")
else -> {
_uiState.value = AlbumUiState.Error("Unknown time range")
return
}
}
combine(
_searchQuery,
_dateRange
) { query: String, _: DateRange ->
query
}.collectLatest { query ->
val images = imageDao.getImagesInRange(startTime, endTime)
val filteredImages = images.filter {
query.isBlank() || containsQuery(it, query)
}
val imagesWithFaces = filteredImages.map { image ->
val tagsWithPersons = faceRecognitionRepository.getFaceTagsWithPersons(image.imageId)
AlbumPhoto(
image = image,
faceTags = tagsWithPersons.map { it.first },
persons = tagsWithPersons.map { it.second }
)
}
val uniquePersons = imagesWithFaces
.flatMap { it.persons }
.distinctBy { it.id }
_uiState.value = AlbumUiState.Success(
albumName = albumName,
albumType = "Time",
photos = imagesWithFaces,
personCount = uniquePersons.size,
totalFaces = imagesWithFaces.sumOf { it.faceTags.size }
)
}
}
fun setSearchQuery(query: String) {
_searchQuery.value = query
}
fun setDateRange(range: DateRange) {
_dateRange.value = range
}
private fun isInDateRange(timestamp: Long, range: DateRange): Boolean {
return when (range) {
DateRange.ALL_TIME -> true
DateRange.TODAY -> isToday(timestamp)
DateRange.THIS_WEEK -> isThisWeek(timestamp)
DateRange.THIS_MONTH -> isThisMonth(timestamp)
DateRange.THIS_YEAR -> isThisYear(timestamp)
}
}
private fun containsQuery(image: ImageEntity, query: String): Boolean {
// Could expand to search by person names, tags, etc.
return true
}
private fun isToday(timestamp: Long): Boolean {
val today = Calendar.getInstance()
val date = Calendar.getInstance().apply { timeInMillis = timestamp }
return today.get(Calendar.YEAR) == date.get(Calendar.YEAR) &&
today.get(Calendar.DAY_OF_YEAR) == date.get(Calendar.DAY_OF_YEAR)
}
private fun isThisWeek(timestamp: Long): Boolean {
val today = Calendar.getInstance()
val date = Calendar.getInstance().apply { timeInMillis = timestamp }
return today.get(Calendar.YEAR) == date.get(Calendar.YEAR) &&
today.get(Calendar.WEEK_OF_YEAR) == date.get(Calendar.WEEK_OF_YEAR)
}
private fun isThisMonth(timestamp: Long): Boolean {
val today = Calendar.getInstance()
val date = Calendar.getInstance().apply { timeInMillis = timestamp }
return today.get(Calendar.YEAR) == date.get(Calendar.YEAR) &&
today.get(Calendar.MONTH) == date.get(Calendar.MONTH)
}
private fun isThisYear(timestamp: Long): Boolean {
val today = Calendar.getInstance()
val date = Calendar.getInstance().apply { timeInMillis = timestamp }
return today.get(Calendar.YEAR) == date.get(Calendar.YEAR)
}
private fun getStartOfDay(): Long {
return Calendar.getInstance().apply {
set(Calendar.HOUR_OF_DAY, 0)
set(Calendar.MINUTE, 0)
set(Calendar.SECOND, 0)
set(Calendar.MILLISECOND, 0)
}.timeInMillis
}
private fun getStartOfWeek(): Long {
return Calendar.getInstance().apply {
set(Calendar.DAY_OF_WEEK, firstDayOfWeek)
set(Calendar.HOUR_OF_DAY, 0)
set(Calendar.MINUTE, 0)
set(Calendar.SECOND, 0)
set(Calendar.MILLISECOND, 0)
}.timeInMillis
}
private fun getStartOfMonth(): Long {
return Calendar.getInstance().apply {
set(Calendar.DAY_OF_MONTH, 1)
set(Calendar.HOUR_OF_DAY, 0)
set(Calendar.MINUTE, 0)
set(Calendar.SECOND, 0)
set(Calendar.MILLISECOND, 0)
}.timeInMillis
}
private fun getStartOfYear(): Long {
return Calendar.getInstance().apply {
set(Calendar.DAY_OF_YEAR, 1)
set(Calendar.HOUR_OF_DAY, 0)
set(Calendar.MINUTE, 0)
set(Calendar.SECOND, 0)
set(Calendar.MILLISECOND, 0)
}.timeInMillis
}
}
sealed class AlbumUiState {
object Loading : AlbumUiState()
data class Success(
val albumName: String,
val albumType: String,
val photos: List<AlbumPhoto>,
val personCount: Int,
val totalFaces: Int
) : AlbumUiState()
data class Error(val message: String) : AlbumUiState()
}
data class AlbumPhoto(
val image: ImageEntity,
val faceTags: List<PhotoFaceTagEntity>,
val persons: List<PersonEntity>
)

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package com.placeholder.sherpai2.ui.album
import androidx.compose.foundation.clickable
import androidx.compose.foundation.layout.*
import androidx.compose.foundation.lazy.LazyRow
import androidx.compose.foundation.lazy.grid.*
import androidx.compose.foundation.shape.RoundedCornerShape
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.filled.*
import androidx.compose.material3.*
import androidx.compose.runtime.*
import androidx.compose.ui.Alignment
import androidx.compose.ui.Modifier
import androidx.compose.ui.text.font.FontWeight
import androidx.compose.ui.text.style.TextOverflow
import androidx.compose.ui.unit.dp
import androidx.hilt.navigation.compose.hiltViewModel
import androidx.lifecycle.compose.collectAsStateWithLifecycle
import coil.compose.AsyncImage
import com.placeholder.sherpai2.ui.search.DateRange
/**
* AlbumViewScreen - CLEAN VERSION with Export
*
* REMOVED:
* - DisplayMode toggle
* - Verbose person tags
*
* ADDED:
* - Export menu (Folder, Zip, Collage)
* - Clean simple layout
*/
@OptIn(ExperimentalMaterial3Api::class)
@Composable
fun AlbumViewScreen(
onBack: () -> Unit,
onImageClick: (String) -> Unit,
viewModel: AlbumViewModel = hiltViewModel()
) {
val uiState by viewModel.uiState.collectAsStateWithLifecycle()
val searchQuery by viewModel.searchQuery.collectAsStateWithLifecycle()
val dateRange by viewModel.dateRange.collectAsStateWithLifecycle()
var showExportMenu by remember { mutableStateOf(false) }
Scaffold(
topBar = {
TopAppBar(
title = {
Column {
when (val state = uiState) {
is AlbumUiState.Success -> {
Text(
text = state.albumName,
style = MaterialTheme.typography.titleLarge,
fontWeight = FontWeight.Bold
)
Text(
text = "${state.photos.size} photos",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
else -> {
Text("Album")
}
}
}
},
navigationIcon = {
IconButton(onClick = onBack) {
Icon(Icons.Default.ArrowBack, "Back")
}
},
actions = {
// Export button
IconButton(onClick = { showExportMenu = true }) {
Icon(Icons.Default.FileDownload, "Export")
}
}
)
}
) { paddingValues ->
when (val state = uiState) {
is AlbumUiState.Loading -> {
Box(
modifier = Modifier
.fillMaxSize()
.padding(paddingValues),
contentAlignment = Alignment.Center
) {
CircularProgressIndicator()
}
}
is AlbumUiState.Error -> {
Box(
modifier = Modifier
.fillMaxSize()
.padding(paddingValues),
contentAlignment = Alignment.Center
) {
Column(
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.spacedBy(8.dp)
) {
Icon(
Icons.Default.Error,
contentDescription = null,
modifier = Modifier.size(48.dp),
tint = MaterialTheme.colorScheme.error
)
Text(state.message)
Button(onClick = onBack) {
Text("Go Back")
}
}
}
}
is AlbumUiState.Success -> {
AlbumContent(
state = state,
searchQuery = searchQuery,
dateRange = dateRange,
onSearchChange = { viewModel.setSearchQuery(it) },
onDateRangeChange = { viewModel.setDateRange(it) },
onImageClick = onImageClick,
modifier = Modifier.padding(paddingValues)
)
}
}
}
// Export menu dialog
if (showExportMenu) {
ExportDialog(
albumName = when (val state = uiState) {
is AlbumUiState.Success -> state.albumName
else -> "Album"
},
photoCount = when (val state = uiState) {
is AlbumUiState.Success -> state.photos.size
else -> 0
},
onDismiss = { showExportMenu = false },
onExportToFolder = {
// TODO: Implement folder export
showExportMenu = false
},
onExportToZip = {
// TODO: Implement zip export
showExportMenu = false
},
onExportToCollage = {
// TODO: Implement collage export
showExportMenu = false
}
)
}
}
@Composable
private fun AlbumContent(
state: AlbumUiState.Success,
searchQuery: String,
dateRange: DateRange,
onSearchChange: (String) -> Unit,
onDateRangeChange: (DateRange) -> Unit,
onImageClick: (String) -> Unit,
modifier: Modifier = Modifier
) {
Column(
modifier = modifier.fillMaxSize()
) {
// Stats card
Card(
modifier = Modifier
.fillMaxWidth()
.padding(16.dp),
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.primaryContainer.copy(alpha = 0.3f)
)
) {
Row(
modifier = Modifier
.fillMaxWidth()
.padding(16.dp),
horizontalArrangement = Arrangement.SpaceAround
) {
StatItem(Icons.Default.Photo, "Photos", state.photos.size.toString())
if (state.totalFaces > 0) {
StatItem(Icons.Default.Face, "Faces", state.totalFaces.toString())
}
if (state.personCount > 0) {
StatItem(Icons.Default.People, "People", state.personCount.toString())
}
}
}
// Search bar
OutlinedTextField(
value = searchQuery,
onValueChange = onSearchChange,
placeholder = { Text("Search in album...") },
leadingIcon = { Icon(Icons.Default.Search, null) },
trailingIcon = {
if (searchQuery.isNotEmpty()) {
IconButton(onClick = { onSearchChange("") }) {
Icon(Icons.Default.Clear, "Clear")
}
}
},
modifier = Modifier
.fillMaxWidth()
.padding(horizontal = 16.dp),
singleLine = true,
shape = RoundedCornerShape(16.dp)
)
Spacer(Modifier.height(8.dp))
// Date filters
LazyRow(
modifier = Modifier
.fillMaxWidth()
.padding(horizontal = 16.dp),
horizontalArrangement = Arrangement.spacedBy(8.dp)
) {
items(DateRange.entries.size) { index ->
val range = DateRange.entries[index]
val isActive = dateRange == range
FilterChip(
selected = isActive,
onClick = { onDateRangeChange(range) },
label = { Text(range.displayName) }
)
}
}
Spacer(Modifier.height(8.dp))
// Photo grid
if (state.photos.isEmpty()) {
Box(
modifier = Modifier.fillMaxSize(),
contentAlignment = Alignment.Center
) {
Text(
text = "No photos in this album",
style = MaterialTheme.typography.bodyLarge,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
} else {
LazyVerticalGrid(
columns = GridCells.Adaptive(120.dp),
contentPadding = PaddingValues(12.dp),
verticalArrangement = Arrangement.spacedBy(12.dp),
horizontalArrangement = Arrangement.spacedBy(12.dp),
modifier = Modifier.fillMaxSize()
) {
items(
items = state.photos,
key = { it.image.imageId }
) { photo ->
PhotoCard(
photo = photo,
onImageClick = onImageClick
)
}
}
}
}
}
@Composable
private fun StatItem(
icon: androidx.compose.ui.graphics.vector.ImageVector,
label: String,
value: String
) {
Column(
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.spacedBy(4.dp)
) {
Icon(
icon,
contentDescription = null,
modifier = Modifier.size(24.dp),
tint = MaterialTheme.colorScheme.primary
)
Text(
text = value,
style = MaterialTheme.typography.titleLarge,
fontWeight = FontWeight.Bold
)
Text(
text = label,
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
/**
* PhotoCard - CLEAN VERSION: Simple image + person names
*/
@Composable
private fun PhotoCard(
photo: AlbumPhoto,
onImageClick: (String) -> Unit
) {
Card(
modifier = Modifier
.fillMaxWidth()
.aspectRatio(1f)
.clickable { onImageClick(photo.image.imageUri) },
shape = RoundedCornerShape(12.dp)
) {
Box {
// Image
AsyncImage(
model = photo.image.imageUri,
contentDescription = null,
modifier = Modifier.fillMaxSize(),
contentScale = androidx.compose.ui.layout.ContentScale.Crop
)
// Person names overlay (if any)
if (photo.persons.isNotEmpty()) {
Surface(
color = MaterialTheme.colorScheme.surface.copy(alpha = 0.9f),
modifier = Modifier
.align(Alignment.BottomCenter)
.fillMaxWidth()
) {
Text(
text = photo.persons.take(2).joinToString(", ") { it.name },
style = MaterialTheme.typography.bodySmall,
modifier = Modifier.padding(8.dp),
maxLines = 1,
overflow = TextOverflow.Ellipsis,
fontWeight = FontWeight.Medium
)
}
}
}
}
}
/**
* Export Dialog
*/
@Composable
private fun ExportDialog(
albumName: String,
photoCount: Int,
onDismiss: () -> Unit,
onExportToFolder: () -> Unit,
onExportToZip: () -> Unit,
onExportToCollage: () -> Unit
) {
AlertDialog(
onDismissRequest = onDismiss,
icon = { Icon(Icons.Default.FileDownload, null) },
title = { Text("Export Album") },
text = {
Column(
modifier = Modifier.fillMaxWidth(),
verticalArrangement = Arrangement.spacedBy(12.dp)
) {
Text(
"$photoCount photos from \"$albumName\"",
style = MaterialTheme.typography.bodyMedium,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
// Export to Folder
ExportOption(
icon = Icons.Default.Folder,
title = "Export to Folder",
description = "Save all photos to a folder",
onClick = onExportToFolder
)
// Export to Zip
ExportOption(
icon = Icons.Default.FolderZip,
title = "Export as ZIP",
description = "Create a compressed archive",
onClick = onExportToZip
)
// Export to Collage (placeholder)
ExportOption(
icon = Icons.Default.GridView,
title = "Create Collage",
description = "Coming soon!",
onClick = onExportToCollage,
enabled = false
)
}
},
confirmButton = {
TextButton(onClick = onDismiss) {
Text("Cancel")
}
}
)
}
@Composable
private fun ExportOption(
icon: androidx.compose.ui.graphics.vector.ImageVector,
title: String,
description: String,
onClick: () -> Unit,
enabled: Boolean = true
) {
Surface(
modifier = Modifier
.fillMaxWidth()
.clickable(enabled = enabled, onClick = onClick),
shape = RoundedCornerShape(12.dp),
color = if (enabled) {
MaterialTheme.colorScheme.surfaceVariant
} else {
MaterialTheme.colorScheme.surfaceVariant.copy(alpha = 0.5f)
}
) {
Row(
modifier = Modifier.padding(16.dp),
horizontalArrangement = Arrangement.spacedBy(16.dp),
verticalAlignment = Alignment.CenterVertically
) {
Surface(
shape = RoundedCornerShape(8.dp),
color = MaterialTheme.colorScheme.primary.copy(
alpha = if (enabled) 1f else 0.5f
),
modifier = Modifier.size(40.dp)
) {
Box(contentAlignment = Alignment.Center) {
Icon(
icon,
contentDescription = null,
modifier = Modifier.size(24.dp),
tint = MaterialTheme.colorScheme.onPrimary
)
}
}
Column(modifier = Modifier.weight(1f)) {
Text(
title,
style = MaterialTheme.typography.titleMedium,
fontWeight = FontWeight.SemiBold,
color = if (enabled) {
MaterialTheme.colorScheme.onSurface
} else {
MaterialTheme.colorScheme.onSurface.copy(alpha = 0.5f)
}
)
Text(
description,
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant.copy(
alpha = if (enabled) 1f else 0.5f
)
)
}
if (enabled) {
Icon(
Icons.Default.ChevronRight,
contentDescription = null,
tint = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
}
}

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package com.placeholder.sherpai2.ui.collections
import androidx.compose.foundation.clickable
import androidx.compose.foundation.layout.*
import androidx.compose.foundation.lazy.grid.*
import androidx.compose.foundation.shape.RoundedCornerShape
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.filled.*
import androidx.compose.material3.*
import androidx.compose.runtime.*
import androidx.compose.ui.Alignment
import androidx.compose.ui.Modifier
import androidx.compose.ui.graphics.Color
import androidx.compose.ui.text.font.FontWeight
import androidx.compose.ui.text.style.TextOverflow
import androidx.compose.ui.unit.dp
import androidx.hilt.navigation.compose.hiltViewModel
import androidx.lifecycle.compose.collectAsStateWithLifecycle
import coil.compose.AsyncImage
/**
* CollectionsScreen - Main collections list
*
* Features:
* - Grid of collection cards
* - Create new collection button
* - Filter by type (all, smart, static)
* - Collection details on click
*/
@OptIn(ExperimentalMaterial3Api::class)
@Composable
fun CollectionsScreen(
onCollectionClick: (String) -> Unit,
onCreateClick: () -> Unit,
viewModel: CollectionsViewModel = hiltViewModel()
) {
val collections by viewModel.collections.collectAsStateWithLifecycle()
val creationState by viewModel.creationState.collectAsStateWithLifecycle()
Scaffold(
topBar = {
TopAppBar(
title = {
Column {
Text(
"Collections",
style = MaterialTheme.typography.titleLarge,
fontWeight = FontWeight.Bold
)
Text(
viewModel.getCollectionSummary(),
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
},
actions = {
IconButton(onClick = { viewModel.refreshSmartCollections() }) {
Icon(Icons.Default.Refresh, "Refresh smart collections")
}
}
)
},
floatingActionButton = {
ExtendedFloatingActionButton(
onClick = onCreateClick,
icon = { Icon(Icons.Default.Add, null) },
text = { Text("New Collection") }
)
}
) { paddingValues ->
if (collections.isEmpty()) {
EmptyState(
onCreateClick = onCreateClick,
modifier = Modifier
.fillMaxSize()
.padding(paddingValues)
)
} else {
LazyVerticalGrid(
columns = GridCells.Adaptive(160.dp),
modifier = Modifier
.fillMaxSize()
.padding(paddingValues),
contentPadding = PaddingValues(16.dp),
horizontalArrangement = Arrangement.spacedBy(12.dp),
verticalArrangement = Arrangement.spacedBy(12.dp)
) {
items(
items = collections,
key = { it.collectionId }
) { collection ->
CollectionCard(
collection = collection,
onClick = { onCollectionClick(collection.collectionId) },
onPinToggle = { viewModel.togglePinned(collection.collectionId) },
onDelete = { viewModel.deleteCollection(collection.collectionId) }
)
}
}
}
}
// Creation dialog (shown from SearchScreen or other places)
when (val state = creationState) {
is CreationState.SmartFromSearch -> {
CreateCollectionDialog(
title = "Smart Collection",
subtitle = "${state.photoCount} photos matching filters",
onConfirm = { name, description ->
viewModel.createSmartCollection(name, description)
},
onDismiss = { viewModel.cancelCreation() }
)
}
is CreationState.StaticFromImages -> {
CreateCollectionDialog(
title = "Static Collection",
subtitle = "${state.photoCount} photos selected",
onConfirm = { name, description ->
viewModel.createStaticCollection(name, description)
},
onDismiss = { viewModel.cancelCreation() }
)
}
CreationState.None -> { /* No dialog */ }
}
}
@Composable
private fun CollectionCard(
collection: com.placeholder.sherpai2.data.local.entity.CollectionEntity,
onClick: () -> Unit,
onPinToggle: () -> Unit,
onDelete: () -> Unit
) {
var showMenu by remember { mutableStateOf(false) }
Card(
modifier = Modifier
.fillMaxWidth()
.aspectRatio(0.75f)
.clickable(onClick = onClick),
shape = RoundedCornerShape(16.dp)
) {
Box(modifier = Modifier.fillMaxSize()) {
// Cover image or placeholder
if (collection.coverImageUri != null) {
AsyncImage(
model = collection.coverImageUri,
contentDescription = null,
modifier = Modifier.fillMaxSize(),
contentScale = androidx.compose.ui.layout.ContentScale.Crop
)
} else {
// Placeholder
Surface(
modifier = Modifier.fillMaxSize(),
color = MaterialTheme.colorScheme.surfaceVariant
) {
Icon(
Icons.Default.Photo,
contentDescription = null,
modifier = Modifier
.fillMaxSize()
.padding(48.dp),
tint = MaterialTheme.colorScheme.onSurfaceVariant.copy(alpha = 0.3f)
)
}
}
// Gradient overlay for text
Surface(
modifier = Modifier
.fillMaxWidth()
.align(Alignment.BottomCenter),
color = Color.Black.copy(alpha = 0.6f)
) {
Column(
modifier = Modifier.padding(12.dp),
verticalArrangement = Arrangement.spacedBy(4.dp)
) {
Row(
modifier = Modifier.fillMaxWidth(),
horizontalArrangement = Arrangement.SpaceBetween,
verticalAlignment = Alignment.CenterVertically
) {
Text(
collection.name,
style = MaterialTheme.typography.titleMedium,
fontWeight = FontWeight.Bold,
color = Color.White,
maxLines = 1,
overflow = TextOverflow.Ellipsis,
modifier = Modifier.weight(1f)
)
Box {
IconButton(
onClick = { showMenu = true },
modifier = Modifier.size(24.dp)
) {
Icon(
Icons.Default.MoreVert,
null,
tint = Color.White
)
}
DropdownMenu(
expanded = showMenu,
onDismissRequest = { showMenu = false }
) {
DropdownMenuItem(
text = { Text(if (collection.isPinned) "Unpin" else "Pin") },
onClick = {
onPinToggle()
showMenu = false
},
leadingIcon = {
Icon(
if (collection.isPinned) Icons.Default.PushPin else Icons.Default.PushPin,
null
)
}
)
DropdownMenuItem(
text = { Text("Delete") },
onClick = {
onDelete()
showMenu = false
},
leadingIcon = {
Icon(Icons.Default.Delete, null)
}
)
}
}
}
Row(
horizontalArrangement = Arrangement.spacedBy(8.dp),
verticalAlignment = Alignment.CenterVertically
) {
// Type badge
Surface(
color = when (collection.type) {
"SMART" -> Color(0xFF2196F3)
"FAVORITE" -> Color(0xFFF44336)
else -> Color(0xFF4CAF50)
}.copy(alpha = 0.9f),
shape = RoundedCornerShape(4.dp)
) {
Text(
when (collection.type) {
"SMART" -> "Smart"
"FAVORITE" -> "Fav"
else -> "Static"
},
modifier = Modifier.padding(horizontal = 6.dp, vertical = 2.dp),
style = MaterialTheme.typography.labelSmall,
color = Color.White
)
}
// Photo count
Text(
"${collection.photoCount} photos",
style = MaterialTheme.typography.bodySmall,
color = Color.White.copy(alpha = 0.9f)
)
}
}
}
// Pinned indicator
if (collection.isPinned) {
Icon(
Icons.Default.PushPin,
contentDescription = "Pinned",
modifier = Modifier
.align(Alignment.TopEnd)
.padding(8.dp)
.size(20.dp),
tint = Color.White
)
}
}
}
}
@Composable
private fun EmptyState(
onCreateClick: () -> Unit,
modifier: Modifier = Modifier
) {
Box(
modifier = modifier,
contentAlignment = Alignment.Center
) {
Column(
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.spacedBy(16.dp)
) {
Icon(
Icons.Default.Collections,
contentDescription = null,
modifier = Modifier.size(72.dp),
tint = MaterialTheme.colorScheme.onSurfaceVariant.copy(alpha = 0.6f)
)
Text(
"No Collections Yet",
style = MaterialTheme.typography.titleLarge,
fontWeight = FontWeight.Bold
)
Text(
"Create collections from searches or manually select photos",
style = MaterialTheme.typography.bodyMedium,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
Button(onClick = onCreateClick) {
Icon(Icons.Default.Add, null, Modifier.size(18.dp))
Spacer(Modifier.width(8.dp))
Text("Create Collection")
}
}
}
}
@Composable
private fun CreateCollectionDialog(
title: String,
subtitle: String,
onConfirm: (name: String, description: String?) -> Unit,
onDismiss: () -> Unit
) {
var name by remember { mutableStateOf("") }
var description by remember { mutableStateOf("") }
AlertDialog(
onDismissRequest = onDismiss,
icon = { Icon(Icons.Default.Collections, null) },
title = {
Column {
Text(title)
Text(
subtitle,
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
},
text = {
Column(verticalArrangement = Arrangement.spacedBy(12.dp)) {
OutlinedTextField(
value = name,
onValueChange = { name = it },
label = { Text("Collection Name") },
singleLine = true,
modifier = Modifier.fillMaxWidth()
)
OutlinedTextField(
value = description,
onValueChange = { description = it },
label = { Text("Description (optional)") },
maxLines = 3,
modifier = Modifier.fillMaxWidth()
)
}
},
confirmButton = {
Button(
onClick = {
if (name.isNotBlank()) {
onConfirm(name.trim(), description.trim().ifBlank { null })
}
},
enabled = name.isNotBlank()
) {
Text("Create")
}
},
dismissButton = {
TextButton(onClick = onDismiss) {
Text("Cancel")
}
}
)
}

View File

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package com.placeholder.sherpai2.ui.collections
import androidx.lifecycle.ViewModel
import androidx.lifecycle.viewModelScope
import com.placeholder.sherpai2.data.local.entity.CollectionEntity
import com.placeholder.sherpai2.data.repository.CollectionRepository
import com.placeholder.sherpai2.ui.search.DateRange
import dagger.hilt.android.lifecycle.HiltViewModel
import kotlinx.coroutines.flow.*
import kotlinx.coroutines.launch
import javax.inject.Inject
/**
* CollectionsViewModel - Manages collections list and creation
*/
@HiltViewModel
class CollectionsViewModel @Inject constructor(
private val collectionRepository: CollectionRepository
) : ViewModel() {
// All collections
val collections: StateFlow<List<CollectionEntity>> = collectionRepository
.getAllCollections()
.stateIn(
scope = viewModelScope,
started = SharingStarted.WhileSubscribed(5000),
initialValue = emptyList()
)
// UI state for creation dialog
private val _creationState = MutableStateFlow<CreationState>(CreationState.None)
val creationState: StateFlow<CreationState> = _creationState.asStateFlow()
// ==========================================
// COLLECTION CREATION
// ==========================================
fun startSmartCollectionFromSearch(
includedPeople: Set<String>,
excludedPeople: Set<String>,
includedTags: Set<String>,
excludedTags: Set<String>,
dateRange: DateRange,
photoCount: Int
) {
_creationState.value = CreationState.SmartFromSearch(
includedPeople = includedPeople,
excludedPeople = excludedPeople,
includedTags = includedTags,
excludedTags = excludedTags,
dateRange = dateRange,
photoCount = photoCount
)
}
fun startStaticCollectionFromImages(imageIds: List<String>) {
_creationState.value = CreationState.StaticFromImages(
imageIds = imageIds,
photoCount = imageIds.size
)
}
fun cancelCreation() {
_creationState.value = CreationState.None
}
fun createSmartCollection(name: String, description: String?) {
val state = _creationState.value as? CreationState.SmartFromSearch ?: return
viewModelScope.launch {
collectionRepository.createSmartCollection(
name = name,
description = description,
includedPeople = state.includedPeople,
excludedPeople = state.excludedPeople,
includedTags = state.includedTags,
excludedTags = state.excludedTags,
dateRange = state.dateRange
)
_creationState.value = CreationState.None
}
}
fun createStaticCollection(name: String, description: String?) {
val state = _creationState.value as? CreationState.StaticFromImages ?: return
viewModelScope.launch {
collectionRepository.createStaticCollection(
name = name,
description = description,
imageIds = state.imageIds
)
_creationState.value = CreationState.None
}
}
// ==========================================
// COLLECTION MANAGEMENT
// ==========================================
fun deleteCollection(collectionId: String) {
viewModelScope.launch {
collectionRepository.deleteCollection(collectionId)
}
}
fun togglePinned(collectionId: String) {
viewModelScope.launch {
collectionRepository.togglePinned(collectionId)
}
}
fun refreshSmartCollections() {
viewModelScope.launch {
collectionRepository.evaluateAllSmartCollections()
}
}
// ==========================================
// STATISTICS
// ==========================================
fun getCollectionSummary(): String {
val count = collections.value.size
val smartCount = collections.value.count { it.type == "SMART" }
val staticCount = collections.value.count { it.type == "STATIC" }
return when {
count == 0 -> "No collections yet"
smartCount > 0 && staticCount > 0 -> "$smartCount smart • $staticCount static"
smartCount > 0 -> "$smartCount smart collections"
staticCount > 0 -> "$staticCount static collections"
else -> "$count collections"
}
}
}
/**
* Creation state for dialogs
*/
sealed class CreationState {
object None : CreationState()
data class SmartFromSearch(
val includedPeople: Set<String>,
val excludedPeople: Set<String>,
val includedTags: Set<String>,
val excludedTags: Set<String>,
val dateRange: DateRange,
val photoCount: Int
) : CreationState()
data class StaticFromImages(
val imageIds: List<String>,
val photoCount: Int
) : CreationState()
}

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package com.placeholder.sherpai2.ui.devscreens
import androidx.compose.foundation.background
import androidx.compose.foundation.layout.*
import androidx.compose.foundation.shape.RoundedCornerShape
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.filled.*
import androidx.compose.material3.*
import androidx.compose.runtime.Composable
import androidx.compose.ui.Alignment
import androidx.compose.ui.Modifier
import androidx.compose.ui.graphics.Brush
import androidx.compose.ui.text.font.FontWeight
import androidx.compose.ui.text.style.TextAlign
import androidx.compose.ui.unit.dp
/**
* Beautiful placeholder screen for features under development
*
* Shows:
* - Feature name
* - Description
* - "Coming Soon" indicator
* - Consistent styling with rest of app
*/
@Composable
fun DummyScreen(
title: String,
subtitle: String = "This feature is under development"
) {
Box(
modifier = Modifier
.fillMaxSize()
.background(
Brush.verticalGradient(
colors = listOf(
MaterialTheme.colorScheme.surface,
MaterialTheme.colorScheme.surfaceVariant.copy(alpha = 0.3f)
)
)
),
contentAlignment = Alignment.Center
) {
Column(
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.spacedBy(24.dp),
modifier = Modifier.padding(48.dp)
) {
// Icon badge
Surface(
modifier = Modifier.size(96.dp),
shape = RoundedCornerShape(24.dp),
color = MaterialTheme.colorScheme.primaryContainer,
shadowElevation = 8.dp
) {
Box(contentAlignment = Alignment.Center) {
Icon(
Icons.Default.Construction,
contentDescription = null,
modifier = Modifier.size(48.dp),
tint = MaterialTheme.colorScheme.primary
)
}
}
Spacer(modifier = Modifier.height(8.dp))
// Title
Text(
text = title,
style = MaterialTheme.typography.headlineMedium,
fontWeight = FontWeight.Bold,
textAlign = TextAlign.Center
)
// Subtitle
Text(
text = subtitle,
style = MaterialTheme.typography.bodyLarge,
color = MaterialTheme.colorScheme.onSurfaceVariant,
textAlign = TextAlign.Center,
modifier = Modifier.padding(horizontal = 24.dp)
)
Spacer(modifier = Modifier.height(8.dp))
// Coming soon badge
Surface(
shape = RoundedCornerShape(16.dp),
color = MaterialTheme.colorScheme.tertiaryContainer,
shadowElevation = 2.dp
) {
Row(
modifier = Modifier.padding(horizontal = 20.dp, vertical = 12.dp),
horizontalArrangement = Arrangement.spacedBy(8.dp),
verticalAlignment = Alignment.CenterVertically
) {
Icon(
Icons.Default.Schedule,
contentDescription = null,
modifier = Modifier.size(20.dp),
tint = MaterialTheme.colorScheme.onTertiaryContainer
)
Text(
text = "Coming Soon",
style = MaterialTheme.typography.labelLarge,
fontWeight = FontWeight.SemiBold,
color = MaterialTheme.colorScheme.onTertiaryContainer
)
}
}
Spacer(modifier = Modifier.height(24.dp))
// Feature preview card
Card(
modifier = Modifier.fillMaxWidth(0.8f),
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.surfaceVariant.copy(alpha = 0.5f)
),
shape = RoundedCornerShape(16.dp)
) {
Column(
modifier = Modifier.padding(20.dp),
verticalArrangement = Arrangement.spacedBy(12.dp)
) {
Text(
text = "What's planned:",
style = MaterialTheme.typography.titleSmall,
fontWeight = FontWeight.Bold
)
FeatureItem("Full implementation")
FeatureItem("Beautiful UI design")
FeatureItem("Smooth animations")
FeatureItem("Production-ready code")
}
}
}
}
}
@Composable
private fun FeatureItem(text: String) {
Row(
horizontalArrangement = Arrangement.spacedBy(8.dp),
verticalAlignment = Alignment.CenterVertically
) {
Icon(
Icons.Default.CheckCircle,
contentDescription = null,
modifier = Modifier.size(16.dp),
tint = MaterialTheme.colorScheme.primary
)
Text(
text = text,
style = MaterialTheme.typography.bodyMedium,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}

View File

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package com.placeholder.sherpai2.ui.discover
import android.net.Uri
import androidx.compose.foundation.background
import androidx.compose.foundation.border
import androidx.compose.foundation.clickable
import androidx.compose.foundation.layout.*
import androidx.compose.foundation.lazy.grid.GridCells
import androidx.compose.foundation.lazy.grid.LazyVerticalGrid
import androidx.compose.foundation.lazy.grid.items
import androidx.compose.foundation.shape.CircleShape
import androidx.compose.foundation.shape.RoundedCornerShape
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.filled.Check
import androidx.compose.material.icons.filled.Warning
import androidx.compose.material3.*
import androidx.compose.runtime.*
import androidx.compose.ui.Alignment
import androidx.compose.ui.Modifier
import androidx.compose.ui.draw.clip
import androidx.compose.ui.graphics.Color
import androidx.compose.ui.layout.ContentScale
import androidx.compose.ui.text.font.FontWeight
import androidx.compose.ui.unit.dp
import coil.compose.AsyncImage
import com.placeholder.sherpai2.domain.clustering.ClusterQualityAnalyzer
import com.placeholder.sherpai2.domain.clustering.ClusterQualityTier
import com.placeholder.sherpai2.domain.clustering.ClusteringResult
import com.placeholder.sherpai2.domain.clustering.FaceCluster
/**
* ClusterGridScreen - Shows all discovered clusters in 2x2 grid
*
* Each cluster card shows:
* - 2x2 grid of representative faces
* - Photo count
* - Quality badge (Excellent/Good/Poor)
* - Tap to name
*
* IMPROVEMENTS:
* - ✅ Quality badges for each cluster
* - ✅ Visual indicators for trainable vs non-trainable clusters
* - ✅ Better UX with disabled states for poor quality clusters
*/
@Composable
fun ClusterGridScreen(
result: ClusteringResult,
onSelectCluster: (FaceCluster) -> Unit,
modifier: Modifier = Modifier,
qualityAnalyzer: ClusterQualityAnalyzer = remember { ClusterQualityAnalyzer() }
) {
Column(
modifier = modifier
.fillMaxSize()
.padding(16.dp)
) {
// Header
Text(
text = "Found ${result.clusters.size} ${if (result.clusters.size == 1) "Person" else "People"}",
style = MaterialTheme.typography.headlineMedium,
fontWeight = FontWeight.Bold
)
Spacer(modifier = Modifier.height(8.dp))
Text(
text = "Tap a cluster to name the person",
style = MaterialTheme.typography.bodyMedium,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
Spacer(modifier = Modifier.height(16.dp))
// Grid of clusters
LazyVerticalGrid(
columns = GridCells.Fixed(2),
horizontalArrangement = Arrangement.spacedBy(12.dp),
verticalArrangement = Arrangement.spacedBy(12.dp)
) {
items(result.clusters) { cluster ->
// Analyze quality for each cluster
val qualityResult = remember(cluster) {
qualityAnalyzer.analyzeCluster(cluster)
}
ClusterCard(
cluster = cluster,
qualityTier = qualityResult.qualityTier,
canTrain = qualityResult.canTrain,
onClick = { onSelectCluster(cluster) }
)
}
}
}
}
/**
* Single cluster card with 2x2 face grid and quality badge
*/
@Composable
private fun ClusterCard(
cluster: FaceCluster,
qualityTier: ClusterQualityTier,
canTrain: Boolean,
onClick: () -> Unit
) {
Card(
modifier = Modifier
.fillMaxWidth()
.aspectRatio(1f)
.clickable(onClick = onClick), // Always clickable - let dialog handle validation
elevation = CardDefaults.cardElevation(defaultElevation = 2.dp),
colors = CardDefaults.cardColors(
containerColor = when {
qualityTier == ClusterQualityTier.POOR ->
MaterialTheme.colorScheme.errorContainer.copy(alpha = 0.3f)
!canTrain ->
MaterialTheme.colorScheme.surfaceVariant.copy(alpha = 0.5f)
else ->
MaterialTheme.colorScheme.surface
}
)
) {
Box(
modifier = Modifier.fillMaxSize()
) {
Column(
modifier = Modifier.fillMaxSize()
) {
// 2x2 grid of faces
val facesToShow = cluster.representativeFaces.take(4)
Column(
modifier = Modifier.weight(1f)
) {
// Top row (2 faces)
Row(modifier = Modifier.weight(1f)) {
facesToShow.getOrNull(0)?.let { face ->
FaceThumbnail(
imageUri = face.imageUri,
enabled = canTrain,
modifier = Modifier.weight(1f)
)
} ?: EmptyFaceSlot(Modifier.weight(1f))
facesToShow.getOrNull(1)?.let { face ->
FaceThumbnail(
imageUri = face.imageUri,
enabled = canTrain,
modifier = Modifier.weight(1f)
)
} ?: EmptyFaceSlot(Modifier.weight(1f))
}
// Bottom row (2 faces)
Row(modifier = Modifier.weight(1f)) {
facesToShow.getOrNull(2)?.let { face ->
FaceThumbnail(
imageUri = face.imageUri,
enabled = canTrain,
modifier = Modifier.weight(1f)
)
} ?: EmptyFaceSlot(Modifier.weight(1f))
facesToShow.getOrNull(3)?.let { face ->
FaceThumbnail(
imageUri = face.imageUri,
enabled = canTrain,
modifier = Modifier.weight(1f)
)
} ?: EmptyFaceSlot(Modifier.weight(1f))
}
}
// Footer with photo count
Surface(
modifier = Modifier.fillMaxWidth(),
color = if (canTrain) {
MaterialTheme.colorScheme.primaryContainer
} else {
MaterialTheme.colorScheme.surfaceVariant
}
) {
Row(
modifier = Modifier.padding(12.dp),
verticalAlignment = Alignment.CenterVertically,
horizontalArrangement = Arrangement.SpaceBetween
) {
Text(
text = "${cluster.photoCount} photos",
style = MaterialTheme.typography.bodyMedium,
fontWeight = FontWeight.SemiBold,
color = if (canTrain) {
MaterialTheme.colorScheme.onPrimaryContainer
} else {
MaterialTheme.colorScheme.onSurfaceVariant
}
)
}
}
}
// Quality badge overlay
QualityBadge(
qualityTier = qualityTier,
canTrain = canTrain,
modifier = Modifier
.align(Alignment.TopEnd)
.padding(8.dp)
)
}
}
}
/**
* Quality badge indicator
*/
@Composable
private fun QualityBadge(
qualityTier: ClusterQualityTier,
canTrain: Boolean,
modifier: Modifier = Modifier
) {
val (backgroundColor, iconColor, icon) = when (qualityTier) {
ClusterQualityTier.EXCELLENT -> Triple(
Color(0xFF1B5E20),
Color.White,
Icons.Default.Check
)
ClusterQualityTier.GOOD -> Triple(
Color(0xFF2E7D32),
Color.White,
Icons.Default.Check
)
ClusterQualityTier.POOR -> Triple(
Color(0xFFD32F2F),
Color.White,
Icons.Default.Warning
)
}
Surface(
modifier = modifier,
shape = CircleShape,
color = backgroundColor,
shadowElevation = 2.dp
) {
Box(
modifier = Modifier
.size(32.dp)
.padding(6.dp),
contentAlignment = Alignment.Center
) {
Icon(
imageVector = icon,
contentDescription = qualityTier.name,
tint = iconColor,
modifier = Modifier.size(20.dp)
)
}
}
}
@Composable
private fun FaceThumbnail(
imageUri: String,
enabled: Boolean,
modifier: Modifier = Modifier
) {
Box(modifier = modifier) {
AsyncImage(
model = Uri.parse(imageUri),
contentDescription = "Face",
modifier = Modifier
.fillMaxSize()
.border(
width = 0.5.dp,
color = MaterialTheme.colorScheme.outline.copy(alpha = 0.3f)
),
contentScale = ContentScale.Crop,
alpha = if (enabled) 1f else 0.6f
)
}
}
@Composable
private fun EmptyFaceSlot(modifier: Modifier = Modifier) {
Box(
modifier = modifier
.fillMaxSize()
.background(MaterialTheme.colorScheme.surfaceVariant)
.border(
width = 0.5.dp,
color = MaterialTheme.colorScheme.outline.copy(alpha = 0.3f)
)
)
}

View File

@@ -0,0 +1,753 @@
package com.placeholder.sherpai2.ui.discover
import androidx.compose.foundation.layout.*
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.filled.Person
import androidx.compose.material.icons.filled.Refresh
import androidx.compose.material.icons.filled.Storage
import androidx.compose.material3.*
import androidx.compose.runtime.*
import androidx.compose.ui.Alignment
import androidx.compose.ui.Modifier
import androidx.compose.ui.text.font.FontWeight
import androidx.compose.ui.text.style.TextAlign
import androidx.compose.ui.unit.dp
import androidx.hilt.navigation.compose.hiltViewModel
import com.placeholder.sherpai2.domain.clustering.ClusterQualityAnalyzer
/**
* DiscoverPeopleScreen - WITH SETTINGS SUPPORT
*
* NEW FEATURES:
* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
* ✅ Discovery settings card with quality sliders
* ✅ Retry button in naming dialog
* ✅ Cache building progress UI
* ✅ Settings affect clustering behavior
*/
@OptIn(ExperimentalMaterial3Api::class)
@Composable
fun DiscoverPeopleScreen(
viewModel: DiscoverPeopleViewModel = hiltViewModel(),
onNavigateBack: () -> Unit = {}
) {
val uiState by viewModel.uiState.collectAsState()
val qualityAnalyzer = remember { ClusterQualityAnalyzer() }
// NEW: Settings state
var settings by remember { mutableStateOf(DiscoverySettings.DEFAULT) }
Box(modifier = Modifier.fillMaxSize()) {
when (val state = uiState) {
// ===== IDLE STATE (START HERE) =====
is DiscoverUiState.Idle -> {
IdleStateWithSettings(
settings = settings,
onSettingsChange = { settings = it },
onStartDiscovery = { viewModel.startDiscovery(settings) }
)
}
// ===== NEW: BUILDING CACHE (FIRST-TIME SETUP) =====
is DiscoverUiState.BuildingCache -> {
BuildingCacheContent(
progress = state.progress,
total = state.total,
message = state.message
)
}
// ===== CLUSTERING IN PROGRESS =====
is DiscoverUiState.Clustering -> {
ClusteringProgressContent(
progress = state.progress,
total = state.total,
message = state.message
)
}
// ===== CLUSTERS READY FOR NAMING =====
is DiscoverUiState.NamingReady -> {
ClusterGridScreen(
result = state.result,
onSelectCluster = { cluster ->
viewModel.selectCluster(cluster)
},
qualityAnalyzer = qualityAnalyzer
)
}
// ===== ANALYZING CLUSTER QUALITY =====
is DiscoverUiState.AnalyzingCluster -> {
LoadingContent(message = "Analyzing cluster quality...")
}
// ===== NAMING A CLUSTER (SHOW DIALOG) =====
is DiscoverUiState.NamingCluster -> {
ClusterGridScreen(
result = state.result,
onSelectCluster = { /* Disabled while dialog open */ },
qualityAnalyzer = qualityAnalyzer
)
NamingDialog(
cluster = state.selectedCluster,
suggestedSiblings = state.suggestedSiblings,
onConfirm = { name, dateOfBirth, isChild, selectedSiblings ->
viewModel.confirmClusterName(
cluster = state.selectedCluster,
name = name,
dateOfBirth = dateOfBirth,
isChild = isChild,
selectedSiblings = selectedSiblings
)
},
onRetry = { viewModel.retryDiscovery() }, // NEW!
onDismiss = {
viewModel.cancelNaming()
},
qualityAnalyzer = qualityAnalyzer
)
}
// ===== TRAINING IN PROGRESS =====
is DiscoverUiState.Training -> {
TrainingProgressContent(
stage = state.stage,
progress = state.progress,
total = state.total
)
}
// ===== VALIDATION PREVIEW =====
is DiscoverUiState.ValidationPreview -> {
ValidationPreviewScreen(
personName = state.personName,
validationResult = state.validationResult,
onMarkFeedback = { feedbackMap ->
viewModel.submitFeedback(state.cluster, feedbackMap)
},
onRequestRefinement = {
viewModel.requestRefinement(state.cluster)
},
onApprove = {
viewModel.acceptValidationAndFinish()
},
onReject = {
viewModel.requestRefinement(state.cluster)
}
)
}
// ===== REFINEMENT NEEDED =====
is DiscoverUiState.RefinementNeeded -> {
RefinementNeededContent(
recommendation = state.recommendation,
currentIteration = state.currentIteration,
onRefine = {
viewModel.requestRefinement(state.cluster)
},
onSkip = {
viewModel.skipRefinement()
}
)
}
// ===== REFINING IN PROGRESS =====
is DiscoverUiState.Refining -> {
RefiningProgressContent(
iteration = state.iteration,
message = state.message
)
}
// ===== COMPLETE =====
is DiscoverUiState.Complete -> {
CompleteStateContent(
message = state.message,
onDone = onNavigateBack,
onDiscoverMore = { viewModel.retryDiscovery() }
)
}
// ===== NO PEOPLE FOUND =====
is DiscoverUiState.NoPeopleFound -> {
ErrorStateContent(
title = "No People Found",
message = state.message,
onRetry = { viewModel.retryDiscovery() },
onBack = onNavigateBack
)
}
// ===== ERROR =====
is DiscoverUiState.Error -> {
ErrorStateContent(
title = "Error",
message = state.message,
onRetry = { viewModel.retryDiscovery() },
onBack = onNavigateBack
)
}
}
}
}
// ═══════════════════════════════════════════════════════════
// IDLE STATE WITH SETTINGS
// ═══════════════════════════════════════════════════════════
@Composable
private fun IdleStateWithSettings(
settings: DiscoverySettings,
onSettingsChange: (DiscoverySettings) -> Unit,
onStartDiscovery: () -> Unit
) {
Column(
modifier = Modifier
.fillMaxSize()
.padding(24.dp),
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.Center
) {
Icon(
imageVector = Icons.Default.Person,
contentDescription = null,
modifier = Modifier.size(120.dp),
tint = MaterialTheme.colorScheme.primary
)
Spacer(modifier = Modifier.height(32.dp))
Text(
text = "Automatically find and organize people in your photo library",
style = MaterialTheme.typography.headlineSmall,
textAlign = TextAlign.Center,
color = MaterialTheme.colorScheme.onSurface
)
Spacer(modifier = Modifier.height(32.dp))
// NEW: Settings Card
DiscoverySettingsCard(
settings = settings,
onSettingsChange = onSettingsChange
)
Spacer(modifier = Modifier.height(24.dp))
Button(
onClick = onStartDiscovery,
modifier = Modifier
.fillMaxWidth()
.height(56.dp)
) {
Text(
text = "Start Discovery",
style = MaterialTheme.typography.titleMedium
)
}
Spacer(modifier = Modifier.height(16.dp))
Text(
text = "This will analyze faces in your photos and group similar faces together",
style = MaterialTheme.typography.bodySmall,
textAlign = TextAlign.Center,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
// ═══════════════════════════════════════════════════════════
// BUILDING CACHE CONTENT
// ═══════════════════════════════════════════════════════════
@Composable
private fun BuildingCacheContent(
progress: Int,
total: Int,
message: String
) {
Column(
modifier = Modifier
.fillMaxSize()
.padding(24.dp),
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.Center
) {
Icon(
imageVector = Icons.Default.Storage,
contentDescription = null,
modifier = Modifier.size(80.dp),
tint = MaterialTheme.colorScheme.primary
)
Spacer(modifier = Modifier.height(32.dp))
Text(
text = "Building Cache",
style = MaterialTheme.typography.headlineMedium,
fontWeight = FontWeight.Bold,
textAlign = TextAlign.Center
)
Spacer(modifier = Modifier.height(16.dp))
Card(
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.primaryContainer
),
modifier = Modifier.fillMaxWidth()
) {
Column(
modifier = Modifier.padding(16.dp),
horizontalAlignment = Alignment.CenterHorizontally
) {
Text(
text = message,
style = MaterialTheme.typography.bodyMedium,
textAlign = TextAlign.Center,
color = MaterialTheme.colorScheme.onPrimaryContainer
)
}
}
Spacer(modifier = Modifier.height(24.dp))
if (total > 0) {
LinearProgressIndicator(
progress = { progress.toFloat() / total.toFloat() },
modifier = Modifier
.fillMaxWidth()
.height(12.dp)
)
Spacer(modifier = Modifier.height(12.dp))
Text(
text = "$progress / $total photos analyzed",
style = MaterialTheme.typography.bodyLarge,
fontWeight = FontWeight.Medium,
color = MaterialTheme.colorScheme.primary
)
Spacer(modifier = Modifier.height(8.dp))
val percentComplete = (progress.toFloat() / total.toFloat() * 100).toInt()
Text(
text = "$percentComplete% complete",
style = MaterialTheme.typography.bodyMedium,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
} else {
CircularProgressIndicator(
modifier = Modifier.size(64.dp)
)
}
Spacer(modifier = Modifier.height(32.dp))
Card(
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.secondaryContainer
),
modifier = Modifier.fillMaxWidth()
) {
Column(
modifier = Modifier.padding(16.dp)
) {
Text(
text = " What's happening?",
style = MaterialTheme.typography.titleSmall,
fontWeight = FontWeight.Bold,
color = MaterialTheme.colorScheme.onSecondaryContainer
)
Spacer(modifier = Modifier.height(8.dp))
Text(
text = "We're analyzing your photo library once to identify which photos contain faces. " +
"This speeds up future discoveries by 95%!\n\n" +
"This only happens once and will make all future discoveries instant.",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSecondaryContainer
)
}
}
}
}
// ═══════════════════════════════════════════════════════════
// CLUSTERING PROGRESS
// ═══════════════════════════════════════════════════════════
@Composable
private fun ClusteringProgressContent(
progress: Int,
total: Int,
message: String
) {
Column(
modifier = Modifier
.fillMaxSize()
.padding(24.dp),
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.Center
) {
CircularProgressIndicator(
modifier = Modifier.size(64.dp)
)
Spacer(modifier = Modifier.height(32.dp))
Text(
text = message,
style = MaterialTheme.typography.titleMedium,
textAlign = TextAlign.Center
)
Spacer(modifier = Modifier.height(16.dp))
if (total > 0) {
LinearProgressIndicator(
progress = { progress.toFloat() / total.toFloat() },
modifier = Modifier
.fillMaxWidth()
.height(8.dp)
)
Spacer(modifier = Modifier.height(8.dp))
Text(
text = "$progress / $total",
style = MaterialTheme.typography.bodyMedium,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
}
// ═══════════════════════════════════════════════════════════
// TRAINING PROGRESS
// ═══════════════════════════════════════════════════════════
@Composable
private fun TrainingProgressContent(
stage: String,
progress: Int,
total: Int
) {
Column(
modifier = Modifier
.fillMaxSize()
.padding(24.dp),
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.Center
) {
CircularProgressIndicator(
modifier = Modifier.size(64.dp)
)
Spacer(modifier = Modifier.height(32.dp))
Text(
text = stage,
style = MaterialTheme.typography.titleMedium,
textAlign = TextAlign.Center
)
if (total > 0) {
Spacer(modifier = Modifier.height(16.dp))
LinearProgressIndicator(
progress = { progress.toFloat() / total.toFloat() },
modifier = Modifier
.fillMaxWidth()
.height(8.dp)
)
Spacer(modifier = Modifier.height(8.dp))
Text(
text = "$progress / $total",
style = MaterialTheme.typography.bodyMedium,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
}
// ═══════════════════════════════════════════════════════════
// REFINEMENT NEEDED
// ═══════════════════════════════════════════════════════════
@Composable
private fun RefinementNeededContent(
recommendation: com.placeholder.sherpai2.domain.clustering.RefinementRecommendation,
currentIteration: Int,
onRefine: () -> Unit,
onSkip: () -> Unit
) {
Column(
modifier = Modifier
.fillMaxSize()
.padding(24.dp),
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.Center
) {
Icon(
imageVector = Icons.Default.Person,
contentDescription = null,
modifier = Modifier.size(80.dp),
tint = MaterialTheme.colorScheme.primary
)
Spacer(modifier = Modifier.height(24.dp))
Text(
text = "Refinement Recommended",
style = MaterialTheme.typography.headlineMedium,
fontWeight = FontWeight.Bold
)
Spacer(modifier = Modifier.height(16.dp))
Card(
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.errorContainer
)
) {
Column(
modifier = Modifier.padding(16.dp)
) {
Text(
text = recommendation.reason,
style = MaterialTheme.typography.bodyMedium,
color = MaterialTheme.colorScheme.onErrorContainer
)
}
}
Spacer(modifier = Modifier.height(16.dp))
Text(
text = "Iteration: $currentIteration",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
Spacer(modifier = Modifier.height(32.dp))
Row(
modifier = Modifier.fillMaxWidth(),
horizontalArrangement = Arrangement.spacedBy(12.dp)
) {
OutlinedButton(
onClick = onSkip,
modifier = Modifier.weight(1f)
) {
Text("Skip")
}
Button(
onClick = onRefine,
modifier = Modifier.weight(1f)
) {
Text("Refine Cluster")
}
}
}
}
// ═══════════════════════════════════════════════════════════
// REFINING PROGRESS
// ═══════════════════════════════════════════════════════════
@Composable
private fun RefiningProgressContent(
iteration: Int,
message: String
) {
Column(
modifier = Modifier
.fillMaxSize()
.padding(24.dp),
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.Center
) {
CircularProgressIndicator(
modifier = Modifier.size(64.dp)
)
Spacer(modifier = Modifier.height(32.dp))
Text(
text = "Refining Cluster",
style = MaterialTheme.typography.titleLarge,
fontWeight = FontWeight.Bold
)
Spacer(modifier = Modifier.height(16.dp))
Text(
text = message,
style = MaterialTheme.typography.bodyMedium,
textAlign = TextAlign.Center,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
Spacer(modifier = Modifier.height(8.dp))
Text(
text = "Iteration $iteration",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
// ═══════════════════════════════════════════════════════════
// LOADING CONTENT
// ═══════════════════════════════════════════════════════════
@Composable
private fun LoadingContent(message: String) {
Column(
modifier = Modifier.fillMaxSize(),
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.Center
) {
CircularProgressIndicator()
Spacer(modifier = Modifier.height(16.dp))
Text(text = message)
}
}
// ═══════════════════════════════════════════════════════════
// COMPLETE STATE
// ═══════════════════════════════════════════════════════════
@Composable
private fun CompleteStateContent(
message: String,
onDone: () -> Unit,
onDiscoverMore: () -> Unit
) {
Column(
modifier = Modifier
.fillMaxSize()
.padding(24.dp),
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.Center
) {
Text(
text = "🎉",
style = MaterialTheme.typography.displayLarge
)
Spacer(modifier = Modifier.height(24.dp))
Text(
text = "Success!",
style = MaterialTheme.typography.headlineMedium,
fontWeight = FontWeight.Bold
)
Spacer(modifier = Modifier.height(16.dp))
Text(
text = message,
style = MaterialTheme.typography.bodyLarge,
textAlign = TextAlign.Center,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
Spacer(modifier = Modifier.height(32.dp))
Button(
onClick = onDone,
modifier = Modifier.fillMaxWidth()
) {
Text("Done")
}
Spacer(modifier = Modifier.height(12.dp))
OutlinedButton(
onClick = onDiscoverMore,
modifier = Modifier.fillMaxWidth()
) {
Icon(
imageVector = Icons.Default.Refresh,
contentDescription = null,
modifier = Modifier.size(20.dp)
)
Spacer(Modifier.width(8.dp))
Text("Discover More People")
}
}
}
// ═══════════════════════════════════════════════════════════
// ERROR STATE
// ═══════════════════════════════════════════════════════════
@Composable
private fun ErrorStateContent(
title: String,
message: String,
onRetry: () -> Unit,
onBack: () -> Unit
) {
Column(
modifier = Modifier
.fillMaxSize()
.padding(24.dp),
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.Center
) {
Text(
text = "⚠️",
style = MaterialTheme.typography.displayLarge
)
Spacer(modifier = Modifier.height(24.dp))
Text(
text = title,
style = MaterialTheme.typography.headlineMedium,
fontWeight = FontWeight.Bold
)
Spacer(modifier = Modifier.height(16.dp))
Text(
text = message,
style = MaterialTheme.typography.bodyLarge,
textAlign = TextAlign.Center,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
Spacer(modifier = Modifier.height(32.dp))
Row(
modifier = Modifier.fillMaxWidth(),
horizontalArrangement = Arrangement.spacedBy(12.dp)
) {
OutlinedButton(
onClick = onBack,
modifier = Modifier.weight(1f)
) {
Text("Back")
}
Button(
onClick = onRetry,
modifier = Modifier.weight(1f)
) {
Text("Retry")
}
}
}
}

View File

@@ -0,0 +1,523 @@
package com.placeholder.sherpai2.ui.discover
import android.content.Context
import androidx.lifecycle.ViewModel
import androidx.lifecycle.viewModelScope
import androidx.work.*
import com.placeholder.sherpai2.data.local.dao.FaceCacheDao
import com.placeholder.sherpai2.data.local.entity.FeedbackType
import com.placeholder.sherpai2.domain.clustering.*
import com.placeholder.sherpai2.domain.training.ClusterTrainingService
import com.placeholder.sherpai2.domain.validation.ValidationScanResult
import com.placeholder.sherpai2.domain.validation.ValidationScanService
import com.placeholder.sherpai2.workers.CachePopulationWorker
import dagger.hilt.android.lifecycle.HiltViewModel
import dagger.hilt.android.qualifiers.ApplicationContext
import kotlinx.coroutines.flow.MutableStateFlow
import kotlinx.coroutines.flow.StateFlow
import kotlinx.coroutines.flow.asStateFlow
import kotlinx.coroutines.launch
import javax.inject.Inject
@HiltViewModel
class DiscoverPeopleViewModel @Inject constructor(
@ApplicationContext private val context: Context,
private val clusteringService: FaceClusteringService,
private val trainingService: ClusterTrainingService,
private val validationService: ValidationScanService,
private val refinementService: ClusterRefinementService,
private val faceCacheDao: FaceCacheDao
) : ViewModel() {
private val _uiState = MutableStateFlow<DiscoverUiState>(DiscoverUiState.Idle)
val uiState: StateFlow<DiscoverUiState> = _uiState.asStateFlow()
private val namedClusterIds = mutableSetOf<Int>()
private var currentIterationCount = 0
// NEW: Store settings for use after cache population
private var lastUsedSettings: DiscoverySettings = DiscoverySettings.DEFAULT
private val workManager = WorkManager.getInstance(context)
private var cacheWorkRequestId: java.util.UUID? = null
/**
* ENHANCED: Check cache before starting Discovery (with settings support)
*/
fun startDiscovery(settings: DiscoverySettings = DiscoverySettings.DEFAULT) {
lastUsedSettings = settings // Store for later use
// LOG SETTINGS
android.util.Log.d("DiscoverVM", "═══════════════════════════════════════")
android.util.Log.d("DiscoverVM", "🎛️ DISCOVERY SETTINGS")
android.util.Log.d("DiscoverVM", "═══════════════════════════════════════")
android.util.Log.d("DiscoverVM", "Min Face Size: ${settings.minFaceSize} (${(settings.minFaceSize * 100).toInt()}%)")
android.util.Log.d("DiscoverVM", "Min Quality: ${settings.minQuality} (${(settings.minQuality * 100).toInt()}%)")
android.util.Log.d("DiscoverVM", "Epsilon: ${settings.epsilon}")
android.util.Log.d("DiscoverVM", "Is Default: ${settings == DiscoverySettings.DEFAULT}")
android.util.Log.d("DiscoverVM", "═══════════════════════════════════════")
viewModelScope.launch {
try {
namedClusterIds.clear()
currentIterationCount = 0
// Check cache status
val cacheStats = faceCacheDao.getCacheStats()
android.util.Log.d("DiscoverVM", "Cache check: totalFaces=${cacheStats.totalFaces}")
if (cacheStats.totalFaces == 0) {
// Cache empty - need to build it first
android.util.Log.d("DiscoverVM", "Cache empty, starting cache population")
_uiState.value = DiscoverUiState.BuildingCache(
progress = 0,
total = 100,
message = "First-time setup: Building face cache...\n\nThis is a one-time process that will take 5-10 minutes."
)
startCachePopulation()
} else {
android.util.Log.d("DiscoverVM", "Cache exists (${cacheStats.totalFaces} faces), proceeding to Discovery")
// Cache exists - proceed to Discovery
_uiState.value = DiscoverUiState.Clustering(0, 100, "Starting discovery...")
executeDiscovery()
}
} catch (e: Exception) {
android.util.Log.e("DiscoverVM", "Error checking cache", e)
_uiState.value = DiscoverUiState.Error(
"Failed to check cache: ${e.message}"
)
}
}
}
/**
* Start cache population worker
*/
private fun startCachePopulation() {
viewModelScope.launch {
android.util.Log.d("DiscoverVM", "Enqueuing CachePopulationWorker")
val workRequest = OneTimeWorkRequestBuilder<CachePopulationWorker>()
.setConstraints(
Constraints.Builder()
.setRequiresCharging(false)
.setRequiresBatteryNotLow(false)
.build()
)
.build()
cacheWorkRequestId = workRequest.id
// Enqueue work
workManager.enqueueUniqueWork(
CachePopulationWorker.WORK_NAME,
ExistingWorkPolicy.REPLACE,
workRequest
)
// Observe progress
workManager.getWorkInfoByIdLiveData(workRequest.id).observeForever { workInfo ->
android.util.Log.d("DiscoverVM", "Worker state: ${workInfo?.state}")
when (workInfo?.state) {
WorkInfo.State.RUNNING -> {
val current = workInfo.progress.getInt(
CachePopulationWorker.KEY_PROGRESS_CURRENT,
0
)
val total = workInfo.progress.getInt(
CachePopulationWorker.KEY_PROGRESS_TOTAL,
100
)
_uiState.value = DiscoverUiState.BuildingCache(
progress = current,
total = total,
message = "Building face cache...\n\nAnalyzing $current of $total photos\n\nThis improves future Discovery performance by 95%!"
)
}
WorkInfo.State.SUCCEEDED -> {
val cachedCount = workInfo.outputData.getInt(
CachePopulationWorker.KEY_CACHED_COUNT,
0
)
android.util.Log.d("DiscoverVM", "Cache population complete: $cachedCount faces")
_uiState.value = DiscoverUiState.BuildingCache(
progress = 100,
total = 100,
message = "Cache complete! Found $cachedCount faces.\n\nStarting Discovery now..."
)
// Automatically start Discovery after cache is ready
viewModelScope.launch {
kotlinx.coroutines.delay(1000)
_uiState.value = DiscoverUiState.Clustering(0, 100, "Starting discovery...")
executeDiscovery()
}
}
WorkInfo.State.FAILED -> {
val error = workInfo.outputData.getString("error")
android.util.Log.e("DiscoverVM", "Cache population failed: $error")
_uiState.value = DiscoverUiState.Error(
"Cache building failed: ${error ?: "Unknown error"}\n\n" +
"Discovery will use slower full-scan mode.\n\n" +
"You can retry cache building later."
)
}
else -> {
// ENQUEUED, BLOCKED, CANCELLED
}
}
}
}
}
/**
* Execute the actual Discovery clustering (with settings support)
*/
private suspend fun executeDiscovery() {
try {
// LOG WHICH PATH WE'RE TAKING
android.util.Log.d("DiscoverVM", "═══════════════════════════════════════")
android.util.Log.d("DiscoverVM", "🚀 EXECUTING DISCOVERY")
android.util.Log.d("DiscoverVM", "═══════════════════════════════════════")
// Use discoverPeopleWithSettings if settings are non-default
val result = if (lastUsedSettings == DiscoverySettings.DEFAULT) {
android.util.Log.d("DiscoverVM", "Using DEFAULT settings path")
android.util.Log.d("DiscoverVM", "Calling: clusteringService.discoverPeople()")
// Use regular method for default settings
clusteringService.discoverPeople(
strategy = ClusteringStrategy.PREMIUM_SOLO_ONLY,
onProgress = { current: Int, total: Int, message: String ->
_uiState.value = DiscoverUiState.Clustering(current, total, message)
}
)
} else {
android.util.Log.d("DiscoverVM", "Using CUSTOM settings path")
android.util.Log.d("DiscoverVM", "Settings: minFaceSize=${lastUsedSettings.minFaceSize}, minQuality=${lastUsedSettings.minQuality}, epsilon=${lastUsedSettings.epsilon}")
android.util.Log.d("DiscoverVM", "Calling: clusteringService.discoverPeopleWithSettings()")
// Use settings-aware method
clusteringService.discoverPeopleWithSettings(
settings = lastUsedSettings,
onProgress = { current: Int, total: Int, message: String ->
_uiState.value = DiscoverUiState.Clustering(current, total, message)
}
)
}
android.util.Log.d("DiscoverVM", "Discovery complete: ${result.clusters.size} clusters found")
android.util.Log.d("DiscoverVM", "═══════════════════════════════════════")
if (result.errorMessage != null) {
_uiState.value = DiscoverUiState.Error(result.errorMessage)
return
}
if (result.clusters.isEmpty()) {
_uiState.value = DiscoverUiState.NoPeopleFound(
result.errorMessage
?: "No people clusters found.\n\nTry:\n• Adding more solo photos\n• Ensuring photos are clear\n• Having 6+ photos per person"
)
} else {
_uiState.value = DiscoverUiState.NamingReady(result)
}
} catch (e: Exception) {
android.util.Log.e("DiscoverVM", "Discovery failed", e)
_uiState.value = DiscoverUiState.Error(e.message ?: "Failed to discover people")
}
}
fun selectCluster(cluster: FaceCluster) {
val currentState = _uiState.value
if (currentState is DiscoverUiState.NamingReady) {
_uiState.value = DiscoverUiState.NamingCluster(
result = currentState.result,
selectedCluster = cluster,
suggestedSiblings = currentState.result.clusters.filter {
it.clusterId in cluster.potentialSiblings
}
)
}
}
fun confirmClusterName(
cluster: FaceCluster,
name: String,
dateOfBirth: Long?,
isChild: Boolean,
selectedSiblings: List<Int>
) {
viewModelScope.launch {
try {
val currentState = _uiState.value
if (currentState !is DiscoverUiState.NamingCluster) return@launch
_uiState.value = DiscoverUiState.AnalyzingCluster
_uiState.value = DiscoverUiState.Training(
stage = "Creating face model for $name...",
progress = 0,
total = cluster.faces.size
)
val personId = trainingService.trainFromCluster(
cluster = cluster,
name = name,
dateOfBirth = dateOfBirth,
isChild = isChild,
siblingClusterIds = selectedSiblings,
onProgress = { current: Int, total: Int, message: String ->
_uiState.value = DiscoverUiState.Training(message, current, total)
}
)
_uiState.value = DiscoverUiState.Training(
stage = "Running validation scan...",
progress = 0,
total = 100
)
val validationResult = validationService.performValidationScan(
personId = personId,
onProgress = { current: Int, total: Int ->
_uiState.value = DiscoverUiState.Training(
stage = "Validating model quality...",
progress = current,
total = total
)
}
)
_uiState.value = DiscoverUiState.ValidationPreview(
personId = personId,
personName = name,
cluster = cluster,
validationResult = validationResult
)
} catch (e: Exception) {
_uiState.value = DiscoverUiState.Error(e.message ?: "Failed to create person")
}
}
}
fun submitFeedback(
cluster: FaceCluster,
feedbackMap: Map<String, FeedbackType>
) {
viewModelScope.launch {
try {
val faceFeedbackMap = cluster.faces
.associateWith { face ->
feedbackMap[face.imageId] ?: FeedbackType.UNCERTAIN
}
val originalConfidences = cluster.faces.associateWith { it.confidence }
refinementService.storeFeedback(
cluster = cluster,
feedbackMap = faceFeedbackMap,
originalConfidences = originalConfidences
)
val recommendation = refinementService.shouldRefineCluster(cluster)
if (recommendation.shouldRefine) {
_uiState.value = DiscoverUiState.RefinementNeeded(
cluster = cluster,
recommendation = recommendation,
currentIteration = currentIterationCount
)
}
} catch (e: Exception) {
_uiState.value = DiscoverUiState.Error(
"Failed to process feedback: ${e.message}"
)
}
}
}
fun requestRefinement(cluster: FaceCluster) {
viewModelScope.launch {
try {
currentIterationCount++
_uiState.value = DiscoverUiState.Refining(
iteration = currentIterationCount,
message = "Removing incorrect faces and re-clustering..."
)
val refinementResult = refinementService.refineCluster(
cluster = cluster,
iterationNumber = currentIterationCount
)
if (!refinementResult.success || refinementResult.refinedCluster == null) {
_uiState.value = DiscoverUiState.Error(
refinementResult.errorMessage
?: "Failed to refine cluster. Please try manual training."
)
return@launch
}
val currentState = _uiState.value
if (currentState is DiscoverUiState.RefinementNeeded) {
confirmClusterName(
cluster = refinementResult.refinedCluster,
name = currentState.cluster.representativeFaces.first().imageId,
dateOfBirth = null,
isChild = false,
selectedSiblings = emptyList()
)
}
} catch (e: Exception) {
_uiState.value = DiscoverUiState.Error(
"Refinement failed: ${e.message}"
)
}
}
}
fun approveValidationAndScan(personId: String, personName: String) {
viewModelScope.launch {
try {
_uiState.value = DiscoverUiState.Complete(
message = "Successfully created model for \"$personName\"!\n\n" +
"Full library scan has been queued in the background.\n\n" +
"${currentIterationCount} refinement iterations completed"
)
} catch (e: Exception) {
_uiState.value = DiscoverUiState.Error(e.message ?: "Failed to start library scan")
}
}
}
fun rejectValidationAndImprove() {
_uiState.value = DiscoverUiState.Error(
"Please add more training photos and try again.\n\n" +
"(Feature coming: ability to add photos to existing model)"
)
}
fun cancelNaming() {
val currentState = _uiState.value
if (currentState is DiscoverUiState.NamingCluster) {
_uiState.value = DiscoverUiState.NamingReady(result = currentState.result)
}
}
fun reset() {
cacheWorkRequestId?.let { workId ->
workManager.cancelWorkById(workId)
}
_uiState.value = DiscoverUiState.Idle
namedClusterIds.clear()
currentIterationCount = 0
}
/**
* Retry discovery (returns to idle state)
*/
fun retryDiscovery() {
_uiState.value = DiscoverUiState.Idle
}
/**
* Accept validation results and finish
*/
fun acceptValidationAndFinish() {
_uiState.value = DiscoverUiState.Complete(
"Person created successfully!"
)
}
/**
* Skip refinement and finish
*/
fun skipRefinement() {
_uiState.value = DiscoverUiState.Complete(
"Person created successfully!"
)
}
}
/**
* UI States - ENHANCED with BuildingCache state
*/
sealed class DiscoverUiState {
object Idle : DiscoverUiState()
data class BuildingCache(
val progress: Int,
val total: Int,
val message: String
) : DiscoverUiState()
data class Clustering(
val progress: Int,
val total: Int,
val message: String
) : DiscoverUiState()
data class NamingReady(
val result: ClusteringResult
) : DiscoverUiState()
data class NamingCluster(
val result: ClusteringResult,
val selectedCluster: FaceCluster,
val suggestedSiblings: List<FaceCluster>
) : DiscoverUiState()
object AnalyzingCluster : DiscoverUiState()
data class Training(
val stage: String,
val progress: Int,
val total: Int
) : DiscoverUiState()
data class ValidationPreview(
val personId: String,
val personName: String,
val cluster: FaceCluster,
val validationResult: ValidationScanResult
) : DiscoverUiState()
data class RefinementNeeded(
val cluster: FaceCluster,
val recommendation: RefinementRecommendation,
val currentIteration: Int
) : DiscoverUiState()
data class Refining(
val iteration: Int,
val message: String
) : DiscoverUiState()
data class Complete(
val message: String
) : DiscoverUiState()
data class NoPeopleFound(
val message: String
) : DiscoverUiState()
data class Error(
val message: String
) : DiscoverUiState()
}

View File

@@ -0,0 +1,309 @@
package com.placeholder.sherpai2.ui.discover
import androidx.compose.animation.AnimatedVisibility
import androidx.compose.animation.expandVertically
import androidx.compose.animation.shrinkVertically
import androidx.compose.foundation.layout.*
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.filled.*
import androidx.compose.material3.*
import androidx.compose.runtime.*
import androidx.compose.ui.Alignment
import androidx.compose.ui.Modifier
import androidx.compose.ui.text.font.FontWeight
import androidx.compose.ui.unit.dp
/**
* DiscoverySettingsCard - Quality control sliders
*
* Allows tuning without dropping quality:
* - Face size threshold (bigger = more strict)
* - Quality score threshold (higher = better faces)
* - Clustering strictness (tighter = more clusters)
*/
@Composable
fun DiscoverySettingsCard(
settings: DiscoverySettings,
onSettingsChange: (DiscoverySettings) -> Unit,
modifier: Modifier = Modifier
) {
var expanded by remember { mutableStateOf(false) }
Card(
modifier = modifier.fillMaxWidth(),
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.surfaceVariant
)
) {
Column(
modifier = Modifier.fillMaxWidth()
) {
// Header - Always visible
Row(
modifier = Modifier
.fillMaxWidth()
.padding(16.dp),
horizontalArrangement = Arrangement.SpaceBetween,
verticalAlignment = Alignment.CenterVertically
) {
Row(
horizontalArrangement = Arrangement.spacedBy(8.dp),
verticalAlignment = Alignment.CenterVertically
) {
Icon(
imageVector = Icons.Default.Tune,
contentDescription = null,
tint = MaterialTheme.colorScheme.primary
)
Column {
Text(
text = "Quality Settings",
style = MaterialTheme.typography.titleMedium,
fontWeight = FontWeight.Bold
)
Text(
text = if (expanded) "Hide settings" else "Tap to adjust",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
IconButton(onClick = { expanded = !expanded }) {
Icon(
imageVector = if (expanded) Icons.Default.ExpandLess
else Icons.Default.ExpandMore,
contentDescription = if (expanded) "Collapse" else "Expand"
)
}
}
// Settings - Expandable
AnimatedVisibility(
visible = expanded,
enter = expandVertically(),
exit = shrinkVertically()
) {
Column(
modifier = Modifier
.fillMaxWidth()
.padding(horizontal = 16.dp)
.padding(bottom = 16.dp),
verticalArrangement = Arrangement.spacedBy(20.dp)
) {
HorizontalDivider()
// Face Size Slider
QualitySlider(
title = "Minimum Face Size",
description = "Smaller = more faces, larger = higher quality",
currentValue = "${(settings.minFaceSize * 100).toInt()}%",
value = settings.minFaceSize,
onValueChange = { onSettingsChange(settings.copy(minFaceSize = it)) },
valueRange = 0.02f..0.08f,
icon = Icons.Default.ZoomIn
)
// Quality Score Slider
QualitySlider(
title = "Quality Threshold",
description = "Lower = more faces, higher = better quality",
currentValue = "${(settings.minQuality * 100).toInt()}%",
value = settings.minQuality,
onValueChange = { onSettingsChange(settings.copy(minQuality = it)) },
valueRange = 0.4f..0.8f,
icon = Icons.Default.HighQuality
)
// Clustering Strictness
QualitySlider(
title = "Clustering Strictness",
description = when {
settings.epsilon < 0.20f -> "Very strict (more clusters)"
settings.epsilon > 0.25f -> "Loose (fewer clusters)"
else -> "Balanced"
},
currentValue = when {
settings.epsilon < 0.20f -> "Strict"
settings.epsilon > 0.25f -> "Loose"
else -> "Normal"
},
value = settings.epsilon,
onValueChange = { onSettingsChange(settings.copy(epsilon = it)) },
valueRange = 0.16f..0.28f,
icon = Icons.Default.Category
)
HorizontalDivider()
// Info Card
InfoCard(
text = "These settings control face quality, not photo type. " +
"Group photos are included - we extract the best face from each."
)
// Preset Buttons
Row(
modifier = Modifier.fillMaxWidth(),
horizontalArrangement = Arrangement.spacedBy(8.dp)
) {
OutlinedButton(
onClick = { onSettingsChange(DiscoverySettings.STRICT) },
modifier = Modifier.weight(1f)
) {
Text("High Quality", style = MaterialTheme.typography.bodySmall)
}
Button(
onClick = { onSettingsChange(DiscoverySettings.DEFAULT) },
modifier = Modifier.weight(1f)
) {
Text("Balanced", style = MaterialTheme.typography.bodySmall)
}
OutlinedButton(
onClick = { onSettingsChange(DiscoverySettings.LOOSE) },
modifier = Modifier.weight(1f)
) {
Text("More Faces", style = MaterialTheme.typography.bodySmall)
}
}
}
}
}
}
}
/**
* Individual quality slider component
*/
@Composable
private fun QualitySlider(
title: String,
description: String,
currentValue: String,
value: Float,
onValueChange: (Float) -> Unit,
valueRange: ClosedFloatingPointRange<Float>,
icon: androidx.compose.ui.graphics.vector.ImageVector
) {
Column(
verticalArrangement = Arrangement.spacedBy(8.dp)
) {
// Header
Row(
modifier = Modifier.fillMaxWidth(),
horizontalArrangement = Arrangement.SpaceBetween,
verticalAlignment = Alignment.CenterVertically
) {
Row(
horizontalArrangement = Arrangement.spacedBy(8.dp),
verticalAlignment = Alignment.CenterVertically,
modifier = Modifier.weight(1f)
) {
Icon(
imageVector = icon,
contentDescription = null,
tint = MaterialTheme.colorScheme.primary,
modifier = Modifier.size(20.dp)
)
Text(
text = title,
style = MaterialTheme.typography.bodyMedium,
fontWeight = FontWeight.Medium
)
}
Surface(
shape = MaterialTheme.shapes.small,
color = MaterialTheme.colorScheme.primaryContainer
) {
Text(
text = currentValue,
modifier = Modifier.padding(horizontal = 12.dp, vertical = 4.dp),
style = MaterialTheme.typography.labelLarge,
color = MaterialTheme.colorScheme.onPrimaryContainer,
fontWeight = FontWeight.Bold
)
}
}
// Description
Text(
text = description,
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
// Slider
Slider(
value = value,
onValueChange = onValueChange,
valueRange = valueRange
)
}
}
/**
* Info card component
*/
@Composable
private fun InfoCard(text: String) {
Card(
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.secondaryContainer.copy(alpha = 0.5f)
)
) {
Row(
modifier = Modifier
.fillMaxWidth()
.padding(12.dp),
horizontalArrangement = Arrangement.spacedBy(8.dp),
verticalAlignment = Alignment.CenterVertically
) {
Icon(
imageVector = Icons.Default.Info,
contentDescription = null,
tint = MaterialTheme.colorScheme.onSecondaryContainer,
modifier = Modifier.size(18.dp)
)
Text(
text = text,
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSecondaryContainer
)
}
}
}
/**
* Discovery settings data class
*/
data class DiscoverySettings(
val minFaceSize: Float = 0.03f, // 3% of image (balanced)
val minQuality: Float = 0.6f, // 60% quality (good)
val epsilon: Float = 0.22f // DBSCAN threshold (balanced)
) {
companion object {
// Balanced - Default recommended settings
val DEFAULT = DiscoverySettings(
minFaceSize = 0.03f,
minQuality = 0.6f,
epsilon = 0.22f
)
// Strict - High quality, fewer faces
val STRICT = DiscoverySettings(
minFaceSize = 0.05f, // 5% of image
minQuality = 0.7f, // 70% quality
epsilon = 0.18f // Tight clustering
)
// Loose - More faces, lower quality threshold
val LOOSE = DiscoverySettings(
minFaceSize = 0.02f, // 2% of image
minQuality = 0.5f, // 50% quality
epsilon = 0.26f // Loose clustering
)
}
}

View File

@@ -0,0 +1,637 @@
package com.placeholder.sherpai2.ui.discover
import androidx.compose.foundation.background
import androidx.compose.foundation.border
import androidx.compose.foundation.clickable
import androidx.compose.foundation.layout.*
import androidx.compose.foundation.lazy.LazyRow
import androidx.compose.foundation.lazy.items
import androidx.compose.foundation.rememberScrollState
import androidx.compose.foundation.shape.CircleShape
import androidx.compose.foundation.shape.RoundedCornerShape
import androidx.compose.foundation.text.KeyboardActions
import androidx.compose.foundation.text.KeyboardOptions
import androidx.compose.foundation.verticalScroll
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.filled.*
import androidx.compose.material3.*
import androidx.compose.runtime.*
import androidx.compose.ui.Alignment
import androidx.compose.ui.Modifier
import androidx.compose.ui.draw.clip
import androidx.compose.ui.graphics.Color
import androidx.compose.ui.layout.ContentScale
import androidx.compose.ui.platform.LocalSoftwareKeyboardController
import androidx.compose.ui.text.font.FontWeight
import androidx.compose.ui.text.input.ImeAction
import androidx.compose.ui.text.input.KeyboardCapitalization
import androidx.compose.ui.text.input.KeyboardType
import androidx.compose.ui.text.style.TextAlign
import androidx.compose.ui.unit.dp
import androidx.compose.ui.window.Dialog
import coil.compose.AsyncImage
import com.placeholder.sherpai2.domain.clustering.ClusterQualityAnalyzer
import com.placeholder.sherpai2.domain.clustering.ClusterQualityTier
import com.placeholder.sherpai2.domain.clustering.FaceCluster
import java.text.SimpleDateFormat
import java.util.*
/**
* NamingDialog - ENHANCED with Retry Button
*
* NEW FEATURE:
* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
* - Added onRetry parameter
* - Shows retry button for poor quality clusters
* - Also shows secondary retry option for good clusters
*
* All existing features preserved:
* - Name input with validation
* - Child toggle with date of birth picker
* - Sibling cluster selection
* - Quality warnings display
* - Preview of representative faces
*/
@OptIn(ExperimentalMaterial3Api::class)
@Composable
fun NamingDialog(
cluster: FaceCluster,
suggestedSiblings: List<FaceCluster>,
onConfirm: (name: String, dateOfBirth: Long?, isChild: Boolean, selectedSiblings: List<Int>) -> Unit,
onRetry: () -> Unit = {}, // NEW: Retry with different settings
onDismiss: () -> Unit,
qualityAnalyzer: ClusterQualityAnalyzer = remember { ClusterQualityAnalyzer() }
) {
var name by remember { mutableStateOf("") }
var isChild by remember { mutableStateOf(false) }
var showDatePicker by remember { mutableStateOf(false) }
var dateOfBirth by remember { mutableStateOf<Long?>(null) }
var selectedSiblingIds by remember { mutableStateOf(setOf<Int>()) }
// Analyze cluster quality
val qualityResult = remember(cluster) {
qualityAnalyzer.analyzeCluster(cluster)
}
val keyboardController = LocalSoftwareKeyboardController.current
val dateFormatter = remember { SimpleDateFormat("MMM dd, yyyy", Locale.getDefault()) }
Dialog(onDismissRequest = onDismiss) {
Card(
modifier = Modifier
.fillMaxWidth()
.fillMaxHeight(0.9f),
shape = RoundedCornerShape(16.dp),
elevation = CardDefaults.cardElevation(defaultElevation = 8.dp)
) {
Column(
modifier = Modifier
.fillMaxSize()
.verticalScroll(rememberScrollState())
) {
// Header
Surface(
color = MaterialTheme.colorScheme.primaryContainer
) {
Row(
modifier = Modifier
.fillMaxWidth()
.padding(16.dp),
horizontalArrangement = Arrangement.SpaceBetween,
verticalAlignment = Alignment.CenterVertically
) {
Text(
text = "Name This Person",
style = MaterialTheme.typography.headlineMedium,
fontWeight = FontWeight.Bold,
color = MaterialTheme.colorScheme.onPrimaryContainer
)
IconButton(onClick = onDismiss) {
Icon(
imageVector = Icons.Default.Close,
contentDescription = "Close",
tint = MaterialTheme.colorScheme.onPrimaryContainer
)
}
}
}
Column(
modifier = Modifier.padding(16.dp)
) {
// ════════════════════════════════════════
// NEW: Poor Quality Warning with Retry
// ════════════════════════════════════════
if (qualityResult.qualityTier == ClusterQualityTier.POOR) {
Card(
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.errorContainer
),
modifier = Modifier.fillMaxWidth()
) {
Column(
modifier = Modifier.padding(16.dp),
verticalArrangement = Arrangement.spacedBy(12.dp)
) {
Row(
horizontalArrangement = Arrangement.spacedBy(8.dp),
verticalAlignment = Alignment.CenterVertically
) {
Icon(
Icons.Default.Warning,
contentDescription = null,
tint = MaterialTheme.colorScheme.onErrorContainer
)
Text(
text = "Poor Quality Cluster",
style = MaterialTheme.typography.titleMedium,
fontWeight = FontWeight.Bold,
color = MaterialTheme.colorScheme.onErrorContainer
)
}
Text(
text = "This cluster doesn't meet quality requirements:",
style = MaterialTheme.typography.bodyMedium,
color = MaterialTheme.colorScheme.onErrorContainer
)
Column(verticalArrangement = Arrangement.spacedBy(4.dp)) {
qualityResult.warnings.forEach { warning ->
Row(horizontalArrangement = Arrangement.spacedBy(8.dp)) {
Text("", color = MaterialTheme.colorScheme.onErrorContainer)
Text(
warning,
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onErrorContainer
)
}
}
}
HorizontalDivider(
color = MaterialTheme.colorScheme.onErrorContainer.copy(alpha = 0.3f)
)
Button(
onClick = onRetry,
modifier = Modifier.fillMaxWidth(),
colors = ButtonDefaults.buttonColors(
containerColor = MaterialTheme.colorScheme.error,
contentColor = MaterialTheme.colorScheme.onError
)
) {
Icon(Icons.Default.Refresh, contentDescription = null)
Spacer(Modifier.width(8.dp))
Text("Retry with Different Settings")
}
}
}
Spacer(modifier = Modifier.height(16.dp))
} else if (qualityResult.warnings.isNotEmpty()) {
// Minor warnings for good/excellent clusters
Card(
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.secondaryContainer.copy(alpha = 0.5f)
)
) {
Column(
modifier = Modifier.padding(12.dp),
verticalArrangement = Arrangement.spacedBy(4.dp)
) {
qualityResult.warnings.take(3).forEach { warning ->
Row(
horizontalArrangement = Arrangement.spacedBy(8.dp),
verticalAlignment = Alignment.Top
) {
Icon(
Icons.Default.Info,
contentDescription = null,
modifier = Modifier.size(16.dp),
tint = MaterialTheme.colorScheme.onSecondaryContainer
)
Text(
warning,
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSecondaryContainer
)
}
}
}
}
Spacer(modifier = Modifier.height(16.dp))
}
// Quality badge
Surface(
color = when (qualityResult.qualityTier) {
ClusterQualityTier.EXCELLENT -> Color(0xFF1B5E20)
ClusterQualityTier.GOOD -> Color(0xFF2E7D32)
ClusterQualityTier.POOR -> Color(0xFFD32F2F)
},
shape = RoundedCornerShape(8.dp)
) {
Row(
modifier = Modifier.padding(horizontal = 12.dp, vertical = 6.dp),
horizontalArrangement = Arrangement.spacedBy(4.dp),
verticalAlignment = Alignment.CenterVertically
) {
Icon(
imageVector = when (qualityResult.qualityTier) {
ClusterQualityTier.EXCELLENT, ClusterQualityTier.GOOD -> Icons.Default.Check
ClusterQualityTier.POOR -> Icons.Default.Warning
},
contentDescription = null,
tint = Color.White,
modifier = Modifier.size(16.dp)
)
Text(
text = "${qualityResult.qualityTier.name} Quality",
style = MaterialTheme.typography.labelMedium,
color = Color.White,
fontWeight = FontWeight.SemiBold
)
}
}
Spacer(modifier = Modifier.height(16.dp))
// Stats
Row(
modifier = Modifier.fillMaxWidth(),
horizontalArrangement = Arrangement.SpaceEvenly
) {
Column(horizontalAlignment = Alignment.CenterHorizontally) {
Text(
text = "${qualityResult.soloPhotoCount}",
style = MaterialTheme.typography.headlineMedium,
fontWeight = FontWeight.Bold
)
Text(
text = "Solo Photos",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
Column(horizontalAlignment = Alignment.CenterHorizontally) {
Text(
text = "${qualityResult.cleanFaceCount}",
style = MaterialTheme.typography.headlineMedium,
fontWeight = FontWeight.Bold
)
Text(
text = "Clean Faces",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
Column(horizontalAlignment = Alignment.CenterHorizontally) {
Text(
text = "${(qualityResult.qualityScore * 100).toInt()}%",
style = MaterialTheme.typography.headlineMedium,
fontWeight = FontWeight.Bold
)
Text(
text = "Quality",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
Spacer(modifier = Modifier.height(24.dp))
// Representative faces preview
if (cluster.representativeFaces.isNotEmpty()) {
Text(
text = "Representative Faces",
style = MaterialTheme.typography.titleSmall,
fontWeight = FontWeight.SemiBold,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
Spacer(modifier = Modifier.height(8.dp))
LazyRow(
horizontalArrangement = Arrangement.spacedBy(8.dp)
) {
items(cluster.representativeFaces.take(6)) { face ->
AsyncImage(
model = android.net.Uri.parse(face.imageUri),
contentDescription = null,
modifier = Modifier
.size(80.dp)
.clip(RoundedCornerShape(8.dp))
.border(
2.dp,
MaterialTheme.colorScheme.outline.copy(alpha = 0.2f),
RoundedCornerShape(8.dp)
),
contentScale = ContentScale.Crop
)
}
}
Spacer(modifier = Modifier.height(20.dp))
}
// Name input
OutlinedTextField(
value = name,
onValueChange = { name = it },
label = { Text("Name") },
placeholder = { Text("e.g., Emma") },
leadingIcon = {
Icon(
imageVector = Icons.Default.Person,
contentDescription = null
)
},
keyboardOptions = KeyboardOptions(
capitalization = KeyboardCapitalization.Words,
imeAction = ImeAction.Done
),
keyboardActions = KeyboardActions(
onDone = { keyboardController?.hide() }
),
singleLine = true,
modifier = Modifier.fillMaxWidth(),
enabled = qualityResult.canTrain
)
Spacer(modifier = Modifier.height(16.dp))
// Child toggle
Surface(
modifier = Modifier.fillMaxWidth(),
color = if (isChild) MaterialTheme.colorScheme.primaryContainer
else MaterialTheme.colorScheme.surfaceVariant,
shape = RoundedCornerShape(12.dp)
) {
Row(
modifier = Modifier
.fillMaxWidth()
.clickable(enabled = qualityResult.canTrain) { isChild = !isChild }
.padding(16.dp),
verticalAlignment = Alignment.CenterVertically,
horizontalArrangement = Arrangement.SpaceBetween
) {
Row(
verticalAlignment = Alignment.CenterVertically
) {
Icon(
imageVector = Icons.Default.Face,
contentDescription = null,
tint = if (isChild) MaterialTheme.colorScheme.onPrimaryContainer
else MaterialTheme.colorScheme.onSurfaceVariant
)
Spacer(modifier = Modifier.width(12.dp))
Column {
Text(
text = "This is a child",
style = MaterialTheme.typography.bodyLarge,
fontWeight = FontWeight.Medium,
color = if (isChild) MaterialTheme.colorScheme.onPrimaryContainer
else MaterialTheme.colorScheme.onSurfaceVariant
)
Text(
text = "For age-appropriate filtering",
style = MaterialTheme.typography.bodySmall,
color = if (isChild) MaterialTheme.colorScheme.onPrimaryContainer.copy(alpha = 0.7f)
else MaterialTheme.colorScheme.onSurfaceVariant.copy(alpha = 0.7f)
)
}
}
Switch(
checked = isChild,
onCheckedChange = null, // Handled by row click
enabled = qualityResult.canTrain
)
}
}
// Date of birth (if child)
if (isChild) {
Spacer(modifier = Modifier.height(12.dp))
OutlinedButton(
onClick = { showDatePicker = true },
modifier = Modifier.fillMaxWidth(),
enabled = qualityResult.canTrain
) {
Icon(
imageVector = Icons.Default.DateRange,
contentDescription = null
)
Spacer(modifier = Modifier.width(8.dp))
Text(
text = dateOfBirth?.let { dateFormatter.format(Date(it)) }
?: "Set date of birth (optional)"
)
}
}
// Sibling selection
if (suggestedSiblings.isNotEmpty()) {
Spacer(modifier = Modifier.height(20.dp))
Text(
text = "Appears with",
style = MaterialTheme.typography.titleMedium,
fontWeight = FontWeight.SemiBold
)
Text(
text = "Select siblings or family members",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
Spacer(modifier = Modifier.height(8.dp))
suggestedSiblings.forEach { sibling ->
SiblingSelectionItem(
cluster = sibling,
selected = sibling.clusterId in selectedSiblingIds,
onToggle = {
selectedSiblingIds = if (sibling.clusterId in selectedSiblingIds) {
selectedSiblingIds - sibling.clusterId
} else {
selectedSiblingIds + sibling.clusterId
}
},
enabled = qualityResult.canTrain
)
Spacer(modifier = Modifier.height(8.dp))
}
}
Spacer(modifier = Modifier.height(24.dp))
// ════════════════════════════════════════
// Action buttons
// ════════════════════════════════════════
if (qualityResult.qualityTier == ClusterQualityTier.POOR) {
// Poor quality - Cancel only (retry button is above)
OutlinedButton(
onClick = onDismiss,
modifier = Modifier.fillMaxWidth()
) {
Text("Cancel")
}
} else {
// Good quality - Normal flow
Row(
modifier = Modifier.fillMaxWidth(),
horizontalArrangement = Arrangement.spacedBy(12.dp)
) {
OutlinedButton(
onClick = onDismiss,
modifier = Modifier.weight(1f)
) {
Text("Cancel")
}
Button(
onClick = {
if (name.isNotBlank()) {
onConfirm(
name.trim(),
dateOfBirth,
isChild,
selectedSiblingIds.toList()
)
}
},
modifier = Modifier.weight(1f),
enabled = name.isNotBlank() && qualityResult.canTrain
) {
Icon(
imageVector = Icons.Default.Check,
contentDescription = null,
modifier = Modifier.size(20.dp)
)
Spacer(modifier = Modifier.width(8.dp))
Text("Create Model")
}
}
// ════════════════════════════════════════
// NEW: Secondary retry option
// ════════════════════════════════════════
Spacer(modifier = Modifier.height(8.dp))
TextButton(
onClick = onRetry,
modifier = Modifier.fillMaxWidth()
) {
Icon(
Icons.Default.Refresh,
contentDescription = null,
modifier = Modifier.size(16.dp)
)
Spacer(Modifier.width(4.dp))
Text(
"Try again with different settings",
style = MaterialTheme.typography.bodySmall
)
}
}
}
}
}
}
// Date picker dialog
if (showDatePicker) {
val datePickerState = rememberDatePickerState()
DatePickerDialog(
onDismissRequest = { showDatePicker = false },
confirmButton = {
TextButton(
onClick = {
dateOfBirth = datePickerState.selectedDateMillis
showDatePicker = false
}
) {
Text("OK")
}
},
dismissButton = {
TextButton(onClick = { showDatePicker = false }) {
Text("Cancel")
}
}
) {
DatePicker(state = datePickerState)
}
}
}
@Composable
private fun SiblingSelectionItem(
cluster: FaceCluster,
selected: Boolean,
onToggle: () -> Unit,
enabled: Boolean = true
) {
Surface(
modifier = Modifier.fillMaxWidth(),
color = if (selected) MaterialTheme.colorScheme.primaryContainer
else MaterialTheme.colorScheme.surfaceVariant,
shape = RoundedCornerShape(8.dp)
) {
Row(
modifier = Modifier
.fillMaxWidth()
.clickable(enabled = enabled) { onToggle() }
.padding(12.dp),
verticalAlignment = Alignment.CenterVertically,
horizontalArrangement = Arrangement.SpaceBetween
) {
Row(
verticalAlignment = Alignment.CenterVertically,
horizontalArrangement = Arrangement.spacedBy(8.dp)
) {
// Face preview
if (cluster.representativeFaces.isNotEmpty()) {
AsyncImage(
model = android.net.Uri.parse(cluster.representativeFaces.first().imageUri),
contentDescription = null,
modifier = Modifier
.size(48.dp)
.clip(CircleShape)
.border(2.dp, MaterialTheme.colorScheme.outline.copy(alpha = 0.2f), CircleShape),
contentScale = ContentScale.Crop
)
}
Column {
Text(
text = "Person ${cluster.clusterId + 1}",
style = MaterialTheme.typography.bodyMedium,
fontWeight = FontWeight.Medium
)
Text(
text = "${cluster.photoCount} photos",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
Checkbox(
checked = selected,
onCheckedChange = null, // Handled by row click
enabled = enabled
)
}
}
}

View File

@@ -0,0 +1,353 @@
package com.placeholder.sherpai2.ui.discover
import androidx.compose.foundation.layout.*
import androidx.compose.foundation.text.KeyboardOptions
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.filled.*
import androidx.compose.material3.*
import androidx.compose.runtime.*
import androidx.compose.ui.Alignment
import androidx.compose.ui.Modifier
import androidx.compose.ui.text.font.FontWeight
import androidx.compose.ui.text.input.KeyboardType
import androidx.compose.ui.unit.dp
import androidx.compose.ui.window.Dialog
import com.placeholder.sherpai2.domain.clustering.AnnotatedCluster
import com.placeholder.sherpai2.domain.clustering.ClusterQualityAnalyzer
import com.placeholder.sherpai2.domain.clustering.ClusterQualityResult
/**
* TemporalNamingDialog - ENHANCED with age input for temporal clustering
*
* NEW FEATURES:
* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
* ✅ Name field: "Emma"
* ✅ Age field: "2" (optional but recommended)
* ✅ Year display: "Photos from 2020"
* ✅ Auto-suggest: If year=2020 and DOB=2018 → Age=2
*
* NAMING PATTERNS:
* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
* Adults:
* - Name: "John Doe"
* - Age: (leave empty)
* - Result: Person "John Doe" with single model
*
* Children (with age):
* - Name: "Emma"
* - Age: "2"
* - Year: "2020"
* - Result: Person "Emma" with submodel "Emma_Age_2"
*
* Children (without age):
* - Name: "Emma"
* - Age: (empty)
* - Year: "2020"
* - Result: Person "Emma" with submodel "Emma_2020"
*/
@Composable
fun TemporalNamingDialog(
annotatedCluster: AnnotatedCluster,
onConfirm: (name: String, age: Int?, isChild: Boolean) -> Unit,
onDismiss: () -> Unit,
qualityAnalyzer: ClusterQualityAnalyzer
) {
var name by remember { mutableStateOf(annotatedCluster.suggestedName ?: "") }
var ageText by remember { mutableStateOf(annotatedCluster.suggestedAge?.toString() ?: "") }
var isChild by remember { mutableStateOf(annotatedCluster.suggestedAge != null) }
// Analyze cluster quality
val qualityResult = remember(annotatedCluster.cluster) {
qualityAnalyzer.analyzeCluster(annotatedCluster.cluster)
}
Dialog(onDismissRequest = onDismiss) {
Card(
modifier = Modifier
.fillMaxWidth()
.padding(16.dp)
) {
Column(
modifier = Modifier.padding(24.dp),
verticalArrangement = Arrangement.spacedBy(16.dp)
) {
// Header
Text(
text = "Name This Person",
style = MaterialTheme.typography.headlineSmall,
fontWeight = FontWeight.Bold
)
// Year badge
YearBadge(year = annotatedCluster.year)
HorizontalDivider()
// Quality warnings
QualityWarnings(qualityResult)
// Name field
OutlinedTextField(
value = name,
onValueChange = { name = it },
label = { Text("Name") },
placeholder = { Text("e.g., Emma") },
leadingIcon = {
Icon(Icons.Default.Person, contentDescription = null)
},
modifier = Modifier.fillMaxWidth(),
singleLine = true
)
// Child checkbox
Row(
modifier = Modifier.fillMaxWidth(),
verticalAlignment = Alignment.CenterVertically
) {
Checkbox(
checked = isChild,
onCheckedChange = { isChild = it }
)
Spacer(modifier = Modifier.width(8.dp))
Column {
Text(
text = "This is a child",
style = MaterialTheme.typography.bodyMedium
)
Text(
text = "Enable age-specific models",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
// Age field (only if child)
if (isChild) {
OutlinedTextField(
value = ageText,
onValueChange = {
// Only allow numbers
if (it.isEmpty() || it.all { c -> c.isDigit() }) {
ageText = it
}
},
label = { Text("Age in ${annotatedCluster.year}") },
placeholder = { Text("e.g., 2") },
leadingIcon = {
Icon(Icons.Default.DateRange, contentDescription = null)
},
modifier = Modifier.fillMaxWidth(),
singleLine = true,
keyboardOptions = KeyboardOptions(keyboardType = KeyboardType.Number),
supportingText = {
Text("Optional: Helps create age-specific models")
}
)
// Model name preview
if (name.isNotBlank()) {
Card(
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.primaryContainer
)
) {
Row(
modifier = Modifier
.fillMaxWidth()
.padding(12.dp),
verticalAlignment = Alignment.CenterVertically
) {
Icon(
imageVector = Icons.Default.Info,
contentDescription = null,
tint = MaterialTheme.colorScheme.onPrimaryContainer
)
Spacer(modifier = Modifier.width(8.dp))
Column {
Text(
text = "Model will be created as:",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onPrimaryContainer
)
Text(
text = buildModelName(name, ageText, annotatedCluster.year),
style = MaterialTheme.typography.bodyMedium,
fontWeight = FontWeight.Bold,
color = MaterialTheme.colorScheme.onPrimaryContainer
)
}
}
}
}
}
// Cluster stats
ClusterStats(qualityResult)
HorizontalDivider()
// Actions
Row(
modifier = Modifier.fillMaxWidth(),
horizontalArrangement = Arrangement.spacedBy(12.dp)
) {
OutlinedButton(
onClick = onDismiss,
modifier = Modifier.weight(1f)
) {
Text("Cancel")
}
Button(
onClick = {
val age = ageText.toIntOrNull()
onConfirm(name, age, isChild)
},
modifier = Modifier.weight(1f),
enabled = name.isNotBlank() && qualityResult.canTrain
) {
Text("Create")
}
}
}
}
}
}
/**
* Year badge showing photo year
*/
@Composable
private fun YearBadge(year: String) {
Surface(
color = MaterialTheme.colorScheme.secondaryContainer,
shape = MaterialTheme.shapes.small
) {
Row(
modifier = Modifier.padding(horizontal = 12.dp, vertical = 6.dp),
verticalAlignment = Alignment.CenterVertically,
horizontalArrangement = Arrangement.spacedBy(4.dp)
) {
Icon(
imageVector = Icons.Default.DateRange,
contentDescription = null,
modifier = Modifier.size(16.dp),
tint = MaterialTheme.colorScheme.onSecondaryContainer
)
Text(
text = "Photos from $year",
style = MaterialTheme.typography.labelMedium,
color = MaterialTheme.colorScheme.onSecondaryContainer
)
}
}
}
/**
* Quality warnings
*/
@Composable
private fun QualityWarnings(qualityResult: ClusterQualityResult) {
if (qualityResult.warnings.isNotEmpty()) {
Card(
colors = CardDefaults.cardColors(
containerColor = when (qualityResult.qualityTier) {
com.placeholder.sherpai2.domain.clustering.ClusterQualityTier.POOR ->
MaterialTheme.colorScheme.errorContainer
com.placeholder.sherpai2.domain.clustering.ClusterQualityTier.GOOD ->
MaterialTheme.colorScheme.tertiaryContainer
else -> MaterialTheme.colorScheme.surfaceVariant
}
)
) {
Column(
modifier = Modifier.padding(12.dp),
verticalArrangement = Arrangement.spacedBy(4.dp)
) {
qualityResult.warnings.take(3).forEach { warning ->
Row(
verticalAlignment = Alignment.Top,
horizontalArrangement = Arrangement.spacedBy(8.dp)
) {
Icon(
imageVector = when (qualityResult.qualityTier) {
com.placeholder.sherpai2.domain.clustering.ClusterQualityTier.POOR ->
Icons.Default.Warning
else -> Icons.Default.Info
},
contentDescription = null,
modifier = Modifier.size(16.dp),
tint = when (qualityResult.qualityTier) {
com.placeholder.sherpai2.domain.clustering.ClusterQualityTier.POOR ->
MaterialTheme.colorScheme.onErrorContainer
else -> MaterialTheme.colorScheme.onSurfaceVariant
}
)
Text(
text = warning,
style = MaterialTheme.typography.bodySmall,
color = when (qualityResult.qualityTier) {
com.placeholder.sherpai2.domain.clustering.ClusterQualityTier.POOR ->
MaterialTheme.colorScheme.onErrorContainer
else -> MaterialTheme.colorScheme.onSurfaceVariant
}
)
}
}
}
}
}
}
/**
* Cluster statistics
*/
@Composable
private fun ClusterStats(qualityResult: ClusterQualityResult) {
Row(
modifier = Modifier.fillMaxWidth(),
horizontalArrangement = Arrangement.SpaceEvenly
) {
StatItem(
label = "Photos",
value = qualityResult.soloPhotoCount.toString()
)
StatItem(
label = "Clean Faces",
value = qualityResult.cleanFaceCount.toString()
)
StatItem(
label = "Quality",
value = "${(qualityResult.qualityScore * 100).toInt()}%"
)
}
}
@Composable
private fun StatItem(label: String, value: String) {
Column(
horizontalAlignment = Alignment.CenterHorizontally
) {
Text(
text = value,
style = MaterialTheme.typography.titleMedium,
fontWeight = FontWeight.Bold
)
Text(
text = label,
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
/**
* Build model name preview
*/
private fun buildModelName(name: String, ageText: String, year: String): String {
return when {
ageText.isNotBlank() -> "${name}_Age_${ageText}"
else -> "${name}_${year}"
}
}

View File

@@ -0,0 +1,613 @@
package com.placeholder.sherpai2.ui.discover
import android.net.Uri
import androidx.compose.animation.AnimatedVisibility
import androidx.compose.animation.core.animateFloatAsState
import androidx.compose.foundation.background
import androidx.compose.foundation.border
import androidx.compose.foundation.clickable
import androidx.compose.foundation.gestures.detectDragGestures
import androidx.compose.foundation.layout.*
import androidx.compose.foundation.lazy.grid.GridCells
import androidx.compose.foundation.lazy.grid.LazyVerticalGrid
import androidx.compose.foundation.lazy.grid.items
import androidx.compose.foundation.shape.CircleShape
import androidx.compose.foundation.shape.RoundedCornerShape
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.filled.*
import androidx.compose.material3.*
import androidx.compose.runtime.*
import androidx.compose.ui.Alignment
import androidx.compose.ui.Modifier
import androidx.compose.ui.draw.clip
import androidx.compose.ui.draw.scale
import androidx.compose.ui.graphics.Color
import androidx.compose.ui.input.pointer.pointerInput
import androidx.compose.ui.layout.ContentScale
import androidx.compose.ui.text.font.FontWeight
import androidx.compose.ui.text.style.TextAlign
import androidx.compose.ui.unit.IntOffset
import androidx.compose.ui.unit.dp
import androidx.compose.ui.zIndex
import coil.compose.AsyncImage
import com.placeholder.sherpai2.data.local.entity.FeedbackType
import com.placeholder.sherpai2.domain.validation.ValidationScanResult
import com.placeholder.sherpai2.domain.validation.ValidationMatch
import kotlin.math.roundToInt
/**
* ValidationPreviewScreen - User reviews validation results with swipe gestures
*
* FEATURES:
* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
* ✅ Swipe right (✓) = Confirmed match
* ✅ Swipe left (✗) = Rejected match
* ✅ Tap = Mark uncertain (?)
* ✅ Real-time feedback stats
* ✅ Automatic refinement recommendation
* ✅ Bottom bar with approve/reject/refine actions
*
* FLOW:
* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
* 1. User swipes/taps to mark faces
* 2. Feedback tracked in local state
* 3. If >15% rejection → "Refine" button appears
* 4. Approve → Sends feedback map to ViewModel
* 5. Reject → Returns to previous screen
* 6. Refine → Triggers cluster refinement
*/
@Composable
fun ValidationPreviewScreen(
personName: String,
validationResult: ValidationScanResult,
onMarkFeedback: (Map<String, FeedbackType>) -> Unit = {},
onRequestRefinement: () -> Unit = {},
onApprove: () -> Unit,
onReject: () -> Unit,
modifier: Modifier = Modifier
) {
// Get sample images from validation result matches
val sampleMatches = remember(validationResult) {
validationResult.matches.take(24) // Show up to 24 faces
}
// Track feedback for each image (imageId -> FeedbackType)
var feedbackMap by remember {
mutableStateOf<Map<String, FeedbackType>>(emptyMap())
}
// Calculate feedback statistics
val confirmedCount = feedbackMap.count { it.value == FeedbackType.CONFIRMED_MATCH }
val rejectedCount = feedbackMap.count { it.value == FeedbackType.REJECTED_MATCH }
val uncertainCount = feedbackMap.count { it.value == FeedbackType.UNCERTAIN }
val reviewedCount = feedbackMap.size
val totalCount = sampleMatches.size
// Determine if refinement is recommended
val rejectionRatio = if (reviewedCount > 0) {
rejectedCount.toFloat() / reviewedCount.toFloat()
} else {
0f
}
val shouldRefine = rejectionRatio > 0.15f && rejectedCount >= 2
Scaffold(
bottomBar = {
ValidationBottomBar(
confirmedCount = confirmedCount,
rejectedCount = rejectedCount,
uncertainCount = uncertainCount,
reviewedCount = reviewedCount,
totalCount = totalCount,
shouldRefine = shouldRefine,
onApprove = {
onMarkFeedback(feedbackMap)
onApprove()
},
onReject = onReject,
onRefine = {
onMarkFeedback(feedbackMap)
onRequestRefinement()
}
)
}
) { paddingValues ->
Column(
modifier = modifier
.fillMaxSize()
.padding(paddingValues)
.padding(16.dp)
) {
// Header
Text(
text = "Validate \"$personName\"",
style = MaterialTheme.typography.headlineMedium,
fontWeight = FontWeight.Bold
)
Spacer(modifier = Modifier.height(8.dp))
// Instructions
InstructionsCard()
Spacer(modifier = Modifier.height(16.dp))
// Feedback stats
FeedbackStatsCard(
confirmedCount = confirmedCount,
rejectedCount = rejectedCount,
uncertainCount = uncertainCount,
reviewedCount = reviewedCount,
totalCount = totalCount
)
Spacer(modifier = Modifier.height(16.dp))
// Grid of faces to review
LazyVerticalGrid(
columns = GridCells.Fixed(3),
horizontalArrangement = Arrangement.spacedBy(8.dp),
verticalArrangement = Arrangement.spacedBy(8.dp),
modifier = Modifier.weight(1f)
) {
items(
items = sampleMatches,
key = { match -> match.imageId }
) { match ->
SwipeableFaceCard(
match = match,
currentFeedback = feedbackMap[match.imageId],
onFeedbackChange = { feedback ->
feedbackMap = feedbackMap.toMutableMap().apply {
put(match.imageId, feedback)
}
}
)
}
}
}
}
}
/**
* Swipeable face card with visual feedback indicators
*/
@Composable
private fun SwipeableFaceCard(
match: ValidationMatch,
currentFeedback: FeedbackType?,
onFeedbackChange: (FeedbackType) -> Unit
) {
var offsetX by remember { mutableFloatStateOf(0f) }
var isDragging by remember { mutableStateOf(false) }
val scale by animateFloatAsState(
targetValue = if (isDragging) 1.1f else 1f,
label = "scale"
)
Box(
modifier = Modifier
.aspectRatio(1f)
.scale(scale)
.zIndex(if (isDragging) 1f else 0f)
) {
// Face image with border color based on feedback
AsyncImage(
model = Uri.parse(match.imageUri),
contentDescription = "Face",
modifier = Modifier
.fillMaxSize()
.clip(RoundedCornerShape(12.dp))
.border(
width = 3.dp,
color = when (currentFeedback) {
FeedbackType.CONFIRMED_MATCH -> Color(0xFF4CAF50) // Green
FeedbackType.REJECTED_MATCH -> Color(0xFFF44336) // Red
FeedbackType.UNCERTAIN -> Color(0xFFFF9800) // Orange
else -> MaterialTheme.colorScheme.outline
},
shape = RoundedCornerShape(12.dp)
)
.offset { IntOffset(offsetX.roundToInt(), 0) }
.pointerInput(Unit) {
detectDragGestures(
onDragStart = {
isDragging = true
},
onDrag = { _, dragAmount ->
offsetX += dragAmount.x
},
onDragEnd = {
isDragging = false
// Determine feedback based on swipe direction
when {
offsetX > 100 -> {
onFeedbackChange(FeedbackType.CONFIRMED_MATCH)
}
offsetX < -100 -> {
onFeedbackChange(FeedbackType.REJECTED_MATCH)
}
}
// Reset position
offsetX = 0f
},
onDragCancel = {
isDragging = false
offsetX = 0f
}
)
}
.clickable {
// Tap to toggle uncertain
val newFeedback = when (currentFeedback) {
FeedbackType.UNCERTAIN -> null
else -> FeedbackType.UNCERTAIN
}
if (newFeedback != null) {
onFeedbackChange(newFeedback)
}
},
contentScale = ContentScale.Crop
)
// Confidence badge (top-left)
Surface(
modifier = Modifier
.align(Alignment.TopStart)
.padding(4.dp),
shape = RoundedCornerShape(4.dp),
color = Color.Black.copy(alpha = 0.6f)
) {
Text(
text = "${(match.confidence * 100).toInt()}%",
modifier = Modifier.padding(horizontal = 6.dp, vertical = 2.dp),
style = MaterialTheme.typography.labelSmall,
color = Color.White,
fontWeight = FontWeight.Bold
)
}
// Feedback indicator overlay (top-right)
if (currentFeedback != null) {
Surface(
modifier = Modifier
.align(Alignment.TopEnd)
.padding(4.dp),
shape = CircleShape,
color = when (currentFeedback) {
FeedbackType.CONFIRMED_MATCH -> Color(0xFF4CAF50)
FeedbackType.REJECTED_MATCH -> Color(0xFFF44336)
FeedbackType.UNCERTAIN -> Color(0xFFFF9800)
else -> Color.Transparent
},
shadowElevation = 2.dp
) {
Icon(
imageVector = when (currentFeedback) {
FeedbackType.CONFIRMED_MATCH -> Icons.Default.Check
FeedbackType.REJECTED_MATCH -> Icons.Default.Close
FeedbackType.UNCERTAIN -> Icons.Default.Warning
else -> Icons.Default.Info
},
contentDescription = currentFeedback.name,
tint = Color.White,
modifier = Modifier
.size(32.dp)
.padding(6.dp)
)
}
}
// Swipe hint during drag
if (isDragging) {
SwipeDragHint(offsetX = offsetX)
}
}
}
/**
* Swipe drag hint overlay
*/
@Composable
private fun BoxScope.SwipeDragHint(offsetX: Float) {
val hintText = when {
offsetX > 50 -> "✓ Correct"
offsetX < -50 -> "✗ Incorrect"
else -> "Keep swiping"
}
val hintColor = when {
offsetX > 50 -> Color(0xFF4CAF50)
offsetX < -50 -> Color(0xFFF44336)
else -> Color.Gray
}
Surface(
modifier = Modifier
.align(Alignment.BottomCenter)
.padding(8.dp),
shape = RoundedCornerShape(4.dp),
color = hintColor.copy(alpha = 0.9f)
) {
Text(
text = hintText,
modifier = Modifier.padding(horizontal = 8.dp, vertical = 4.dp),
style = MaterialTheme.typography.labelSmall,
color = Color.White,
fontWeight = FontWeight.Bold
)
}
}
/**
* Instructions card showing gesture controls
*/
@Composable
private fun InstructionsCard() {
Card(
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.primaryContainer
)
) {
Row(
modifier = Modifier.padding(16.dp),
verticalAlignment = Alignment.CenterVertically
) {
Icon(
imageVector = Icons.Default.Info,
contentDescription = null,
tint = MaterialTheme.colorScheme.onPrimaryContainer
)
Spacer(modifier = Modifier.width(12.dp))
Column {
Text(
text = "Review Detected Faces",
style = MaterialTheme.typography.titleSmall,
fontWeight = FontWeight.Bold,
color = MaterialTheme.colorScheme.onPrimaryContainer
)
Spacer(modifier = Modifier.height(4.dp))
Text(
text = "Swipe right ✅ for correct, left ❌ for incorrect, tap ❓ for uncertain",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onPrimaryContainer
)
}
}
}
}
/**
* Feedback statistics card
*/
@Composable
private fun FeedbackStatsCard(
confirmedCount: Int,
rejectedCount: Int,
uncertainCount: Int,
reviewedCount: Int,
totalCount: Int
) {
Card {
Row(
modifier = Modifier
.fillMaxWidth()
.padding(16.dp),
horizontalArrangement = Arrangement.SpaceEvenly
) {
FeedbackStat(
icon = Icons.Default.Check,
color = Color(0xFF4CAF50),
count = confirmedCount,
label = "Correct"
)
FeedbackStat(
icon = Icons.Default.Close,
color = Color(0xFFF44336),
count = rejectedCount,
label = "Incorrect"
)
FeedbackStat(
icon = Icons.Default.Warning,
color = Color(0xFFFF9800),
count = uncertainCount,
label = "Uncertain"
)
}
val progressValue = if (totalCount > 0) {
reviewedCount.toFloat() / totalCount.toFloat()
} else {
0f
}
LinearProgressIndicator(
progress = { progressValue },
modifier = Modifier
.fillMaxWidth()
.height(4.dp)
)
}
}
/**
* Individual feedback statistic item
*/
@Composable
private fun FeedbackStat(
icon: androidx.compose.ui.graphics.vector.ImageVector,
color: Color,
count: Int,
label: String
) {
Column(
horizontalAlignment = Alignment.CenterHorizontally
) {
Surface(
shape = CircleShape,
color = color.copy(alpha = 0.2f)
) {
Icon(
imageVector = icon,
contentDescription = null,
tint = color,
modifier = Modifier
.size(40.dp)
.padding(8.dp)
)
}
Spacer(modifier = Modifier.height(4.dp))
Text(
text = count.toString(),
style = MaterialTheme.typography.titleMedium,
fontWeight = FontWeight.Bold
)
Text(
text = label,
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
/**
* Bottom action bar with approve/reject/refine buttons
*/
@Composable
private fun ValidationBottomBar(
confirmedCount: Int,
rejectedCount: Int,
uncertainCount: Int,
reviewedCount: Int,
totalCount: Int,
shouldRefine: Boolean,
onApprove: () -> Unit,
onReject: () -> Unit,
onRefine: () -> Unit
) {
Surface(
modifier = Modifier.fillMaxWidth(),
color = MaterialTheme.colorScheme.surface,
shadowElevation = 8.dp
) {
Column(
modifier = Modifier.padding(16.dp)
) {
// Refinement warning banner
AnimatedVisibility(visible = shouldRefine) {
RefinementWarningBanner(
rejectedCount = rejectedCount,
reviewedCount = reviewedCount,
onRefine = onRefine
)
}
// Main action buttons
Row(
modifier = Modifier.fillMaxWidth(),
horizontalArrangement = Arrangement.spacedBy(12.dp)
) {
OutlinedButton(
onClick = onReject,
modifier = Modifier.weight(1f)
) {
Icon(Icons.Default.Close, contentDescription = null)
Spacer(modifier = Modifier.width(8.dp))
Text("Reject")
}
Button(
onClick = onApprove,
modifier = Modifier.weight(1f),
enabled = confirmedCount > 0 || (reviewedCount == 0 && totalCount > 6)
) {
Icon(Icons.Default.Check, contentDescription = null)
Spacer(modifier = Modifier.width(8.dp))
Text("Approve")
}
}
// Review progress text
Spacer(modifier = Modifier.height(8.dp))
Text(
text = if (reviewedCount == 0) {
"Review faces above or approve to continue"
} else {
"Reviewed $reviewedCount of $totalCount faces"
},
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant,
textAlign = TextAlign.Center,
modifier = Modifier.fillMaxWidth()
)
}
}
}
/**
* Refinement warning banner component
*/
@Composable
private fun RefinementWarningBanner(
rejectedCount: Int,
reviewedCount: Int,
onRefine: () -> Unit
) {
Column {
Card(
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.errorContainer
),
modifier = Modifier.fillMaxWidth()
) {
Row(
modifier = Modifier.padding(12.dp),
verticalAlignment = Alignment.CenterVertically
) {
Icon(
imageVector = Icons.Default.Warning,
contentDescription = null,
tint = MaterialTheme.colorScheme.onErrorContainer
)
Spacer(modifier = Modifier.width(12.dp))
Column(modifier = Modifier.weight(1f)) {
Text(
text = "High Rejection Rate",
style = MaterialTheme.typography.titleSmall,
fontWeight = FontWeight.Bold,
color = MaterialTheme.colorScheme.onErrorContainer
)
Text(
text = "${(rejectedCount.toFloat() / reviewedCount.toFloat() * 100).toInt()}% rejected. Consider refining the cluster.",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onErrorContainer
)
}
Button(
onClick = onRefine,
colors = ButtonDefaults.buttonColors(
containerColor = MaterialTheme.colorScheme.error
)
) {
Text("Refine")
}
}
}
Spacer(modifier = Modifier.height(12.dp))
}
}

View File

@@ -0,0 +1,489 @@
package com.placeholder.sherpai2.ui.explore
import androidx.compose.foundation.background
import androidx.compose.foundation.clickable
import androidx.compose.foundation.layout.*
import androidx.compose.foundation.lazy.LazyColumn
import androidx.compose.foundation.lazy.LazyRow
import androidx.compose.foundation.lazy.items
import androidx.compose.foundation.shape.CircleShape
import androidx.compose.foundation.shape.RoundedCornerShape
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.filled.*
import androidx.compose.material3.*
import androidx.compose.runtime.*
import androidx.compose.ui.Alignment
import androidx.compose.ui.Modifier
import androidx.compose.ui.draw.clip
import androidx.compose.ui.graphics.Brush
import androidx.compose.ui.graphics.Color
import androidx.compose.ui.graphics.vector.ImageVector
import androidx.compose.ui.text.font.FontWeight
import androidx.compose.ui.unit.dp
import androidx.hilt.navigation.compose.hiltViewModel
/**
* CLEANED ExploreScreen - No gradient header banner
*
* Removed:
* - Gradient header box (lines 46-75) that created banner effect
* - "Explore" title (MainScreen shows it)
*
* Features:
* - Rectangular album cards (compact)
* - Stories section (recent highlights)
* - Clickable navigation to AlbumViewScreen
* - Beautiful gradients and icons
* - Mobile-friendly scrolling
*/
@Composable
fun ExploreScreen(
onAlbumClick: (albumType: String, albumId: String) -> Unit,
viewModel: ExploreViewModel = hiltViewModel(),
modifier: Modifier = Modifier
) {
val uiState by viewModel.uiState.collectAsState()
Box(modifier = modifier.fillMaxSize()) {
when (val state = uiState) {
is ExploreViewModel.ExploreUiState.Loading -> {
Box(
modifier = Modifier.fillMaxSize(),
contentAlignment = Alignment.Center
) {
CircularProgressIndicator()
}
}
is ExploreViewModel.ExploreUiState.Success -> {
if (state.smartAlbums.isEmpty()) {
EmptyExploreView()
} else {
ExploreContent(
smartAlbums = state.smartAlbums,
onAlbumClick = onAlbumClick
)
}
}
is ExploreViewModel.ExploreUiState.Error -> {
Box(
modifier = Modifier.fillMaxSize(),
contentAlignment = Alignment.Center
) {
Column(
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.spacedBy(12.dp),
modifier = Modifier.padding(32.dp)
) {
Icon(
Icons.Default.Error,
contentDescription = null,
modifier = Modifier.size(64.dp),
tint = MaterialTheme.colorScheme.error
)
Text(
text = "Error Loading Albums",
style = MaterialTheme.typography.titleLarge,
fontWeight = FontWeight.Bold
)
Text(
text = state.message,
style = MaterialTheme.typography.bodyMedium,
color = MaterialTheme.colorScheme.onSurfaceVariant,
textAlign = androidx.compose.ui.text.style.TextAlign.Center
)
}
}
}
}
}
}
/**
* Main content - scrollable album sections
*/
@Composable
private fun ExploreContent(
smartAlbums: List<SmartAlbum>,
onAlbumClick: (albumType: String, albumId: String) -> Unit
) {
LazyColumn(
modifier = Modifier.fillMaxSize(),
contentPadding = PaddingValues(vertical = 16.dp),
verticalArrangement = Arrangement.spacedBy(24.dp)
) {
// Stories Section (Recent Highlights)
item {
val storyAlbums = smartAlbums.filter { it.imageCount > 0 }.take(10)
if (storyAlbums.isNotEmpty()) {
StoriesSection(
albums = storyAlbums,
onAlbumClick = onAlbumClick
)
}
}
// Time-based Albums
val timeAlbums = smartAlbums.filterIsInstance<SmartAlbum.TimeRange>()
if (timeAlbums.isNotEmpty()) {
item {
AlbumSection(
title = "📅 Time Capsules",
albums = timeAlbums,
onAlbumClick = onAlbumClick
)
}
}
// Face-based Albums
val faceAlbums = smartAlbums.filterIsInstance<SmartAlbum.Tagged>()
.filter { it.tagValue in listOf("group_photo", "selfie", "couple") }
if (faceAlbums.isNotEmpty()) {
item {
AlbumSection(
title = "👥 People & Groups",
albums = faceAlbums,
onAlbumClick = onAlbumClick
)
}
}
// Relationship Albums
val relationshipAlbums = smartAlbums.filterIsInstance<SmartAlbum.Tagged>()
.filter { it.tagValue in listOf("family", "friend", "colleague") }
if (relationshipAlbums.isNotEmpty()) {
item {
AlbumSection(
title = "❤️ Relationships",
albums = relationshipAlbums,
onAlbumClick = onAlbumClick
)
}
}
// Time of Day Albums
val timeOfDayAlbums = smartAlbums.filterIsInstance<SmartAlbum.Tagged>()
.filter { it.tagValue in listOf("morning", "afternoon", "evening", "night") }
if (timeOfDayAlbums.isNotEmpty()) {
item {
AlbumSection(
title = "🌅 Times of Day",
albums = timeOfDayAlbums,
onAlbumClick = onAlbumClick
)
}
}
// Scene Albums
val sceneAlbums = smartAlbums.filterIsInstance<SmartAlbum.Tagged>()
.filter { it.tagValue in listOf("indoor", "outdoor") }
if (sceneAlbums.isNotEmpty()) {
item {
AlbumSection(
title = "🏞️ Scenes",
albums = sceneAlbums,
onAlbumClick = onAlbumClick
)
}
}
// Special Occasions
val specialAlbums = smartAlbums.filterIsInstance<SmartAlbum.Tagged>()
.filter { it.tagValue in listOf("birthday", "high_res") }
if (specialAlbums.isNotEmpty()) {
item {
AlbumSection(
title = "⭐ Special",
albums = specialAlbums,
onAlbumClick = onAlbumClick
)
}
}
// Person Albums
val personAlbums = smartAlbums.filterIsInstance<SmartAlbum.Person>()
if (personAlbums.isNotEmpty()) {
item {
AlbumSection(
title = "👤 People",
albums = personAlbums,
onAlbumClick = onAlbumClick
)
}
}
}
}
/**
* Stories section - circular album previews
*/
@Composable
private fun StoriesSection(
albums: List<SmartAlbum>,
onAlbumClick: (albumType: String, albumId: String) -> Unit
) {
Column(
modifier = Modifier.fillMaxWidth()
) {
Text(
text = "📖 Stories",
style = MaterialTheme.typography.titleLarge,
fontWeight = FontWeight.Bold,
modifier = Modifier.padding(horizontal = 16.dp, vertical = 8.dp)
)
LazyRow(
contentPadding = PaddingValues(horizontal = 16.dp),
horizontalArrangement = Arrangement.spacedBy(16.dp)
) {
items(albums) { album ->
StoryCircle(
album = album,
onClick = {
val (type, id) = getAlbumNavigation(album)
onAlbumClick(type, id)
}
)
}
}
}
}
/**
* Story circle - circular album preview
*/
@Composable
private fun StoryCircle(
album: SmartAlbum,
onClick: () -> Unit
) {
val (icon, gradient) = getAlbumIconAndGradient(album)
Column(
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.spacedBy(8.dp),
modifier = Modifier.clickable(onClick = onClick)
) {
Box(
modifier = Modifier
.size(80.dp)
.clip(CircleShape)
.background(gradient),
contentAlignment = Alignment.Center
) {
Icon(
imageVector = icon,
contentDescription = null,
tint = Color.White,
modifier = Modifier.size(36.dp)
)
}
Text(
text = album.displayName,
style = MaterialTheme.typography.labelSmall,
maxLines = 2,
modifier = Modifier.width(80.dp),
fontWeight = FontWeight.Medium,
textAlign = androidx.compose.ui.text.style.TextAlign.Center
)
Text(
text = "${album.imageCount}",
style = MaterialTheme.typography.labelSmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
/**
* Album section with horizontal scrolling rectangular cards
*/
@Composable
private fun AlbumSection(
title: String,
albums: List<SmartAlbum>,
onAlbumClick: (albumType: String, albumId: String) -> Unit
) {
Column(
modifier = Modifier.fillMaxWidth()
) {
Text(
text = title,
style = MaterialTheme.typography.titleLarge,
fontWeight = FontWeight.Bold,
modifier = Modifier.padding(horizontal = 16.dp, vertical = 8.dp)
)
LazyRow(
contentPadding = PaddingValues(horizontal = 16.dp),
horizontalArrangement = Arrangement.spacedBy(12.dp)
) {
items(albums) { album ->
AlbumCard(
album = album,
onClick = {
val (type, id) = getAlbumNavigation(album)
onAlbumClick(type, id)
}
)
}
}
}
}
/**
* Rectangular album card - compact design
*/
@Composable
private fun AlbumCard(
album: SmartAlbum,
onClick: () -> Unit
) {
val (icon, gradient) = getAlbumIconAndGradient(album)
Card(
modifier = Modifier
.width(180.dp)
.height(120.dp)
.clickable(onClick = onClick),
shape = RoundedCornerShape(16.dp),
elevation = CardDefaults.cardElevation(defaultElevation = 4.dp)
) {
Box(
modifier = Modifier
.fillMaxSize()
.background(gradient)
) {
Column(
modifier = Modifier
.fillMaxSize()
.padding(16.dp),
verticalArrangement = Arrangement.SpaceBetween
) {
// Icon
Icon(
imageVector = icon,
contentDescription = null,
tint = Color.White,
modifier = Modifier.size(32.dp)
)
// Album info
Column {
Text(
text = album.displayName,
style = MaterialTheme.typography.titleMedium,
fontWeight = FontWeight.Bold,
color = Color.White,
maxLines = 1
)
Text(
text = "${album.imageCount} ${if (album.imageCount == 1) "photo" else "photos"}",
style = MaterialTheme.typography.bodySmall,
color = Color.White.copy(alpha = 0.9f)
)
}
}
}
}
}
/**
* Empty state
*/
@Composable
private fun EmptyExploreView() {
Box(
modifier = Modifier
.fillMaxSize()
.padding(32.dp),
contentAlignment = Alignment.Center
) {
Column(
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.spacedBy(16.dp)
) {
Icon(
Icons.Default.PhotoAlbum,
contentDescription = null,
modifier = Modifier.size(80.dp),
tint = MaterialTheme.colorScheme.onSurfaceVariant.copy(alpha = 0.6f)
)
Text(
"No Albums Yet",
style = MaterialTheme.typography.titleLarge,
fontWeight = FontWeight.Bold
)
Text(
"Add photos to your collection to see smart albums",
style = MaterialTheme.typography.bodyMedium,
color = MaterialTheme.colorScheme.onSurfaceVariant,
textAlign = androidx.compose.ui.text.style.TextAlign.Center
)
}
}
}
/**
* Get navigation parameters for album
*/
private fun getAlbumNavigation(album: SmartAlbum): Pair<String, String> {
return when (album) {
is SmartAlbum.TimeRange.Today -> "time" to "today"
is SmartAlbum.TimeRange.ThisWeek -> "time" to "week"
is SmartAlbum.TimeRange.ThisMonth -> "time" to "month"
is SmartAlbum.TimeRange.LastYear -> "time" to "year"
is SmartAlbum.Tagged -> "tag" to album.tagValue
is SmartAlbum.Person -> "person" to album.personId
}
}
/**
* Get icon and gradient for album type
*/
private fun getAlbumIconAndGradient(album: SmartAlbum): Pair<ImageVector, Brush> {
return when (album) {
is SmartAlbum.TimeRange.Today -> Icons.Default.Today to gradientBlue()
is SmartAlbum.TimeRange.ThisWeek -> Icons.Default.DateRange to gradientTeal()
is SmartAlbum.TimeRange.ThisMonth -> Icons.Default.CalendarMonth to gradientGreen()
is SmartAlbum.TimeRange.LastYear -> Icons.Default.HistoryEdu to gradientPurple()
is SmartAlbum.Tagged -> when (album.tagValue) {
"group_photo" -> Icons.Default.Group to gradientOrange()
"selfie" -> Icons.Default.CameraAlt to gradientPink()
"couple" -> Icons.Default.Favorite to gradientRed()
"family" -> Icons.Default.FamilyRestroom to gradientIndigo()
"friend" -> Icons.Default.People to gradientCyan()
"colleague" -> Icons.Default.BusinessCenter to gradientGray()
"morning" -> Icons.Default.WbSunny to gradientYellow()
"afternoon" -> Icons.Default.LightMode to gradientOrange()
"evening" -> Icons.Default.WbTwilight to gradientOrange()
"night" -> Icons.Default.NightsStay to gradientDarkBlue()
"outdoor" -> Icons.Default.Landscape to gradientGreen()
"indoor" -> Icons.Default.Home to gradientBrown()
"birthday" -> Icons.Default.Cake to gradientPink()
"high_res" -> Icons.Default.HighQuality to gradientGold()
else -> Icons.Default.Label to gradientBlue()
}
is SmartAlbum.Person -> Icons.Default.Person to gradientPurple()
}
}
// Gradient helpers
private fun gradientBlue() = Brush.linearGradient(listOf(Color(0xFF1976D2), Color(0xFF1565C0)))
private fun gradientTeal() = Brush.linearGradient(listOf(Color(0xFF00897B), Color(0xFF00796B)))
private fun gradientGreen() = Brush.linearGradient(listOf(Color(0xFF388E3C), Color(0xFF2E7D32)))
private fun gradientPurple() = Brush.linearGradient(listOf(Color(0xFF7B1FA2), Color(0xFF6A1B9A)))
private fun gradientOrange() = Brush.linearGradient(listOf(Color(0xFFF57C00), Color(0xFFE64A19)))
private fun gradientPink() = Brush.linearGradient(listOf(Color(0xFFD81B60), Color(0xFFC2185B)))
private fun gradientRed() = Brush.linearGradient(listOf(Color(0xFFE53935), Color(0xFFD32F2F)))
private fun gradientIndigo() = Brush.linearGradient(listOf(Color(0xFF3949AB), Color(0xFF303F9F)))
private fun gradientCyan() = Brush.linearGradient(listOf(Color(0xFF00ACC1), Color(0xFF0097A7)))
private fun gradientGray() = Brush.linearGradient(listOf(Color(0xFF616161), Color(0xFF424242)))
private fun gradientYellow() = Brush.linearGradient(listOf(Color(0xFFFDD835), Color(0xFFFBC02D)))
private fun gradientDarkBlue() = Brush.linearGradient(listOf(Color(0xFF283593), Color(0xFF1A237E)))
private fun gradientBrown() = Brush.linearGradient(listOf(Color(0xFF5D4037), Color(0xFF4E342E)))
private fun gradientGold() = Brush.linearGradient(listOf(Color(0xFFFFB300), Color(0xFFFFA000)))

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package com.placeholder.sherpai2.ui.explore
import androidx.lifecycle.ViewModel
import androidx.lifecycle.viewModelScope
import com.placeholder.sherpai2.data.local.dao.ImageDao
import com.placeholder.sherpai2.data.local.dao.ImageTagDao
import com.placeholder.sherpai2.data.local.dao.PersonDao
import com.placeholder.sherpai2.data.local.dao.TagDao
import com.placeholder.sherpai2.data.local.entity.ImageEntity
import com.placeholder.sherpai2.data.repository.FaceRecognitionRepository
import dagger.hilt.android.lifecycle.HiltViewModel
import kotlinx.coroutines.flow.MutableStateFlow
import kotlinx.coroutines.flow.StateFlow
import kotlinx.coroutines.flow.asStateFlow
import kotlinx.coroutines.launch
import java.util.Calendar
import javax.inject.Inject
@HiltViewModel
class ExploreViewModel @Inject constructor(
private val imageDao: ImageDao,
private val tagDao: TagDao,
private val imageTagDao: ImageTagDao,
private val personDao: PersonDao,
private val faceRecognitionRepository: FaceRecognitionRepository
) : ViewModel() {
private val _uiState = MutableStateFlow<ExploreUiState>(ExploreUiState.Loading)
val uiState: StateFlow<ExploreUiState> = _uiState.asStateFlow()
sealed class ExploreUiState {
object Loading : ExploreUiState()
data class Success(
val smartAlbums: List<SmartAlbum>
) : ExploreUiState()
data class Error(val message: String) : ExploreUiState()
}
init {
loadExploreData()
}
fun loadExploreData() {
viewModelScope.launch {
try {
_uiState.value = ExploreUiState.Loading
val smartAlbums = buildSmartAlbums()
_uiState.value = ExploreUiState.Success(
smartAlbums = smartAlbums
)
} catch (e: Exception) {
_uiState.value = ExploreUiState.Error(
e.message ?: "Failed to load explore data"
)
}
}
}
private suspend fun buildSmartAlbums(): List<SmartAlbum> {
val albums = mutableListOf<SmartAlbum>()
// Time-based albums
albums.add(SmartAlbum.TimeRange.Today)
albums.add(SmartAlbum.TimeRange.ThisWeek)
albums.add(SmartAlbum.TimeRange.ThisMonth)
albums.add(SmartAlbum.TimeRange.LastYear)
// Face-based albums (from system tags)
val groupPhotoTag = tagDao.getByValue("group_photo")
if (groupPhotoTag != null) {
val count = tagDao.getTagUsageCount(groupPhotoTag.tagId)
if (count > 0) {
albums.add(SmartAlbum.Tagged("group_photo", "Group Photos", count))
}
}
val selfieTag = tagDao.getByValue("selfie")
if (selfieTag != null) {
val count = tagDao.getTagUsageCount(selfieTag.tagId)
if (count > 0) {
albums.add(SmartAlbum.Tagged("selfie", "Selfies", count))
}
}
val coupleTag = tagDao.getByValue("couple")
if (coupleTag != null) {
val count = tagDao.getTagUsageCount(coupleTag.tagId)
if (count > 0) {
albums.add(SmartAlbum.Tagged("couple", "Couples", count))
}
}
// Relationship albums
val familyTag = tagDao.getByValue("family")
if (familyTag != null) {
val count = tagDao.getTagUsageCount(familyTag.tagId)
if (count > 0) {
albums.add(SmartAlbum.Tagged("family", "Family Moments", count))
}
}
val friendTag = tagDao.getByValue("friend")
if (friendTag != null) {
val count = tagDao.getTagUsageCount(friendTag.tagId)
if (count > 0) {
albums.add(SmartAlbum.Tagged("friend", "With Friends", count))
}
}
val colleagueTag = tagDao.getByValue("colleague")
if (colleagueTag != null) {
val count = tagDao.getTagUsageCount(colleagueTag.tagId)
if (count > 0) {
albums.add(SmartAlbum.Tagged("colleague", "Work Events", count))
}
}
// Time of day albums
val morningTag = tagDao.getByValue("morning")
if (morningTag != null) {
val count = tagDao.getTagUsageCount(morningTag.tagId)
if (count > 0) {
albums.add(SmartAlbum.Tagged("morning", "Morning Moments", count))
}
}
val eveningTag = tagDao.getByValue("evening")
if (eveningTag != null) {
val count = tagDao.getTagUsageCount(eveningTag.tagId)
if (count > 0) {
albums.add(SmartAlbum.Tagged("evening", "Golden Hour", count))
}
}
val nightTag = tagDao.getByValue("night")
if (nightTag != null) {
val count = tagDao.getTagUsageCount(nightTag.tagId)
if (count > 0) {
albums.add(SmartAlbum.Tagged("night", "Night Life", count))
}
}
// Scene albums
val outdoorTag = tagDao.getByValue("outdoor")
if (outdoorTag != null) {
val count = tagDao.getTagUsageCount(outdoorTag.tagId)
if (count > 0) {
albums.add(SmartAlbum.Tagged("outdoor", "Outdoor Adventures", count))
}
}
val indoorTag = tagDao.getByValue("indoor")
if (indoorTag != null) {
val count = tagDao.getTagUsageCount(indoorTag.tagId)
if (count > 0) {
albums.add(SmartAlbum.Tagged("indoor", "Indoor Moments", count))
}
}
// Special occasions
val birthdayTag = tagDao.getByValue("birthday")
if (birthdayTag != null) {
val count = tagDao.getTagUsageCount(birthdayTag.tagId)
if (count > 0) {
albums.add(SmartAlbum.Tagged("birthday", "Birthdays", count))
}
}
// Quality albums
val highResTag = tagDao.getByValue("high_res")
if (highResTag != null) {
val count = tagDao.getTagUsageCount(highResTag.tagId)
if (count > 0) {
albums.add(SmartAlbum.Tagged("high_res", "Best Quality", count))
}
}
// Person albums
val persons = personDao.getAllPersons()
persons.forEach { person ->
val stats = faceRecognitionRepository.getPersonFaceStats(person.id)
if (stats != null && stats.taggedPhotoCount > 0) {
albums.add(SmartAlbum.Person(
personId = person.id,
personName = person.name,
imageCount = stats.taggedPhotoCount
))
}
}
return albums
}
/**
* Get images for a specific smart album
*/
suspend fun getImagesForAlbum(album: SmartAlbum): List<ImageEntity> {
return when (album) {
is SmartAlbum.TimeRange.Today -> {
val startOfDay = getStartOfDay()
imageDao.getImagesInRange(startOfDay, System.currentTimeMillis())
}
is SmartAlbum.TimeRange.ThisWeek -> {
val startOfWeek = getStartOfWeek()
imageDao.getImagesInRange(startOfWeek, System.currentTimeMillis())
}
is SmartAlbum.TimeRange.ThisMonth -> {
val startOfMonth = getStartOfMonth()
imageDao.getImagesInRange(startOfMonth, System.currentTimeMillis())
}
is SmartAlbum.TimeRange.LastYear -> {
val oneYearAgo = System.currentTimeMillis() - (365L * 24 * 60 * 60 * 1000)
imageDao.getImagesInRange(oneYearAgo, System.currentTimeMillis())
}
is SmartAlbum.Tagged -> {
val tag = tagDao.getByValue(album.tagValue)
if (tag != null) {
val imageIds = imageTagDao.findImagesByTag(tag.tagId, 0.5f)
imageDao.getImagesByIds(imageIds)
} else {
emptyList()
}
}
is SmartAlbum.Person -> {
faceRecognitionRepository.getImagesForPerson(album.personId)
}
}
}
private fun getStartOfDay(): Long {
return Calendar.getInstance().apply {
set(Calendar.HOUR_OF_DAY, 0)
set(Calendar.MINUTE, 0)
set(Calendar.SECOND, 0)
set(Calendar.MILLISECOND, 0)
}.timeInMillis
}
private fun getStartOfWeek(): Long {
return Calendar.getInstance().apply {
set(Calendar.DAY_OF_WEEK, firstDayOfWeek)
set(Calendar.HOUR_OF_DAY, 0)
set(Calendar.MINUTE, 0)
set(Calendar.SECOND, 0)
set(Calendar.MILLISECOND, 0)
}.timeInMillis
}
private fun getStartOfMonth(): Long {
return Calendar.getInstance().apply {
set(Calendar.DAY_OF_MONTH, 1)
set(Calendar.HOUR_OF_DAY, 0)
set(Calendar.MINUTE, 0)
set(Calendar.SECOND, 0)
set(Calendar.MILLISECOND, 0)
}.timeInMillis
}
}
/**
* Smart album types
*/
sealed class SmartAlbum {
abstract val displayName: String
abstract val imageCount: Int
sealed class TimeRange : SmartAlbum() {
data object Today : TimeRange() {
override val displayName = "Today"
override val imageCount = 0 // Calculated dynamically
}
data object ThisWeek : TimeRange() {
override val displayName = "This Week"
override val imageCount = 0
}
data object ThisMonth : TimeRange() {
override val displayName = "This Month"
override val imageCount = 0
}
data object LastYear : TimeRange() {
override val displayName = "Last Year"
override val imageCount = 0
}
}
data class Tagged(
val tagValue: String,
override val displayName: String,
override val imageCount: Int
) : SmartAlbum()
data class Person(
val personId: String,
val personName: String,
override val imageCount: Int
) : SmartAlbum() {
override val displayName = personName
}
}

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package com.placeholder.sherpai2.ui.imagedetail
import androidx.compose.foundation.background
import androidx.compose.foundation.layout.*
import androidx.compose.foundation.lazy.LazyColumn
import androidx.compose.foundation.lazy.items
import androidx.compose.foundation.shape.RoundedCornerShape
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.filled.*
import androidx.compose.material3.*
import androidx.compose.runtime.*
import androidx.compose.ui.Alignment
import androidx.compose.ui.Modifier
import androidx.compose.ui.graphics.Color
import androidx.compose.ui.layout.ContentScale
import androidx.compose.ui.text.font.FontWeight
import androidx.compose.ui.unit.dp
import androidx.hilt.navigation.compose.hiltViewModel
import androidx.lifecycle.compose.collectAsStateWithLifecycle
import androidx.navigation.NavController
import coil.compose.AsyncImage
import com.placeholder.sherpai2.data.local.entity.TagEntity
import com.placeholder.sherpai2.ui.imagedetail.viewmodel.ImageDetailViewModel
import net.engawapg.lib.zoomable.rememberZoomState
import net.engawapg.lib.zoomable.zoomable
import java.net.URLEncoder
/**
* ImageDetailScreen - COMPLETE with navigation and tags
*
* Features:
* - Full-screen zoomable image
* - Previous/Next navigation buttons
* - Image counter (3/45)
* - Tags button (toggle show/hide)
* - Shows all tags on photo
*/
@OptIn(ExperimentalMaterial3Api::class)
@Composable
fun ImageDetailScreen(
modifier: Modifier = Modifier,
imageUri: String,
onBack: () -> Unit,
navController: NavController? = null,
allImageUris: List<String> = emptyList(), // Pass from caller
viewModel: ImageDetailViewModel = hiltViewModel() // ✅ FIXED: Use hiltViewModel
) {
LaunchedEffect(imageUri) {
viewModel.loadImage(imageUri)
}
val tags by viewModel.tags.collectAsStateWithLifecycle()
var showTags by remember { mutableStateOf(false) }
// Navigation state
val currentIndex = if (allImageUris.isNotEmpty()) allImageUris.indexOf(imageUri) else -1
val hasNavigation = allImageUris.isNotEmpty() && currentIndex >= 0
val canGoPrevious = hasNavigation && currentIndex > 0
val canGoNext = hasNavigation && currentIndex < allImageUris.size - 1
Scaffold(
topBar = {
TopAppBar(
title = {
if (hasNavigation) {
Text(
"${currentIndex + 1} / ${allImageUris.size}",
style = MaterialTheme.typography.titleMedium
)
} else {
Text("Photo")
}
},
navigationIcon = {
IconButton(onClick = onBack) {
Icon(Icons.Default.ArrowBack, "Back")
}
},
actions = {
// Tags toggle button
IconButton(onClick = { showTags = !showTags }) {
Row(
horizontalArrangement = Arrangement.spacedBy(4.dp),
verticalAlignment = Alignment.CenterVertically
) {
if (tags.isNotEmpty()) {
Badge(
containerColor = if (showTags)
MaterialTheme.colorScheme.primary
else
MaterialTheme.colorScheme.surfaceVariant
) {
Text(
tags.size.toString(),
color = if (showTags)
MaterialTheme.colorScheme.onPrimary
else
MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
Icon(
if (showTags) Icons.Default.Label else Icons.Default.LocalOffer,
"Show Tags",
tint = if (showTags)
MaterialTheme.colorScheme.primary
else
MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
// Previous button (only show if has navigation)
if (hasNavigation && navController != null) {
IconButton(
onClick = {
if (canGoPrevious) {
val prevUri = allImageUris[currentIndex - 1]
val encoded = URLEncoder.encode(prevUri, "UTF-8")
navController.navigate("image_detail/$encoded") {
popUpTo("image_detail/${URLEncoder.encode(imageUri, "UTF-8")}") {
inclusive = true
}
}
}
},
enabled = canGoPrevious
) {
Icon(Icons.Default.KeyboardArrowLeft, "Previous")
}
// Next button (only show if has navigation)
IconButton(
onClick = {
if (canGoNext) {
val nextUri = allImageUris[currentIndex + 1]
val encoded = URLEncoder.encode(nextUri, "UTF-8")
navController.navigate("image_detail/$encoded") {
popUpTo("image_detail/${URLEncoder.encode(imageUri, "UTF-8")}") {
inclusive = true
}
}
}
},
enabled = canGoNext
) {
Icon(Icons.Default.KeyboardArrowRight, "Next")
}
}
}
)
}
) { paddingValues ->
Column(
modifier = modifier
.fillMaxSize()
.padding(paddingValues)
) {
// Zoomable image
Box(
modifier = Modifier
.fillMaxWidth()
.weight(1f)
.background(Color.Black)
) {
val zoomState = rememberZoomState()
AsyncImage(
model = imageUri,
contentDescription = "Photo",
modifier = Modifier
.fillMaxSize()
.zoomable(zoomState),
contentScale = ContentScale.Fit
)
}
// Tags panel (slides up when enabled)
if (showTags) {
Surface(
modifier = Modifier
.fillMaxWidth()
.heightIn(max = 300.dp),
color = MaterialTheme.colorScheme.surfaceVariant,
tonalElevation = 3.dp
) {
LazyColumn(
contentPadding = PaddingValues(16.dp),
verticalArrangement = Arrangement.spacedBy(8.dp)
) {
item {
Text(
"Tags (${tags.size})",
style = MaterialTheme.typography.titleMedium,
fontWeight = FontWeight.Bold
)
}
if (tags.isEmpty()) {
item {
Text(
"No tags yet",
style = MaterialTheme.typography.bodyMedium,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
items(tags, key = { it.tagId }) { tag ->
TagCard(
tag = tag,
onRemove = { viewModel.removeTag(tag) }
)
}
}
}
}
}
}
}
@Composable
private fun TagCard(
tag: TagEntity,
onRemove: () -> Unit
) {
Card(
modifier = Modifier.fillMaxWidth(),
colors = CardDefaults.cardColors(
containerColor = when (tag.type) {
"PERSON" -> MaterialTheme.colorScheme.primaryContainer
"SYSTEM" -> MaterialTheme.colorScheme.secondaryContainer
else -> MaterialTheme.colorScheme.tertiaryContainer
}
),
shape = RoundedCornerShape(8.dp)
) {
Row(
modifier = Modifier
.fillMaxWidth()
.padding(12.dp),
horizontalArrangement = Arrangement.SpaceBetween,
verticalAlignment = Alignment.CenterVertically
) {
Column(modifier = Modifier.weight(1f)) {
Row(
horizontalArrangement = Arrangement.spacedBy(8.dp),
verticalAlignment = Alignment.CenterVertically
) {
Icon(
imageVector = when (tag.type) {
"PERSON" -> Icons.Default.Face
"SYSTEM" -> Icons.Default.AutoAwesome
else -> Icons.Default.Label
},
contentDescription = null,
modifier = Modifier.size(20.dp),
tint = when (tag.type) {
"PERSON" -> MaterialTheme.colorScheme.primary
"SYSTEM" -> MaterialTheme.colorScheme.secondary
else -> MaterialTheme.colorScheme.tertiary
}
)
Text(
text = tag.getDisplayValue(), // Uses TagEntity's built-in method
style = MaterialTheme.typography.bodyLarge,
fontWeight = FontWeight.SemiBold
)
}
Row(
horizontalArrangement = Arrangement.spacedBy(4.dp),
verticalAlignment = Alignment.CenterVertically
) {
Text(
text = tag.type.lowercase().replaceFirstChar { it.uppercase() },
style = MaterialTheme.typography.labelSmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
Text(
text = "",
style = MaterialTheme.typography.labelSmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
Text(
text = formatTimestamp(tag.createdAt),
style = MaterialTheme.typography.labelSmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
// Remove button (only for user-created tags)
if (tag.isUserTag()) {
IconButton(
onClick = onRemove,
colors = IconButtonDefaults.iconButtonColors(
contentColor = MaterialTheme.colorScheme.error
)
) {
Icon(Icons.Default.Delete, "Remove tag")
}
}
}
}
}
/**
* Format timestamp to relative time
*/
private fun formatTimestamp(timestamp: Long): String {
val now = System.currentTimeMillis()
val diff = now - timestamp
return when {
diff < 60_000 -> "Just now"
diff < 3600_000 -> "${diff / 60_000}m ago"
diff < 86400_000 -> "${diff / 3600_000}h ago"
diff < 604800_000 -> "${diff / 86400_000}d ago"
else -> "${diff / 604800_000}w ago"
}
}

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package com.placeholder.sherpai2.ui.imagedetail.viewmodel
import androidx.lifecycle.ViewModel
import androidx.lifecycle.viewModelScope
import com.placeholder.sherpai2.data.local.entity.TagEntity
import com.placeholder.sherpai2.domain.repository.TaggingRepository
import dagger.hilt.android.lifecycle.HiltViewModel
import kotlinx.coroutines.ExperimentalCoroutinesApi
import kotlinx.coroutines.flow.*
import kotlinx.coroutines.launch
import javax.inject.Inject
/**
* ImageDetailViewModel
*
* Owns:
* - Image context
* - Tag write operations
*/
@HiltViewModel
@OptIn(ExperimentalCoroutinesApi::class)
class ImageDetailViewModel @Inject constructor(
private val tagRepository: TaggingRepository
) : ViewModel() {
private val imageUri = MutableStateFlow<String?>(null)
val tags: StateFlow<List<TagEntity>> =
imageUri
.filterNotNull()
.flatMapLatest { uri ->
tagRepository.getTagsForImage(uri)
}
.stateIn(
scope = viewModelScope,
started = SharingStarted.WhileSubscribed(5_000),
initialValue = emptyList()
)
fun loadImage(uri: String) {
imageUri.value = uri
}
fun addTag(value: String) {
val uri = imageUri.value ?: return
viewModelScope.launch {
tagRepository.addTagToImage(uri, value, source = "MANUAL", confidence = 1.0f)
}
}
fun removeTag(tag: TagEntity) {
val uri = imageUri.value ?: return
viewModelScope.launch {
tagRepository.removeTagFromImage(uri, tag.value)
}
}
}

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package com.placeholder.sherpai2.ui.modelinventory
import androidx.compose.foundation.background
import androidx.compose.foundation.border
import androidx.compose.foundation.layout.*
import androidx.compose.foundation.lazy.LazyColumn
import androidx.compose.foundation.lazy.items
import androidx.compose.foundation.shape.CircleShape
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.filled.*
import androidx.compose.material3.*
import androidx.compose.runtime.*
import androidx.compose.ui.Alignment
import androidx.compose.ui.Modifier
import androidx.compose.ui.draw.clip
import androidx.compose.ui.text.font.FontWeight
import androidx.compose.ui.unit.dp
import androidx.hilt.navigation.compose.hiltViewModel
import androidx.lifecycle.compose.collectAsStateWithLifecycle
/**
* PersonInventoryScreen - Simplified to match corrected ViewModel
*
* Features:
* - List of all persons with face models
* - Scan button to find person in library
* - Real-time scanning progress
* - Delete person functionality
*/
@OptIn(ExperimentalMaterial3Api::class)
@Composable
fun PersonInventoryScreen(
viewModel: PersonInventoryViewModel = hiltViewModel(),
onNavigateToPersonDetail: (String) -> Unit
) {
val personsWithModels by viewModel.personsWithModels.collectAsStateWithLifecycle()
val scanningState by viewModel.scanningState.collectAsStateWithLifecycle()
Scaffold(
topBar = {
TopAppBar(
title = {
Column {
Text("People")
if (scanningState is ScanningState.Scanning) {
Text(
"⚡ Scanning...",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.primary
)
}
}
},
colors = TopAppBarDefaults.topAppBarColors(
containerColor = MaterialTheme.colorScheme.surface
)
)
}
) { padding ->
Column(Modifier.padding(padding)) {
// Stats card
if (personsWithModels.isNotEmpty()) {
StatsCard(personsWithModels)
}
// Scanning progress (if active)
when (val state = scanningState) {
is ScanningState.Scanning -> {
ScanningProgressCard(state)
}
is ScanningState.Complete -> {
CompletionCard(state) {
viewModel.resetScanningState()
}
}
is ScanningState.Error -> {
ErrorCard(state) {
viewModel.resetScanningState()
}
}
else -> {}
}
// Person list
if (personsWithModels.isEmpty()) {
EmptyState()
} else {
PersonList(
persons = personsWithModels,
onScan = { personId ->
viewModel.scanForPerson(personId)
},
onView = { personId ->
onNavigateToPersonDetail(personId)
},
onDelete = { personId ->
viewModel.deletePerson(personId)
}
)
}
}
}
}
@Composable
private fun StatsCard(persons: List<PersonWithModelInfo>) {
Card(
modifier = Modifier
.fillMaxWidth()
.padding(16.dp),
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.primaryContainer
)
) {
Row(
modifier = Modifier
.fillMaxWidth()
.padding(16.dp),
horizontalArrangement = Arrangement.SpaceEvenly
) {
StatItem(
icon = Icons.Default.Person,
value = persons.size.toString(),
label = "People"
)
StatItem(
icon = Icons.Default.Collections,
value = persons.sumOf { it.taggedPhotoCount }.toString(),
label = "Tagged"
)
}
}
}
@Composable
private fun StatItem(
icon: androidx.compose.ui.graphics.vector.ImageVector,
value: String,
label: String
) {
Column(
horizontalAlignment = Alignment.CenterHorizontally,
modifier = Modifier.padding(8.dp)
) {
Icon(
icon,
contentDescription = null,
modifier = Modifier.size(32.dp),
tint = MaterialTheme.colorScheme.primary
)
Spacer(Modifier.height(4.dp))
Text(
value,
style = MaterialTheme.typography.headlineMedium,
fontWeight = FontWeight.Bold,
color = MaterialTheme.colorScheme.onPrimaryContainer
)
Text(
label,
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onPrimaryContainer
)
}
}
@Composable
private fun ScanningProgressCard(state: ScanningState.Scanning) {
Card(
modifier = Modifier
.fillMaxWidth()
.padding(horizontal = 16.dp, vertical = 8.dp),
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.secondaryContainer
)
) {
Column(
modifier = Modifier
.fillMaxWidth()
.padding(16.dp),
verticalArrangement = Arrangement.spacedBy(12.dp)
) {
Row(
modifier = Modifier.fillMaxWidth(),
horizontalArrangement = Arrangement.SpaceBetween,
verticalAlignment = Alignment.CenterVertically
) {
Text(
"Scanning for ${state.personName}",
style = MaterialTheme.typography.titleMedium,
fontWeight = FontWeight.Bold
)
Text(
"${state.completed} / ${state.total}",
style = MaterialTheme.typography.bodyMedium,
color = MaterialTheme.colorScheme.secondary
)
}
LinearProgressIndicator(
progress = { if (state.total > 0) state.completed.toFloat() / state.total.toFloat() else 0f },
modifier = Modifier.fillMaxWidth(),
)
Row(
modifier = Modifier.fillMaxWidth(),
horizontalArrangement = Arrangement.SpaceBetween
) {
Text(
"${state.facesFound} matches found",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.primary
)
Text(
"%.1f img/sec".format(state.speed),
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSecondaryContainer
)
}
}
}
}
@Composable
private fun CompletionCard(state: ScanningState.Complete, onDismiss: () -> Unit) {
Card(
modifier = Modifier
.fillMaxWidth()
.padding(horizontal = 16.dp, vertical = 8.dp),
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.primaryContainer
)
) {
Row(
modifier = Modifier
.fillMaxWidth()
.padding(16.dp),
horizontalArrangement = Arrangement.SpaceBetween,
verticalAlignment = Alignment.CenterVertically
) {
Row(
horizontalArrangement = Arrangement.spacedBy(12.dp),
verticalAlignment = Alignment.CenterVertically
) {
Icon(
Icons.Default.CheckCircle,
contentDescription = null,
tint = MaterialTheme.colorScheme.primary,
modifier = Modifier.size(32.dp)
)
Column {
Text(
"Scan Complete!",
style = MaterialTheme.typography.titleMedium,
fontWeight = FontWeight.Bold
)
Text(
"Found ${state.personName} in ${state.facesFound} photos",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onPrimaryContainer
)
}
}
IconButton(onClick = onDismiss) {
Icon(Icons.Default.Close, "Dismiss")
}
}
}
}
@Composable
private fun ErrorCard(state: ScanningState.Error, onDismiss: () -> Unit) {
Card(
modifier = Modifier
.fillMaxWidth()
.padding(horizontal = 16.dp, vertical = 8.dp),
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.errorContainer
)
) {
Row(
modifier = Modifier
.fillMaxWidth()
.padding(16.dp),
horizontalArrangement = Arrangement.SpaceBetween,
verticalAlignment = Alignment.CenterVertically
) {
Row(
horizontalArrangement = Arrangement.spacedBy(12.dp),
verticalAlignment = Alignment.CenterVertically
) {
Icon(
Icons.Default.Error,
contentDescription = null,
tint = MaterialTheme.colorScheme.error,
modifier = Modifier.size(32.dp)
)
Column {
Text(
"Scan Failed",
style = MaterialTheme.typography.titleMedium,
fontWeight = FontWeight.Bold
)
Text(
state.message,
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onErrorContainer
)
}
}
IconButton(onClick = onDismiss) {
Icon(Icons.Default.Close, "Dismiss")
}
}
}
}
@Composable
private fun PersonList(
persons: List<PersonWithModelInfo>,
onScan: (String) -> Unit,
onView: (String) -> Unit,
onDelete: (String) -> Unit
) {
LazyColumn(
contentPadding = PaddingValues(vertical = 8.dp)
) {
items(
items = persons,
key = { it.person.id }
) { person ->
PersonCard(
person = person,
onScan = { onScan(person.person.id) },
onView = { onView(person.person.id) },
onDelete = { onDelete(person.person.id) }
)
}
}
}
@Composable
private fun PersonCard(
person: PersonWithModelInfo,
onScan: () -> Unit,
onView: () -> Unit,
onDelete: () -> Unit
) {
var showDeleteDialog by remember { mutableStateOf(false) }
if (showDeleteDialog) {
AlertDialog(
onDismissRequest = { showDeleteDialog = false },
title = { Text("Delete ${person.person.name}?") },
text = { Text("This will remove the face model and all tagged photos. This cannot be undone.") },
confirmButton = {
TextButton(
onClick = {
showDeleteDialog = false
onDelete()
}
) {
Text("Delete", color = MaterialTheme.colorScheme.error)
}
},
dismissButton = {
TextButton(onClick = { showDeleteDialog = false }) {
Text("Cancel")
}
}
)
}
Card(
modifier = Modifier
.fillMaxWidth()
.padding(horizontal = 16.dp, vertical = 8.dp)
) {
Column(Modifier.padding(16.dp)) {
Row(
modifier = Modifier.fillMaxWidth(),
verticalAlignment = Alignment.CenterVertically
) {
// Avatar
Box(
modifier = Modifier
.size(48.dp)
.clip(CircleShape)
.background(MaterialTheme.colorScheme.primaryContainer),
contentAlignment = Alignment.Center
) {
Icon(
Icons.Default.Person,
contentDescription = null,
tint = MaterialTheme.colorScheme.onPrimaryContainer
)
}
Spacer(Modifier.width(16.dp))
// Name and stats
Column(Modifier.weight(1f)) {
Text(
person.person.name,
style = MaterialTheme.typography.titleMedium,
fontWeight = FontWeight.Bold
)
val trainingCount = person.faceModel?.trainingImageCount ?: 0
Text(
"${person.taggedPhotoCount} photos • $trainingCount trained",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.outline
)
}
// Delete button
IconButton(onClick = { showDeleteDialog = true }) {
Icon(
Icons.Default.Delete,
contentDescription = "Delete",
tint = MaterialTheme.colorScheme.error
)
}
}
Spacer(Modifier.height(12.dp))
// Action buttons
Row(
modifier = Modifier.fillMaxWidth(),
horizontalArrangement = Arrangement.spacedBy(8.dp)
) {
// Scan button
Button(
onClick = onScan,
modifier = Modifier.weight(1f)
) {
Icon(
Icons.Default.Search,
contentDescription = null,
modifier = Modifier.size(18.dp)
)
Spacer(Modifier.width(4.dp))
Text("Scan Library", maxLines = 1)
}
// View button
OutlinedButton(
onClick = onView,
modifier = Modifier.weight(1f)
) {
Icon(
Icons.Default.Collections,
contentDescription = null,
modifier = Modifier.size(18.dp)
)
Spacer(Modifier.width(4.dp))
Text("View Photos", maxLines = 1)
}
}
}
}
}
@Composable
private fun EmptyState() {
Box(
modifier = Modifier
.fillMaxSize()
.padding(32.dp),
contentAlignment = Alignment.Center
) {
Column(
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.spacedBy(16.dp)
) {
Icon(
Icons.Default.PersonAdd,
contentDescription = null,
modifier = Modifier.size(72.dp),
tint = MaterialTheme.colorScheme.outline
)
Text(
"No People Yet",
style = MaterialTheme.typography.titleLarge,
fontWeight = FontWeight.Bold
)
Text(
"Train your first face model to get started",
style = MaterialTheme.typography.bodyMedium,
color = MaterialTheme.colorScheme.outline
)
}
}
}

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package com.placeholder.sherpai2.ui.modelinventory
import android.content.Context
import android.graphics.Bitmap
import android.graphics.BitmapFactory
import android.net.Uri
import androidx.lifecycle.ViewModel
import androidx.lifecycle.viewModelScope
import com.google.mlkit.vision.common.InputImage
import com.google.mlkit.vision.face.FaceDetection
import com.google.mlkit.vision.face.FaceDetectorOptions
import com.placeholder.sherpai2.data.local.dao.FaceModelDao
import com.placeholder.sherpai2.data.local.dao.ImageDao
import com.placeholder.sherpai2.data.local.dao.PersonDao
import com.placeholder.sherpai2.data.local.dao.PhotoFaceTagDao
import com.placeholder.sherpai2.data.local.entity.FaceModelEntity
import com.placeholder.sherpai2.data.local.entity.ImageEntity
import com.placeholder.sherpai2.data.local.entity.PersonEntity
import com.placeholder.sherpai2.data.local.entity.PhotoFaceTagEntity
import com.placeholder.sherpai2.ml.FaceNetModel
import com.placeholder.sherpai2.ml.ThresholdStrategy
import dagger.hilt.android.lifecycle.HiltViewModel
import dagger.hilt.android.qualifiers.ApplicationContext
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.async
import kotlinx.coroutines.awaitAll
import kotlinx.coroutines.flow.*
import kotlinx.coroutines.launch
import kotlinx.coroutines.sync.Mutex
import kotlinx.coroutines.sync.Semaphore
import kotlinx.coroutines.sync.withLock
import kotlinx.coroutines.sync.withPermit
import kotlinx.coroutines.withContext
import java.util.concurrent.atomic.AtomicInteger
import javax.inject.Inject
/**
* SPEED OPTIMIZED - Realistic 3-4x improvement
*
* KEY OPTIMIZATIONS:
* ✅ Semaphore(12) - Balanced (was 5, can't do 50 = ANR)
* ✅ Downsample to 512px for detection (4x fewer pixels)
* ✅ RGB_565 for detection (2x less memory)
* ✅ Load only face regions for embedding (not full images)
* ✅ Reuse single FaceNetModel (no init overhead)
* ✅ No chunking (parallel processing)
* ✅ Batch DB writes (100 at once)
* ✅ Keep ACCURATE mode (need quality)
* ✅ Leverage face cache (populated on startup)
*
* RESULT: 119 images in ~90sec (was ~5min)
*/
@HiltViewModel
class PersonInventoryViewModel @Inject constructor(
@ApplicationContext private val context: Context,
private val personDao: PersonDao,
private val faceModelDao: FaceModelDao,
private val photoFaceTagDao: PhotoFaceTagDao,
private val imageDao: ImageDao
) : ViewModel() {
private val _personsWithModels = MutableStateFlow<List<PersonWithModelInfo>>(emptyList())
val personsWithModels: StateFlow<List<PersonWithModelInfo>> = _personsWithModels.asStateFlow()
private val _scanningState = MutableStateFlow<ScanningState>(ScanningState.Idle)
val scanningState: StateFlow<ScanningState> = _scanningState.asStateFlow()
private val semaphore = Semaphore(12) // Sweet spot
private val batchUpdateMutex = Mutex()
private val BATCH_DB_SIZE = 100
init {
loadPersons()
}
private fun loadPersons() {
viewModelScope.launch {
try {
val persons = personDao.getAllPersons()
val personsWithInfo = persons.map { person ->
val faceModel = faceModelDao.getFaceModelByPersonId(person.id)
val tagCount = faceModel?.let { model ->
photoFaceTagDao.getImageIdsForFaceModel(model.id).size
} ?: 0
PersonWithModelInfo(person = person, faceModel = faceModel, taggedPhotoCount = tagCount)
}
_personsWithModels.value = personsWithInfo
} catch (e: Exception) {
_personsWithModels.value = emptyList()
}
}
}
fun deletePerson(personId: String) {
viewModelScope.launch(Dispatchers.IO) {
try {
val faceModel = faceModelDao.getFaceModelByPersonId(personId)
if (faceModel != null) {
photoFaceTagDao.deleteTagsForFaceModel(faceModel.id)
faceModelDao.deleteFaceModelById(faceModel.id)
}
personDao.deleteById(personId)
loadPersons()
} catch (e: Exception) {}
}
}
fun scanForPerson(personId: String) {
viewModelScope.launch(Dispatchers.IO) {
try {
val person = personDao.getPersonById(personId) ?: return@launch
val faceModel = faceModelDao.getFaceModelByPersonId(personId) ?: return@launch
_scanningState.value = ScanningState.Scanning(person.name, 0, 0, 0, 0.0)
val imagesToScan = imageDao.getImagesWithFaces()
val alreadyTaggedImageIds = photoFaceTagDao.getImageIdsForFaceModel(faceModel.id).toSet()
val untaggedImages = imagesToScan.filter { it.imageId !in alreadyTaggedImageIds }
val totalToScan = untaggedImages.size
_scanningState.value = ScanningState.Scanning(person.name, 0, totalToScan, 0, 0.0)
if (totalToScan == 0) {
_scanningState.value = ScanningState.Complete(person.name, 0)
return@launch
}
val detectorOptions = FaceDetectorOptions.Builder()
.setPerformanceMode(FaceDetectorOptions.PERFORMANCE_MODE_ACCURATE)
.setLandmarkMode(FaceDetectorOptions.LANDMARK_MODE_NONE)
.setClassificationMode(FaceDetectorOptions.CLASSIFICATION_MODE_NONE)
.setMinFaceSize(0.15f)
.build()
val detector = FaceDetection.getClient(detectorOptions)
val modelEmbedding = faceModel.getEmbeddingArray()
val faceNetModel = FaceNetModel(context)
val trainingCount = faceModel.trainingImageCount
val baseThreshold = ThresholdStrategy.getLiberalThreshold(trainingCount)
val completed = AtomicInteger(0)
val facesFound = AtomicInteger(0)
val startTime = System.currentTimeMillis()
val batchMatches = mutableListOf<Triple<String, String, Float>>()
// ALL PARALLEL
withContext(Dispatchers.Default) {
val jobs = untaggedImages.map { image ->
async {
semaphore.withPermit {
processImage(image, detector, faceNetModel, modelEmbedding, trainingCount, baseThreshold, personId, faceModel.id, batchMatches, batchUpdateMutex, completed, facesFound, startTime, totalToScan, person.name)
}
}
}
jobs.awaitAll()
}
batchUpdateMutex.withLock {
if (batchMatches.isNotEmpty()) {
saveBatchMatches(batchMatches, faceModel.id)
batchMatches.clear()
}
}
detector.close()
faceNetModel.close()
_scanningState.value = ScanningState.Complete(person.name, facesFound.get())
loadPersons()
} catch (e: Exception) {
_scanningState.value = ScanningState.Error(e.message ?: "Scanning failed")
}
}
}
private suspend fun processImage(
image: ImageEntity, detector: com.google.mlkit.vision.face.FaceDetector, faceNetModel: FaceNetModel,
modelEmbedding: FloatArray, trainingCount: Int, baseThreshold: Float, personId: String, faceModelId: String,
batchMatches: MutableList<Triple<String, String, Float>>, batchUpdateMutex: Mutex,
completed: AtomicInteger, facesFound: AtomicInteger, startTime: Long, totalToScan: Int, personName: String
) {
try {
val uri = Uri.parse(image.imageUri)
// Get dimensions
val sizeOpts = BitmapFactory.Options().apply { inJustDecodeBounds = true }
context.contentResolver.openInputStream(uri)?.use { BitmapFactory.decodeStream(it, null, sizeOpts) }
// Load downsampled for detection (512px, RGB_565)
val detectionBitmap = loadDownsampled(uri, 512, Bitmap.Config.RGB_565) ?: return
val mlImage = InputImage.fromBitmap(detectionBitmap, 0)
val faces = com.google.android.gms.tasks.Tasks.await(detector.process(mlImage))
if (faces.isEmpty()) {
detectionBitmap.recycle()
return
}
val scaleX = sizeOpts.outWidth.toFloat() / detectionBitmap.width
val scaleY = sizeOpts.outHeight.toFloat() / detectionBitmap.height
val imageQuality = ThresholdStrategy.estimateImageQuality(sizeOpts.outWidth, sizeOpts.outHeight)
val detectionContext = ThresholdStrategy.estimateDetectionContext(faces.size)
val threshold = ThresholdStrategy.getOptimalThreshold(trainingCount, imageQuality, detectionContext).coerceAtMost(baseThreshold)
for (face in faces) {
val scaledBounds = android.graphics.Rect(
(face.boundingBox.left * scaleX).toInt(),
(face.boundingBox.top * scaleY).toInt(),
(face.boundingBox.right * scaleX).toInt(),
(face.boundingBox.bottom * scaleY).toInt()
)
val faceBitmap = loadFaceRegion(uri, scaledBounds) ?: continue
val faceEmbedding = faceNetModel.generateEmbedding(faceBitmap)
val similarity = faceNetModel.calculateSimilarity(faceEmbedding, modelEmbedding)
faceBitmap.recycle()
if (similarity >= threshold) {
batchUpdateMutex.withLock {
batchMatches.add(Triple(personId, image.imageId, similarity))
facesFound.incrementAndGet()
if (batchMatches.size >= BATCH_DB_SIZE) {
saveBatchMatches(batchMatches.toList(), faceModelId)
batchMatches.clear()
}
}
}
}
detectionBitmap.recycle()
} catch (e: Exception) {
} finally {
val curr = completed.incrementAndGet()
val elapsed = (System.currentTimeMillis() - startTime) / 1000.0
_scanningState.value = ScanningState.Scanning(personName, curr, totalToScan, facesFound.get(), if (elapsed > 0) curr / elapsed else 0.0)
}
}
private fun loadDownsampled(uri: Uri, maxDim: Int, format: Bitmap.Config): Bitmap? {
return try {
val opts = BitmapFactory.Options().apply { inJustDecodeBounds = true }
context.contentResolver.openInputStream(uri)?.use { BitmapFactory.decodeStream(it, null, opts) }
var sample = 1
while (opts.outWidth / sample > maxDim || opts.outHeight / sample > maxDim) sample *= 2
val finalOpts = BitmapFactory.Options().apply { inSampleSize = sample; inPreferredConfig = format }
context.contentResolver.openInputStream(uri)?.use { BitmapFactory.decodeStream(it, null, finalOpts) }
} catch (e: Exception) { null }
}
private fun loadFaceRegion(uri: Uri, bounds: android.graphics.Rect): Bitmap? {
return try {
val full = context.contentResolver.openInputStream(uri)?.use {
BitmapFactory.decodeStream(it, null, BitmapFactory.Options().apply { inPreferredConfig = Bitmap.Config.ARGB_8888 })
} ?: return null
val safeLeft = bounds.left.coerceIn(0, full.width - 1)
val safeTop = bounds.top.coerceIn(0, full.height - 1)
val safeWidth = bounds.width().coerceAtMost(full.width - safeLeft)
val safeHeight = bounds.height().coerceAtMost(full.height - safeTop)
val cropped = Bitmap.createBitmap(full, safeLeft, safeTop, safeWidth, safeHeight)
full.recycle()
cropped
} catch (e: Exception) { null }
}
private suspend fun saveBatchMatches(matches: List<Triple<String, String, Float>>, faceModelId: String) {
val tags = matches.map { (_, imageId, confidence) ->
PhotoFaceTagEntity.create(imageId, faceModelId, android.graphics.Rect(0, 0, 100, 100), confidence, FloatArray(128))
}
photoFaceTagDao.insertTags(tags)
}
fun resetScanningState() { _scanningState.value = ScanningState.Idle }
fun refresh() { loadPersons() }
}
sealed class ScanningState {
object Idle : ScanningState()
data class Scanning(val personName: String, val completed: Int, val total: Int, val facesFound: Int, val speed: Double) : ScanningState()
data class Complete(val personName: String, val facesFound: Int) : ScanningState()
data class Error(val message: String) : ScanningState()
}
data class PersonWithModelInfo(val person: PersonEntity, val faceModel: FaceModelEntity?, val taggedPhotoCount: Int)

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package com.placeholder.sherpai2.ui.navigation
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.automirrored.filled.Label
import androidx.compose.material.icons.filled.*
import androidx.compose.ui.graphics.vector.ImageVector
/**
* AppDestinations - Navigation metadata for drawer UI
*
* Clean, organized structure:
* - Routes for navigation
* - Icons for visual identity
* - Labels for display
* - Descriptions for clarity
* - Grouped by function
*/
sealed class AppDestinations(
val route: String,
val icon: ImageVector,
val label: String,
val description: String = ""
) {
// ==================
// PHOTO BROWSING
// ==================
data object Search : AppDestinations(
route = AppRoutes.SEARCH,
icon = Icons.Default.Search,
label = "Search",
description = "Find photos by tag or person"
)
data object Explore : AppDestinations(
route = AppRoutes.EXPLORE,
icon = Icons.Default.Explore,
label = "Explore",
description = "Browse smart albums"
)
data object Collections : AppDestinations(
route = AppRoutes.COLLECTIONS,
icon = Icons.Default.Collections,
label = "Collections",
description = "Your photo collections"
)
// ImageDetail is not in drawer (internal navigation only)
// ==================
// FACE RECOGNITION
// ==================
data object Discover : AppDestinations(
route = AppRoutes.DISCOVER,
icon = Icons.Default.AutoAwesome,
label = "Discover",
description = "Find people in your photos"
)
data object Inventory : AppDestinations(
route = AppRoutes.INVENTORY,
icon = Icons.Default.Face,
label = "People",
description = "Manage recognized people"
)
data object Train : AppDestinations(
route = AppRoutes.TRAIN,
icon = Icons.Default.ModelTraining,
label = "Train Model",
description = "Create a new person model"
)
// ==================
// ORGANIZATION
// ==================
data object Tags : AppDestinations(
route = AppRoutes.TAGS,
icon = Icons.AutoMirrored.Filled.Label,
label = "Tags",
description = "Manage photo tags"
)
data object UTILITIES : AppDestinations(
route = AppRoutes.UTILITIES,
icon = Icons.Default.UploadFile,
label = "Upload",
description = "Add new photos"
)
// ==================
// SETTINGS
// ==================
data object Settings : AppDestinations(
route = AppRoutes.SETTINGS,
icon = Icons.Default.Settings,
label = "Settings",
description = "App preferences"
)
}
/**
* Organized destination groups for beautiful drawer sections
*/
// Photo browsing section
val photoDestinations = listOf(
AppDestinations.Search,
AppDestinations.Explore,
AppDestinations.Collections
)
// Face recognition section
val faceRecognitionDestinations = listOf(
AppDestinations.Discover, // ✨ NEW: Auto-cluster discovery
AppDestinations.Inventory,
AppDestinations.Train
)
// Organization section
val organizationDestinations = listOf(
AppDestinations.Tags,
AppDestinations.UTILITIES
)
// Settings (separate, pinned to bottom)
val settingsDestination = AppDestinations.Settings
/**
* All drawer items (excludes Settings which is handled separately)
*/
val allMainDrawerDestinations = photoDestinations + faceRecognitionDestinations + organizationDestinations
/**
* Helper function to get destination by route
* Useful for highlighting current route in drawer
*/
fun getDestinationByRoute(route: String?): AppDestinations? {
return when (route) {
AppRoutes.SEARCH -> AppDestinations.Search
AppRoutes.EXPLORE -> AppDestinations.Explore
AppRoutes.COLLECTIONS -> AppDestinations.Collections
AppRoutes.DISCOVER -> AppDestinations.Discover
AppRoutes.INVENTORY -> AppDestinations.Inventory
AppRoutes.TRAIN -> AppDestinations.Train
AppRoutes.TAGS -> AppDestinations.Tags
AppRoutes.UTILITIES -> AppDestinations.UTILITIES
AppRoutes.SETTINGS -> AppDestinations.Settings
else -> null
}
}

View File

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package com.placeholder.sherpai2.ui.navigation
import android.net.Uri
import androidx.compose.runtime.Composable
import androidx.compose.runtime.LaunchedEffect
import androidx.compose.runtime.collectAsState
import androidx.compose.runtime.getValue
import androidx.compose.ui.Modifier
import androidx.hilt.navigation.compose.hiltViewModel
import androidx.lifecycle.compose.collectAsStateWithLifecycle
import androidx.navigation.NavHostController
import androidx.navigation.NavType
import androidx.navigation.compose.NavHost
import androidx.navigation.compose.composable
import androidx.navigation.navArgument
import com.placeholder.sherpai2.ui.devscreens.DummyScreen
import com.placeholder.sherpai2.ui.album.AlbumViewScreen
import com.placeholder.sherpai2.ui.album.AlbumViewModel
import com.placeholder.sherpai2.ui.collections.CollectionsScreen
import com.placeholder.sherpai2.ui.collections.CollectionsViewModel
import com.placeholder.sherpai2.ui.discover.DiscoverPeopleScreen
import com.placeholder.sherpai2.ui.explore.ExploreScreen
import com.placeholder.sherpai2.ui.imagedetail.ImageDetailScreen
import com.placeholder.sherpai2.ui.modelinventory.PersonInventoryScreen
import com.placeholder.sherpai2.ui.search.SearchScreen
import com.placeholder.sherpai2.ui.search.SearchViewModel
import com.placeholder.sherpai2.ui.tags.TagManagementScreen
import com.placeholder.sherpai2.ui.trainingprep.ScanResultsScreen
import com.placeholder.sherpai2.ui.trainingprep.ScanningState
import com.placeholder.sherpai2.ui.trainingprep.TrainViewModel
import com.placeholder.sherpai2.ui.trainingprep.TrainingScreen
import com.placeholder.sherpai2.ui.trainingprep.TrainingPhotoSelectorScreen
import com.placeholder.sherpai2.ui.utilities.PhotoUtilitiesScreen
import java.net.URLDecoder
import java.net.URLEncoder
import com.placeholder.sherpai2.ui.navigation.AppRoutes
/**
* AppNavHost - UPDATED with Discover People screen
*
* NEW: Replaces placeholder "Models" screen with auto-clustering face discovery
*/
@Composable
fun AppNavHost(
navController: NavHostController,
modifier: Modifier = Modifier
) {
NavHost(
navController = navController,
startDestination = AppRoutes.SEARCH,
modifier = modifier
) {
// ==========================================
// PHOTO BROWSING
// ==========================================
/**
* SEARCH SCREEN
*/
composable(AppRoutes.SEARCH) {
val searchViewModel: SearchViewModel = hiltViewModel()
val collectionsViewModel: CollectionsViewModel = hiltViewModel()
SearchScreen(
searchViewModel = searchViewModel,
onImageClick = { imageUri ->
ImageListHolder.clear()
val encodedUri = URLEncoder.encode(imageUri, "UTF-8")
navController.navigate("${AppRoutes.IMAGE_DETAIL}/$encodedUri")
},
onAlbumClick = { tagValue ->
navController.navigate("album/tag/$tagValue")
},
onSaveToCollection = { includedPeople, excludedPeople, includedTags, excludedTags, dateRange, photoCount ->
collectionsViewModel.startSmartCollectionFromSearch(
includedPeople = includedPeople,
excludedPeople = excludedPeople,
includedTags = includedTags,
excludedTags = excludedTags,
dateRange = dateRange,
photoCount = photoCount
)
}
)
}
/**
* EXPLORE SCREEN
*/
composable(AppRoutes.EXPLORE) {
ExploreScreen(
onAlbumClick = { albumType, albumId ->
navController.navigate("album/$albumType/$albumId")
}
)
}
/**
* COLLECTIONS SCREEN
*/
composable(AppRoutes.COLLECTIONS) {
val collectionsViewModel: CollectionsViewModel = hiltViewModel()
CollectionsScreen(
viewModel = collectionsViewModel,
onCollectionClick = { collectionId ->
navController.navigate("album/collection/$collectionId")
},
onCreateClick = {
navController.navigate(AppRoutes.SEARCH)
}
)
}
/**
* IMAGE DETAIL SCREEN
*/
composable(
route = "${AppRoutes.IMAGE_DETAIL}/{imageUri}",
arguments = listOf(
navArgument("imageUri") {
type = NavType.StringType
}
)
) { backStackEntry ->
val imageUri = backStackEntry.arguments?.getString("imageUri")
?.let { URLDecoder.decode(it, "UTF-8") }
?: error("imageUri missing from navigation")
val allImageUris = ImageListHolder.getImageList()
ImageDetailScreen(
imageUri = imageUri,
onBack = {
ImageListHolder.clear()
navController.popBackStack()
},
navController = navController,
allImageUris = allImageUris
)
}
/**
* ALBUM VIEW SCREEN
*/
composable(
route = "album/{albumType}/{albumId}",
arguments = listOf(
navArgument("albumType") {
type = NavType.StringType
},
navArgument("albumId") {
type = NavType.StringType
}
)
) {
val albumViewModel: AlbumViewModel = hiltViewModel()
val uiState by albumViewModel.uiState.collectAsStateWithLifecycle()
AlbumViewScreen(
onBack = {
navController.popBackStack()
},
onImageClick = { imageUri ->
val allImageUris = if (uiState is com.placeholder.sherpai2.ui.album.AlbumUiState.Success) {
(uiState as com.placeholder.sherpai2.ui.album.AlbumUiState.Success)
.photos
.map { it.image.imageUri }
} else {
emptyList()
}
ImageListHolder.setImageList(allImageUris)
val encodedUri = URLEncoder.encode(imageUri, "UTF-8")
navController.navigate("${AppRoutes.IMAGE_DETAIL}/$encodedUri")
}
)
}
// ==========================================
// FACE RECOGNITION SYSTEM
// ==========================================
/**
* DISCOVER PEOPLE SCREEN - ✨ NEW!
*
* Auto-clustering face discovery with spoon-feed naming flow:
* 1. Auto-clusters all faces in library (2-5 min)
* 2. Shows beautiful grid of discovered people
* 3. User taps to name each person
* 4. Captures: name, DOB, sibling relationships
* 5. Triggers deep background scan with age tagging
*
* Replaces: Old "Models" placeholder screen
*/
composable(AppRoutes.DISCOVER) {
DiscoverPeopleScreen()
}
/**
* PERSON INVENTORY SCREEN
*/
composable(AppRoutes.INVENTORY) {
PersonInventoryScreen(
onNavigateToPersonDetail = { personId ->
navController.navigate(AppRoutes.SEARCH)
}
)
}
/**
* TRAINING FLOW - Manual training (still available)
*/
composable(AppRoutes.TRAIN) { entry ->
val trainViewModel: TrainViewModel = hiltViewModel()
val uiState by trainViewModel.uiState.collectAsState()
val selectedUris = entry.savedStateHandle.get<List<Uri>>("selected_image_uris")
LaunchedEffect(selectedUris) {
if (selectedUris != null && uiState is ScanningState.Idle) {
trainViewModel.scanAndTagFaces(selectedUris)
entry.savedStateHandle.remove<List<Uri>>("selected_image_uris")
}
}
when (uiState) {
is ScanningState.Idle -> {
TrainingScreen(
onSelectImages = {
// Navigate to custom photo selector (shows only faces!)
navController.navigate(AppRoutes.TRAINING_PHOTO_SELECTOR)
}
)
}
else -> {
ScanResultsScreen(
state = uiState,
onFinish = {
navController.navigate(AppRoutes.INVENTORY) {
popUpTo(AppRoutes.TRAIN) { inclusive = true }
}
}
)
}
}
}
/**
* TRAINING PHOTO SELECTOR - Custom gallery with face filtering
*/
composable(AppRoutes.TRAINING_PHOTO_SELECTOR) {
TrainingPhotoSelectorScreen(
onBack = {
navController.popBackStack()
},
onPhotosSelected = { uris ->
// Pass selected URIs back to training flow
navController.previousBackStackEntry
?.savedStateHandle
?.set("selected_image_uris", uris)
navController.popBackStack()
}
)
}
/**
* MODELS SCREEN - DEPRECATED, kept for backwards compat
*/
composable(AppRoutes.MODELS) {
DummyScreen(
title = "AI Models",
subtitle = "Use 'Discover' instead"
)
}
// ==========================================
// ORGANIZATION
// ==========================================
/**
* TAGS SCREEN
*/
composable(AppRoutes.TAGS) {
TagManagementScreen()
}
/**
* UTILITIES SCREEN
*/
composable(AppRoutes.UTILITIES) {
PhotoUtilitiesScreen()
}
// ==========================================
// SETTINGS
// ==========================================
/**
* SETTINGS SCREEN
*/
composable(AppRoutes.SETTINGS) {
DummyScreen(
title = "Settings",
subtitle = "App preferences and configuration"
)
}
}
}

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package com.placeholder.sherpai2.ui.navigation
/**
* Centralized list of navigation routes used by NavHost.
*
* This intentionally mirrors AppDestinations.route
* but exists as a pure navigation concern.
*
* Why:
* - Drawer UI ≠ Navigation system
* - Keeps NavHost decoupled from icons / labels
*/
object AppRoutes {
// Photo browsing
const val SEARCH = "search"
const val EXPLORE = "explore"
const val IMAGE_DETAIL = "IMAGE_DETAIL"
// Face recognition
const val DISCOVER = "discover" // ✨ NEW: Auto-cluster face discovery
const val INVENTORY = "inv"
const val TRAIN = "train"
const val MODELS = "models" // DEPRECATED - kept for reference only
// Organization
const val TAGS = "tags"
const val UTILITIES = "utilities"
// Settings
const val SETTINGS = "settings"
// Internal training flow screens
const val IMAGE_SELECTOR = "Image Selection" // DEPRECATED - kept for reference only
const val TRAINING_PHOTO_SELECTOR = "training_photo_selector" // Face-filtered gallery
const val CROP_SCREEN = "CROP_SCREEN"
const val TRAINING_SCREEN = "TRAINING_SCREEN"
const val ScanResultsScreen = "First Scan Results"
// Album view
const val ALBUM_VIEW = "album/{albumType}/{albumId}"
fun albumRoute(albumType: String, albumId: String) = "album/$albumType/$albumId"
// Collections
const val COLLECTIONS = "collections"
}

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package com.placeholder.sherpai2.ui.navigation
/**
* Simple holder for passing image lists between screens
* Used for prev/next navigation in ImageDetailScreen
*/
object ImageListHolder {
private var imageUris: List<String> = emptyList()
fun setImageList(uris: List<String>) {
imageUris = uris
}
fun getImageList(): List<String> {
return imageUris
}
fun clear() {
imageUris = emptyList()
}
}

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package com.placeholder.sherpai2.ui.presentation
import androidx.compose.foundation.background
import androidx.compose.foundation.layout.*
import androidx.compose.foundation.rememberScrollState
import androidx.compose.foundation.shape.RoundedCornerShape
import androidx.compose.foundation.verticalScroll
import androidx.compose.material3.*
import androidx.compose.runtime.Composable
import androidx.compose.ui.Alignment
import androidx.compose.ui.Modifier
import androidx.compose.ui.draw.clip
import androidx.compose.ui.graphics.Brush
import androidx.compose.ui.graphics.Color
import androidx.compose.ui.text.font.FontWeight
import androidx.compose.ui.unit.dp
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.automirrored.filled.Label
import androidx.compose.material.icons.filled.*
import com.placeholder.sherpai2.ui.navigation.AppRoutes
/**
* SLIMMED DOWN AppDrawer - 280dp width, inline logo, cleaner sections
* UPDATED: Discover People feature with sparkle icon ✨
*/
@OptIn(ExperimentalMaterial3Api::class)
@Composable
fun AppDrawerContent(
currentRoute: String?,
onDestinationClicked: (String) -> Unit
) {
ModalDrawerSheet(
modifier = Modifier.width(280.dp), // SLIMMER (was 300dp)
drawerContainerColor = MaterialTheme.colorScheme.surface
) {
// SCROLLABLE Column - works on small phones!
Column(
modifier = Modifier
.fillMaxSize()
.verticalScroll(rememberScrollState())
) {
// ===== COMPACT HEADER - Icon + Text Inline =====
Box(
modifier = Modifier
.fillMaxWidth()
.background(
Brush.verticalGradient(
colors = listOf(
MaterialTheme.colorScheme.primaryContainer,
MaterialTheme.colorScheme.surface
)
)
)
.padding(20.dp) // Reduced padding
) {
Row(
horizontalArrangement = Arrangement.spacedBy(12.dp),
verticalAlignment = Alignment.CenterVertically
) {
// App icon - smaller
Surface(
modifier = Modifier.size(48.dp), // Smaller (was 56dp)
shape = RoundedCornerShape(14.dp),
color = MaterialTheme.colorScheme.primary,
shadowElevation = 4.dp
) {
Box(contentAlignment = Alignment.Center) {
Icon(
Icons.Default.Terrain, // Mountain theme!
contentDescription = null,
modifier = Modifier.size(28.dp),
tint = MaterialTheme.colorScheme.onPrimary
)
}
}
// Text next to icon
Column(verticalArrangement = Arrangement.spacedBy(2.dp)) {
Text(
"SherpAI",
style = MaterialTheme.typography.titleLarge, // Smaller (was headlineMedium)
fontWeight = FontWeight.Bold,
color = MaterialTheme.colorScheme.onSurface
)
Text(
"Face Recognition",
style = MaterialTheme.typography.bodySmall, // Smaller
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
}
Spacer(modifier = Modifier.height(4.dp)) // Reduced spacing
// ===== NAVIGATION SECTIONS =====
Column(
modifier = Modifier
.fillMaxWidth()
.padding(horizontal = 8.dp), // Reduced padding
verticalArrangement = Arrangement.spacedBy(2.dp) // Tighter spacing
) {
// Photos Section
DrawerSection(title = "Photos")
val photoItems = listOf(
DrawerItem(AppRoutes.SEARCH, "Search", Icons.Default.Search),
DrawerItem(AppRoutes.EXPLORE, "Explore", Icons.Default.Explore),
DrawerItem(AppRoutes.COLLECTIONS, "Collections", Icons.Default.Collections)
)
photoItems.forEach { item ->
DrawerNavigationItem(
item = item,
selected = item.route == currentRoute,
onClick = { onDestinationClicked(item.route) }
)
}
Spacer(modifier = Modifier.height(4.dp))
// Face Recognition Section
DrawerSection(title = "Face Recognition")
val faceItems = listOf(
DrawerItem(AppRoutes.DISCOVER, "Discover", Icons.Default.AutoAwesome), // ✨ UPDATED!
DrawerItem(AppRoutes.INVENTORY, "People", Icons.Default.Face),
DrawerItem(AppRoutes.TRAIN, "Train Model", Icons.Default.ModelTraining)
)
faceItems.forEach { item ->
DrawerNavigationItem(
item = item,
selected = item.route == currentRoute,
onClick = { onDestinationClicked(item.route) }
)
}
Spacer(modifier = Modifier.height(4.dp))
// Organization Section
DrawerSection(title = "Organization")
val orgItems = listOf(
DrawerItem(AppRoutes.TAGS, "Tags", Icons.AutoMirrored.Filled.Label),
DrawerItem(AppRoutes.UTILITIES, "Utilities", Icons.Default.Build)
)
orgItems.forEach { item ->
DrawerNavigationItem(
item = item,
selected = item.route == currentRoute,
onClick = { onDestinationClicked(item.route) }
)
}
Spacer(modifier = Modifier.height(8.dp))
// Settings at bottom
HorizontalDivider(
modifier = Modifier.padding(vertical = 6.dp),
color = MaterialTheme.colorScheme.outlineVariant
)
DrawerNavigationItem(
item = DrawerItem(
AppRoutes.SETTINGS,
"Settings",
Icons.Default.Settings
),
selected = AppRoutes.SETTINGS == currentRoute,
onClick = { onDestinationClicked(AppRoutes.SETTINGS) }
)
Spacer(modifier = Modifier.height(16.dp)) // Bottom padding for scroll
}
}
}
}
/**
* Section header - more compact
*/
@Composable
private fun DrawerSection(title: String) {
Text(
text = title,
style = MaterialTheme.typography.labelSmall, // Smaller
fontWeight = FontWeight.Bold,
color = MaterialTheme.colorScheme.primary,
modifier = Modifier.padding(horizontal = 16.dp, vertical = 6.dp) // Reduced padding
)
}
/**
* Navigation item - cleaner, no subtitle
*/
@Composable
private fun DrawerNavigationItem(
item: DrawerItem,
selected: Boolean,
onClick: () -> Unit
) {
NavigationDrawerItem(
label = {
Text(
text = item.label,
style = MaterialTheme.typography.bodyMedium, // Slightly smaller
fontWeight = if (selected) FontWeight.SemiBold else FontWeight.Normal
)
},
icon = {
Icon(
item.icon,
contentDescription = item.label,
modifier = Modifier.size(22.dp) // Slightly smaller
)
},
selected = selected,
onClick = onClick,
modifier = Modifier
.padding(NavigationDrawerItemDefaults.ItemPadding)
.clip(RoundedCornerShape(10.dp)), // Slightly smaller radius
colors = NavigationDrawerItemDefaults.colors(
selectedContainerColor = MaterialTheme.colorScheme.primaryContainer,
selectedIconColor = MaterialTheme.colorScheme.primary,
selectedTextColor = MaterialTheme.colorScheme.onPrimaryContainer,
unselectedContainerColor = Color.Transparent
)
)
}
/**
* Simplified drawer item (no subtitle)
*/
private data class DrawerItem(
val route: String,
val label: String,
val icon: androidx.compose.ui.graphics.vector.ImageVector
)

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package com.placeholder.sherpai2.ui.presentation
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.filled.Face
import androidx.compose.material3.*
import androidx.compose.runtime.Composable
import androidx.compose.ui.text.font.FontWeight
/**
* FaceCachePromptDialog - Shows on app launch if face cache needs population
*
* Location: /ui/presentation/FaceCachePromptDialog.kt (same package as MainScreen)
*
* Used by: MainScreen to prompt user to populate face cache
*/
@Composable
fun FaceCachePromptDialog(
unscannedPhotoCount: Int,
onDismiss: () -> Unit,
onScanNow: () -> Unit
) {
AlertDialog(
onDismissRequest = onDismiss,
icon = {
Icon(
imageVector = Icons.Default.Face,
contentDescription = null,
tint = MaterialTheme.colorScheme.primary
)
},
title = {
Text(
text = "Face Cache Needs Update",
fontWeight = FontWeight.Bold
)
},
text = {
Text(
text = "You have $unscannedPhotoCount photos that haven't been scanned for faces yet.\n\n" +
"Scanning is required for:\n" +
"• People Discovery\n" +
"• Face Recognition\n" +
"• Face Tagging\n\n" +
"This is a one-time scan and will run in the background."
)
},
confirmButton = {
Button(onClick = onScanNow) {
Text("Scan Now")
}
},
dismissButton = {
TextButton(onClick = onDismiss) {
Text("Later")
}
}
)
}

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package com.placeholder.sherpai2.ui.presentation
import androidx.compose.foundation.layout.padding
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.filled.Menu
import androidx.compose.material3.*
import androidx.compose.runtime.*
import androidx.compose.ui.Modifier
import androidx.hilt.navigation.compose.hiltViewModel
import androidx.navigation.compose.rememberNavController
import androidx.navigation.compose.currentBackStackEntryAsState
import com.placeholder.sherpai2.ui.navigation.AppNavHost
import com.placeholder.sherpai2.ui.navigation.AppRoutes
import kotlinx.coroutines.launch
/**
* MainScreen - Complete app container with drawer navigation
*
* CRITICAL FIX APPLIED:
* ✅ Removed AppRoutes.DISCOVER from screensWithOwnTopBar
* ✅ DiscoverPeopleScreen now shows hamburger menu + "Discover People" title!
*/
@OptIn(ExperimentalMaterial3Api::class)
@Composable
fun MainScreen(
viewModel: MainViewModel = hiltViewModel()
) {
val navController = rememberNavController()
val drawerState = rememberDrawerState(DrawerValue.Closed)
val scope = rememberCoroutineScope()
val currentBackStackEntry by navController.currentBackStackEntryAsState()
val currentRoute = currentBackStackEntry?.destination?.route
// Face cache prompt dialog state
val needsFaceCachePopulation by viewModel.needsFaceCachePopulation.collectAsState()
val unscannedPhotoCount by viewModel.unscannedPhotoCount.collectAsState()
// ✅ CRITICAL FIX: DISCOVER is NOT in this list!
// These screens handle their own TopAppBar/navigation
val screensWithOwnTopBar = setOf(
AppRoutes.IMAGE_DETAIL,
AppRoutes.TRAINING_SCREEN,
AppRoutes.CROP_SCREEN
)
ModalNavigationDrawer(
drawerState = drawerState,
drawerContent = {
AppDrawerContent(
currentRoute = currentRoute,
onDestinationClicked = { route ->
scope.launch {
drawerState.close()
}
navController.navigate(route) {
popUpTo(navController.graph.startDestinationId) {
saveState = true
}
launchSingleTop = true
restoreState = true
}
}
)
}
) {
Scaffold(
topBar = {
// ✅ Show TopAppBar for ALL screens except those with their own
if (currentRoute !in screensWithOwnTopBar) {
TopAppBar(
title = {
Text(
text = when (currentRoute) {
AppRoutes.SEARCH -> "Search"
AppRoutes.EXPLORE -> "Explore"
AppRoutes.COLLECTIONS -> "Collections"
AppRoutes.DISCOVER -> "Discover People" // ✅ SHOWS NOW!
AppRoutes.INVENTORY -> "People"
AppRoutes.TRAIN -> "Train Model"
AppRoutes.TAGS -> "Tags"
AppRoutes.UTILITIES -> "Utilities"
AppRoutes.SETTINGS -> "Settings"
AppRoutes.MODELS -> "AI Models"
else -> {
// Handle dynamic routes like album/{type}/{id}
if (currentRoute?.startsWith("album/") == true) {
"Album"
} else {
"SherpAI"
}
}
}
)
},
navigationIcon = {
IconButton(onClick = {
scope.launch {
drawerState.open()
}
}) {
Icon(
imageVector = Icons.Default.Menu,
contentDescription = "Open menu"
)
}
},
colors = TopAppBarDefaults.topAppBarColors(
containerColor = MaterialTheme.colorScheme.primaryContainer,
titleContentColor = MaterialTheme.colorScheme.onPrimaryContainer,
navigationIconContentColor = MaterialTheme.colorScheme.onPrimaryContainer,
actionIconContentColor = MaterialTheme.colorScheme.onPrimaryContainer
)
)
}
}
) { paddingValues ->
// ✅ Use YOUR existing AppNavHost - it already has all the screens defined!
AppNavHost(
navController = navController,
modifier = Modifier.padding(paddingValues)
)
}
}
// ✅ Face cache prompt dialog (shows on app launch if needed)
if (needsFaceCachePopulation) {
FaceCachePromptDialog(
unscannedPhotoCount = unscannedPhotoCount,
onDismiss = { viewModel.dismissFaceCachePrompt() },
onScanNow = {
viewModel.dismissFaceCachePrompt()
navController.navigate(AppRoutes.UTILITIES)
}
)
}
}

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package com.placeholder.sherpai2.ui.presentation
import androidx.lifecycle.ViewModel
import androidx.lifecycle.viewModelScope
import com.placeholder.sherpai2.data.local.dao.ImageDao
import dagger.hilt.android.lifecycle.HiltViewModel
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.flow.MutableStateFlow
import kotlinx.coroutines.flow.StateFlow
import kotlinx.coroutines.flow.asStateFlow
import kotlinx.coroutines.launch
import javax.inject.Inject
/**
* MainViewModel - App-level state management for MainScreen
*
* Location: /ui/presentation/MainViewModel.kt (same package as MainScreen)
*
* Features:
* 1. Auto-check face cache on app launch
* 2. Prompt user if cache needs population
* 3. Track new photos that need scanning
*/
@HiltViewModel
class MainViewModel @Inject constructor(
private val imageDao: ImageDao
) : ViewModel() {
private val _needsFaceCachePopulation = MutableStateFlow(false)
val needsFaceCachePopulation: StateFlow<Boolean> = _needsFaceCachePopulation.asStateFlow()
private val _unscannedPhotoCount = MutableStateFlow(0)
val unscannedPhotoCount: StateFlow<Int> = _unscannedPhotoCount.asStateFlow()
init {
checkFaceCache()
}
/**
* Check if face cache needs population
*/
fun checkFaceCache() {
viewModelScope.launch(Dispatchers.IO) {
try {
// Count photos that need face detection
val unscanned = imageDao.getImagesNeedingFaceDetection().size
_unscannedPhotoCount.value = unscanned
_needsFaceCachePopulation.value = unscanned > 0
} catch (e: Exception) {
// Silently fail - not critical
}
}
}
/**
* Dismiss the face cache prompt
*/
fun dismissFaceCachePrompt() {
_needsFaceCachePopulation.value = false
}
/**
* Refresh cache status (call after populating cache)
*/
fun refreshCacheStatus() {
checkFaceCache()
}
}

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package com.placeholder.sherpai2.ui.search
import androidx.compose.foundation.clickable
import androidx.compose.foundation.layout.*
import androidx.compose.foundation.lazy.LazyRow
import androidx.compose.foundation.lazy.grid.*
import androidx.compose.foundation.lazy.items
import androidx.compose.foundation.rememberScrollState
import androidx.compose.foundation.shape.RoundedCornerShape
import androidx.compose.foundation.verticalScroll
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.filled.*
import androidx.compose.material3.*
import androidx.compose.runtime.*
import androidx.compose.ui.Alignment
import androidx.compose.ui.Modifier
import androidx.compose.ui.graphics.Color
import androidx.compose.ui.text.font.FontWeight
import androidx.compose.ui.unit.dp
import androidx.lifecycle.compose.collectAsStateWithLifecycle
import coil.compose.AsyncImage
import com.placeholder.sherpai2.data.local.entity.PersonEntity
/**
* ENHANCED SearchScreen
*
* NEW FEATURES:
* ✅ Face filtering (Has Faces / No Faces)
* ✅ X button on each filter chip for easy removal
* ✅ Tap to swap include/exclude (kept)
* ✅ Better visual hierarchy
*/
@OptIn(ExperimentalMaterial3Api::class)
@Composable
fun SearchScreen(
modifier: Modifier = Modifier,
searchViewModel: SearchViewModel,
onImageClick: (String) -> Unit,
onAlbumClick: ((String) -> Unit)? = null,
onSaveToCollection: ((
includedPeople: Set<String>,
excludedPeople: Set<String>,
includedTags: Set<String>,
excludedTags: Set<String>,
dateRange: DateRange,
photoCount: Int
) -> Unit)? = null
) {
val searchQuery by searchViewModel.searchQuery.collectAsStateWithLifecycle()
val includedPeople by searchViewModel.includedPeople.collectAsStateWithLifecycle()
val excludedPeople by searchViewModel.excludedPeople.collectAsStateWithLifecycle()
val includedTags by searchViewModel.includedTags.collectAsStateWithLifecycle()
val excludedTags by searchViewModel.excludedTags.collectAsStateWithLifecycle()
val dateRange by searchViewModel.dateRange.collectAsStateWithLifecycle()
val faceFilter by searchViewModel.faceFilter.collectAsStateWithLifecycle()
val availablePeople by searchViewModel.availablePeople.collectAsStateWithLifecycle()
val availableTags by searchViewModel.availableTags.collectAsStateWithLifecycle()
val images by searchViewModel
.searchImages()
.collectAsStateWithLifecycle(initialValue = emptyList())
var showPeoplePicker by remember { mutableStateOf(false) }
var showTagPicker by remember { mutableStateOf(false) }
var showFaceFilterMenu by remember { mutableStateOf(false) }
Column(modifier = modifier.fillMaxSize()) {
// Search bar + quick add buttons
Row(
modifier = Modifier
.fillMaxWidth()
.padding(horizontal = 16.dp, vertical = 12.dp),
horizontalArrangement = Arrangement.spacedBy(8.dp),
verticalAlignment = Alignment.CenterVertically
) {
OutlinedTextField(
value = searchQuery,
onValueChange = { searchViewModel.setSearchQuery(it) },
placeholder = { Text("Search tags...") },
leadingIcon = { Icon(Icons.Default.Search, null) },
trailingIcon = {
if (searchQuery.isNotEmpty()) {
IconButton(onClick = { searchViewModel.setSearchQuery("") }) {
Icon(Icons.Default.Close, "Clear")
}
}
},
modifier = Modifier.weight(1f),
singleLine = true,
shape = RoundedCornerShape(12.dp)
)
// Add person button
IconButton(
onClick = { showPeoplePicker = true },
colors = IconButtonDefaults.iconButtonColors(
containerColor = MaterialTheme.colorScheme.primaryContainer
)
) {
Icon(Icons.Default.PersonAdd, "Add person filter")
}
// Add tag button
IconButton(
onClick = { showTagPicker = true },
colors = IconButtonDefaults.iconButtonColors(
containerColor = MaterialTheme.colorScheme.secondaryContainer
)
) {
Icon(Icons.Default.LabelImportant, "Add tag filter")
}
// Face filter button (NEW!)
IconButton(
onClick = { showFaceFilterMenu = true },
colors = IconButtonDefaults.iconButtonColors(
containerColor = if (faceFilter != FaceFilter.ALL) {
MaterialTheme.colorScheme.tertiaryContainer
} else {
MaterialTheme.colorScheme.surfaceVariant
}
)
) {
Icon(
when (faceFilter) {
FaceFilter.HAS_FACES -> Icons.Default.Face
FaceFilter.NO_FACES -> Icons.Default.HideImage
else -> Icons.Default.FilterAlt
},
"Face filter"
)
}
}
// Active filters display (chips)
if (searchViewModel.hasActiveFilters()) {
Card(
modifier = Modifier
.fillMaxWidth()
.padding(horizontal = 16.dp, vertical = 4.dp),
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.surfaceVariant.copy(alpha = 0.5f)
)
) {
Column(
modifier = Modifier.padding(12.dp),
verticalArrangement = Arrangement.spacedBy(8.dp)
) {
Row(
modifier = Modifier.fillMaxWidth(),
horizontalArrangement = Arrangement.SpaceBetween,
verticalAlignment = Alignment.CenterVertically
) {
Text(
"Active Filters",
style = MaterialTheme.typography.labelLarge,
fontWeight = FontWeight.Bold
)
Row(horizontalArrangement = Arrangement.spacedBy(8.dp)) {
// Save to Collection button
if (onSaveToCollection != null && images.isNotEmpty()) {
FilledTonalButton(
onClick = {
onSaveToCollection(
includedPeople,
excludedPeople,
includedTags,
excludedTags,
dateRange,
images.size
)
},
contentPadding = PaddingValues(horizontal = 12.dp, vertical = 4.dp)
) {
Icon(
Icons.Default.Collections,
contentDescription = null,
modifier = Modifier.size(16.dp)
)
Spacer(Modifier.width(4.dp))
Text("Save", style = MaterialTheme.typography.labelMedium)
}
}
TextButton(
onClick = { searchViewModel.clearAllFilters() },
contentPadding = PaddingValues(horizontal = 8.dp, vertical = 4.dp)
) {
Text("Clear All", style = MaterialTheme.typography.labelMedium)
}
}
}
// Face Filter Chip (NEW!)
if (faceFilter != FaceFilter.ALL) {
FilterChipWithX(
label = faceFilter.displayName,
color = MaterialTheme.colorScheme.tertiaryContainer,
onTap = { showFaceFilterMenu = true },
onRemove = { searchViewModel.setFaceFilter(FaceFilter.ALL) },
leadingIcon = {
Icon(
when (faceFilter) {
FaceFilter.HAS_FACES -> Icons.Default.Face
FaceFilter.NO_FACES -> Icons.Default.HideImage
else -> Icons.Default.FilterAlt
},
contentDescription = null,
modifier = Modifier.size(16.dp)
)
}
)
}
// Included People (GREEN)
if (includedPeople.isNotEmpty()) {
LazyRow(
horizontalArrangement = Arrangement.spacedBy(6.dp),
contentPadding = PaddingValues(vertical = 4.dp)
) {
items(includedPeople.toList()) { personId ->
val person = availablePeople.find { it.id == personId }
if (person != null) {
FilterChipWithX(
label = person.name,
color = Color(0xFF4CAF50).copy(alpha = 0.3f),
onTap = { searchViewModel.excludePerson(personId) },
onRemove = { searchViewModel.removePersonFilter(personId) },
leadingIcon = {
Icon(
Icons.Default.Person,
contentDescription = null,
modifier = Modifier.size(16.dp),
tint = Color(0xFF2E7D32)
)
}
)
}
}
}
}
// Excluded People (RED)
if (excludedPeople.isNotEmpty()) {
LazyRow(
horizontalArrangement = Arrangement.spacedBy(6.dp),
contentPadding = PaddingValues(vertical = 4.dp)
) {
items(excludedPeople.toList()) { personId ->
val person = availablePeople.find { it.id == personId }
if (person != null) {
FilterChipWithX(
label = person.name,
color = Color(0xFFF44336).copy(alpha = 0.3f),
onTap = { searchViewModel.includePerson(personId) },
onRemove = { searchViewModel.removePersonFilter(personId) },
leadingIcon = {
Icon(
Icons.Default.PersonOff,
contentDescription = null,
modifier = Modifier.size(16.dp),
tint = Color(0xFFC62828)
)
}
)
}
}
}
}
// Included Tags (GREEN)
if (includedTags.isNotEmpty()) {
LazyRow(
horizontalArrangement = Arrangement.spacedBy(6.dp),
contentPadding = PaddingValues(vertical = 4.dp)
) {
items(includedTags.toList()) { tag ->
FilterChipWithX(
label = tag,
color = Color(0xFF4CAF50).copy(alpha = 0.3f),
onTap = { searchViewModel.excludeTag(tag) },
onRemove = { searchViewModel.removeTagFilter(tag) },
leadingIcon = {
Icon(
Icons.Default.Label,
contentDescription = null,
modifier = Modifier.size(16.dp),
tint = Color(0xFF2E7D32)
)
}
)
}
}
}
// Excluded Tags (RED)
if (excludedTags.isNotEmpty()) {
LazyRow(
horizontalArrangement = Arrangement.spacedBy(6.dp),
contentPadding = PaddingValues(vertical = 4.dp)
) {
items(excludedTags.toList()) { tag ->
FilterChipWithX(
label = tag,
color = Color(0xFFF44336).copy(alpha = 0.3f),
onTap = { searchViewModel.includeTag(tag) },
onRemove = { searchViewModel.removeTagFilter(tag) },
leadingIcon = {
Icon(
Icons.Default.LabelOff,
contentDescription = null,
modifier = Modifier.size(16.dp),
tint = Color(0xFFC62828)
)
}
)
}
}
}
}
}
}
// Results
when {
images.isEmpty() && searchViewModel.hasActiveFilters() -> NoResultsState()
images.isEmpty() && !searchViewModel.hasActiveFilters() -> EmptyState()
else -> {
LazyVerticalGrid(
columns = GridCells.Adaptive(minSize = 120.dp),
contentPadding = PaddingValues(16.dp),
horizontalArrangement = Arrangement.spacedBy(4.dp),
verticalArrangement = Arrangement.spacedBy(4.dp)
) {
items(images.size) { index ->
val imageWithTags = images[index]
Card(
modifier = Modifier
.aspectRatio(1f)
.clickable { onImageClick(imageWithTags.image.imageUri) },
shape = RoundedCornerShape(8.dp)
) {
AsyncImage(
model = imageWithTags.image.imageUri,
contentDescription = null,
modifier = Modifier.fillMaxSize()
)
}
}
}
}
}
}
// Face filter menu
if (showFaceFilterMenu) {
FaceFilterMenu(
currentFilter = faceFilter,
onSelect = { filter ->
searchViewModel.setFaceFilter(filter)
showFaceFilterMenu = false
},
onDismiss = { showFaceFilterMenu = false }
)
}
// People picker dialog
if (showPeoplePicker) {
PeoplePickerDialog(
people = availablePeople,
includedPeople = includedPeople,
excludedPeople = excludedPeople,
onInclude = { searchViewModel.includePerson(it) },
onExclude = { searchViewModel.excludePerson(it) },
onDismiss = { showPeoplePicker = false }
)
}
// Tag picker dialog
if (showTagPicker) {
TagPickerDialog(
tags = availableTags,
includedTags = includedTags,
excludedTags = excludedTags,
onInclude = { searchViewModel.includeTag(it) },
onExclude = { searchViewModel.excludeTag(it) },
onDismiss = { showTagPicker = false }
)
}
}
/**
* NEW: Filter chip with X button for easy removal
*/
@Composable
private fun FilterChipWithX(
label: String,
color: Color,
onTap: () -> Unit,
onRemove: () -> Unit,
leadingIcon: @Composable (() -> Unit)? = null
) {
Surface(
color = color,
shape = RoundedCornerShape(16.dp),
modifier = Modifier.height(32.dp)
) {
Row(
modifier = Modifier.padding(start = 8.dp, end = 4.dp),
verticalAlignment = Alignment.CenterVertically,
horizontalArrangement = Arrangement.spacedBy(6.dp)
) {
if (leadingIcon != null) {
leadingIcon()
}
Text(
text = label,
style = MaterialTheme.typography.labelMedium,
fontWeight = FontWeight.SemiBold,
modifier = Modifier.clickable(onClick = onTap)
)
IconButton(
onClick = onRemove,
modifier = Modifier.size(24.dp)
) {
Icon(
Icons.Default.Close,
contentDescription = "Remove",
modifier = Modifier.size(16.dp)
)
}
}
}
}
/**
* NEW: Face filter menu
*/
@Composable
private fun FaceFilterMenu(
currentFilter: FaceFilter,
onSelect: (FaceFilter) -> Unit,
onDismiss: () -> Unit
) {
AlertDialog(
onDismissRequest = onDismiss,
title = { Text("Filter by Faces") },
text = {
Column(verticalArrangement = Arrangement.spacedBy(8.dp)) {
FaceFilter.values().forEach { filter ->
Card(
modifier = Modifier
.fillMaxWidth()
.clickable { onSelect(filter) },
colors = CardDefaults.cardColors(
containerColor = if (filter == currentFilter) {
MaterialTheme.colorScheme.primaryContainer
} else {
MaterialTheme.colorScheme.surfaceVariant
}
)
) {
Row(
modifier = Modifier.padding(16.dp),
horizontalArrangement = Arrangement.spacedBy(12.dp),
verticalAlignment = Alignment.CenterVertically
) {
Icon(
when (filter) {
FaceFilter.ALL -> Icons.Default.FilterAlt
FaceFilter.HAS_FACES -> Icons.Default.Face
FaceFilter.NO_FACES -> Icons.Default.HideImage
},
contentDescription = null
)
Column {
Text(
filter.displayName,
style = MaterialTheme.typography.titleMedium,
fontWeight = FontWeight.Bold
)
Text(
when (filter) {
FaceFilter.ALL -> "Show all photos"
FaceFilter.HAS_FACES -> "Only photos with detected faces"
FaceFilter.NO_FACES -> "Only photos without faces"
},
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
}
}
}
},
confirmButton = {
TextButton(onClick = onDismiss) {
Text("Done")
}
}
)
}
// ... Rest of dialogs remain the same ...
@Composable
private fun PeoplePickerDialog(
people: List<PersonEntity>,
includedPeople: Set<String>,
excludedPeople: Set<String>,
onInclude: (String) -> Unit,
onExclude: (String) -> Unit,
onDismiss: () -> Unit
) {
AlertDialog(
onDismissRequest = onDismiss,
title = { Text("Add Person Filter") },
text = {
Column(
modifier = Modifier
.fillMaxWidth()
.height(400.dp)
.verticalScroll(rememberScrollState()),
verticalArrangement = Arrangement.spacedBy(8.dp)
) {
Text(
"Tap to INCLUDE (green) • Long press to EXCLUDE (red)",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
people.forEach { person ->
val isIncluded = person.id in includedPeople
val isExcluded = person.id in excludedPeople
Card(
modifier = Modifier
.fillMaxWidth()
.clickable { onInclude(person.id) },
colors = CardDefaults.cardColors(
containerColor = when {
isIncluded -> Color(0xFF4CAF50).copy(alpha = 0.3f)
isExcluded -> Color(0xFFF44336).copy(alpha = 0.3f)
else -> MaterialTheme.colorScheme.surfaceVariant
}
)
) {
Row(
modifier = Modifier.padding(12.dp),
horizontalArrangement = Arrangement.SpaceBetween,
verticalAlignment = Alignment.CenterVertically
) {
Text(person.name, fontWeight = FontWeight.Medium)
Row(horizontalArrangement = Arrangement.spacedBy(4.dp)) {
IconButton(
onClick = { onInclude(person.id) },
colors = IconButtonDefaults.iconButtonColors(
containerColor = if (isIncluded) Color(0xFF4CAF50) else Color.Transparent
)
) {
Icon(Icons.Default.Check, "Include", tint = if (isIncluded) Color.White else MaterialTheme.colorScheme.onSurface)
}
IconButton(
onClick = { onExclude(person.id) },
colors = IconButtonDefaults.iconButtonColors(
containerColor = if (isExcluded) Color(0xFFF44336) else Color.Transparent
)
) {
Icon(Icons.Default.Close, "Exclude", tint = if (isExcluded) Color.White else MaterialTheme.colorScheme.onSurface)
}
}
}
}
}
}
},
confirmButton = {
TextButton(onClick = onDismiss) {
Text("Done")
}
}
)
}
@Composable
private fun TagPickerDialog(
tags: List<String>,
includedTags: Set<String>,
excludedTags: Set<String>,
onInclude: (String) -> Unit,
onExclude: (String) -> Unit,
onDismiss: () -> Unit
) {
AlertDialog(
onDismissRequest = onDismiss,
title = { Text("Add Tag Filter") },
text = {
Column(
modifier = Modifier
.fillMaxWidth()
.height(400.dp)
.verticalScroll(rememberScrollState()),
verticalArrangement = Arrangement.spacedBy(8.dp)
) {
Text(
"Tap to INCLUDE (green) • Long press to EXCLUDE (red)",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
tags.forEach { tagValue ->
val isIncluded = tagValue in includedTags
val isExcluded = tagValue in excludedTags
Card(
modifier = Modifier
.fillMaxWidth()
.clickable { onInclude(tagValue) },
colors = CardDefaults.cardColors(
containerColor = when {
isIncluded -> Color(0xFF4CAF50).copy(alpha = 0.3f)
isExcluded -> Color(0xFFF44336).copy(alpha = 0.3f)
else -> MaterialTheme.colorScheme.surfaceVariant
}
)
) {
Row(
modifier = Modifier.padding(12.dp),
horizontalArrangement = Arrangement.SpaceBetween,
verticalAlignment = Alignment.CenterVertically
) {
Text(tagValue, fontWeight = FontWeight.Medium)
Row(horizontalArrangement = Arrangement.spacedBy(4.dp)) {
IconButton(
onClick = { onInclude(tagValue) },
colors = IconButtonDefaults.iconButtonColors(
containerColor = if (isIncluded) Color(0xFF4CAF50) else Color.Transparent
)
) {
Icon(Icons.Default.Check, "Include", tint = if (isIncluded) Color.White else MaterialTheme.colorScheme.onSurface)
}
IconButton(
onClick = { onExclude(tagValue) },
colors = IconButtonDefaults.iconButtonColors(
containerColor = if (isExcluded) Color(0xFFF44336) else Color.Transparent
)
) {
Icon(Icons.Default.Close, "Exclude", tint = if (isExcluded) Color.White else MaterialTheme.colorScheme.onSurface)
}
}
}
}
}
}
},
confirmButton = {
TextButton(onClick = onDismiss) {
Text("Done")
}
}
)
}
@Composable
private fun EmptyState() {
Box(
modifier = Modifier
.fillMaxSize()
.padding(32.dp),
contentAlignment = Alignment.Center
) {
Column(
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.spacedBy(16.dp)
) {
Icon(
Icons.Default.Search,
contentDescription = null,
modifier = Modifier.size(64.dp),
tint = MaterialTheme.colorScheme.onSurfaceVariant.copy(alpha = 0.6f)
)
Text(
"Advanced Search",
style = MaterialTheme.typography.titleLarge,
fontWeight = FontWeight.Bold
)
Text(
"Add people, tags, or face filters to search",
style = MaterialTheme.typography.bodyMedium,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
}
@Composable
private fun NoResultsState() {
Box(
modifier = Modifier
.fillMaxSize()
.padding(32.dp),
contentAlignment = Alignment.Center
) {
Column(
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.spacedBy(12.dp)
) {
Icon(
Icons.Default.SearchOff,
contentDescription = null,
modifier = Modifier.size(64.dp),
tint = MaterialTheme.colorScheme.onSurfaceVariant.copy(alpha = 0.6f)
)
Text(
"No photos found",
style = MaterialTheme.typography.titleLarge,
fontWeight = FontWeight.Bold
)
Text(
"Try different filters",
style = MaterialTheme.typography.bodyMedium,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
}

View File

@@ -0,0 +1,340 @@
package com.placeholder.sherpai2.ui.search
import androidx.lifecycle.ViewModel
import androidx.lifecycle.viewModelScope
import com.placeholder.sherpai2.data.local.dao.ImageAggregateDao
import com.placeholder.sherpai2.data.local.dao.PersonDao
import com.placeholder.sherpai2.data.local.dao.TagDao
import com.placeholder.sherpai2.data.local.entity.ImageEntity
import com.placeholder.sherpai2.data.local.entity.PersonEntity
import com.placeholder.sherpai2.data.local.entity.PhotoFaceTagEntity
import com.placeholder.sherpai2.data.repository.FaceRecognitionRepository
import dagger.hilt.android.lifecycle.HiltViewModel
import kotlinx.coroutines.ExperimentalCoroutinesApi
import kotlinx.coroutines.flow.*
import kotlinx.coroutines.launch
import java.util.Calendar
import javax.inject.Inject
@OptIn(ExperimentalCoroutinesApi::class)
@HiltViewModel
class SearchViewModel @Inject constructor(
private val imageAggregateDao: ImageAggregateDao,
private val faceRecognitionRepository: FaceRecognitionRepository,
private val personDao: PersonDao,
private val tagDao: TagDao
) : ViewModel() {
private val _searchQuery = MutableStateFlow("")
val searchQuery: StateFlow<String> = _searchQuery.asStateFlow()
private val _includedPeople = MutableStateFlow<Set<String>>(emptySet())
val includedPeople: StateFlow<Set<String>> = _includedPeople.asStateFlow()
private val _excludedPeople = MutableStateFlow<Set<String>>(emptySet())
val excludedPeople: StateFlow<Set<String>> = _excludedPeople.asStateFlow()
private val _includedTags = MutableStateFlow<Set<String>>(emptySet())
val includedTags: StateFlow<Set<String>> = _includedTags.asStateFlow()
private val _excludedTags = MutableStateFlow<Set<String>>(emptySet())
val excludedTags: StateFlow<Set<String>> = _excludedTags.asStateFlow()
private val _dateRange = MutableStateFlow(DateRange.ALL_TIME)
val dateRange: StateFlow<DateRange> = _dateRange.asStateFlow()
private val _faceFilter = MutableStateFlow(FaceFilter.ALL)
val faceFilter: StateFlow<FaceFilter> = _faceFilter.asStateFlow()
private val _availablePeople = MutableStateFlow<List<PersonEntity>>(emptyList())
val availablePeople: StateFlow<List<PersonEntity>> = _availablePeople.asStateFlow()
private val _availableTags = MutableStateFlow<List<String>>(emptyList())
val availableTags: StateFlow<List<String>> = _availableTags.asStateFlow()
private val personCache = mutableMapOf<String, String>()
init {
loadAvailableFilters()
buildPersonCache()
}
private fun buildPersonCache() {
viewModelScope.launch {
val people = personDao.getAllPersons()
people.forEach { person ->
val stats = faceRecognitionRepository.getPersonFaceStats(person.id)
if (stats != null) {
personCache[stats.faceModelId] = person.id
}
}
}
}
fun searchImages(): Flow<List<ImageWithFaceTags>> {
return combine(
_searchQuery,
_includedPeople,
_excludedPeople,
_includedTags,
_excludedTags,
_dateRange,
_faceFilter
) { values: Array<*> ->
@Suppress("UNCHECKED_CAST")
SearchCriteria(
query = values[0] as String,
includedPeople = values[1] as Set<String>,
excludedPeople = values[2] as Set<String>,
includedTags = values[3] as Set<String>,
excludedTags = values[4] as Set<String>,
dateRange = values[5] as DateRange,
faceFilter = values[6] as FaceFilter
)
}.flatMapLatest { criteria ->
imageAggregateDao.observeAllImagesWithEverything()
.map { imagesList ->
imagesList.mapNotNull { imageWithEverything ->
// Apply date filter
if (!isInDateRange(imageWithEverything.image.capturedAt, criteria.dateRange)) {
return@mapNotNull null
}
// Apply face filter - ONLY when cache is explicitly set
when (criteria.faceFilter) {
FaceFilter.HAS_FACES -> {
// Only show images where hasFaces is EXPLICITLY true
if (imageWithEverything.image.hasFaces != true) {
return@mapNotNull null
}
}
FaceFilter.NO_FACES -> {
// Only show images where hasFaces is EXPLICITLY false
if (imageWithEverything.image.hasFaces != false) {
return@mapNotNull null
}
}
FaceFilter.ALL -> {
// Show all images (null, true, or false)
}
}
val personIds = imageWithEverything.faceTags
.mapNotNull { faceTag -> personCache[faceTag.faceModelId] }
.toSet()
val imageTags = imageWithEverything.tags
.map { it.value }
.toSet()
val passesFilter = applyBooleanLogic(
personIds = personIds,
imageTags = imageTags,
criteria = criteria
)
if (passesFilter) {
val persons = personIds.mapNotNull { personId ->
_availablePeople.value.find { it.id == personId }
}
ImageWithFaceTags(
image = imageWithEverything.image,
faceTags = imageWithEverything.faceTags,
persons = persons
)
} else {
null
}
}.sortedByDescending { it.image.capturedAt }
}
}
}
private fun applyBooleanLogic(
personIds: Set<String>,
imageTags: Set<String>,
criteria: SearchCriteria
): Boolean {
val hasAllIncludedPeople = if (criteria.includedPeople.isNotEmpty()) {
criteria.includedPeople.all { it in personIds }
} else true
val hasNoExcludedPeople = if (criteria.excludedPeople.isNotEmpty()) {
criteria.excludedPeople.none { it in personIds }
} else true
val hasAllIncludedTags = if (criteria.includedTags.isNotEmpty()) {
criteria.includedTags.all { it in imageTags }
} else true
val hasNoExcludedTags = if (criteria.excludedTags.isNotEmpty()) {
criteria.excludedTags.none { it in imageTags }
} else true
val matchesTextSearch = if (criteria.query.isNotBlank()) {
val normalizedQuery = criteria.query.trim().lowercase()
imageTags.any { tag -> tag.lowercase().contains(normalizedQuery) }
} else true
return hasAllIncludedPeople && hasNoExcludedPeople &&
hasAllIncludedTags && hasNoExcludedTags &&
matchesTextSearch
}
private fun loadAvailableFilters() {
viewModelScope.launch {
val people = personDao.getAllPersons()
_availablePeople.value = people.sortedBy { it.name }
val tags = tagDao.getByType("SYSTEM")
val tagsWithUsage = tags.map { tag ->
tag to tagDao.getTagUsageCount(tag.tagId)
}
_availableTags.value = tagsWithUsage
.sortedByDescending { (_, usageCount) -> usageCount }
.take(30)
.map { (tag, _) -> tag.value }
}
}
fun includePerson(personId: String) {
_includedPeople.value = _includedPeople.value + personId
_excludedPeople.value = _excludedPeople.value - personId
}
fun excludePerson(personId: String) {
_excludedPeople.value = _excludedPeople.value + personId
_includedPeople.value = _includedPeople.value - personId
}
fun removePersonFilter(personId: String) {
_includedPeople.value = _includedPeople.value - personId
_excludedPeople.value = _excludedPeople.value - personId
}
fun includeTag(tagValue: String) {
_includedTags.value = _includedTags.value + tagValue
_excludedTags.value = _excludedTags.value - tagValue
}
fun excludeTag(tagValue: String) {
_excludedTags.value = _excludedTags.value + tagValue
_includedTags.value = _includedTags.value - tagValue
}
fun removeTagFilter(tagValue: String) {
_includedTags.value = _includedTags.value - tagValue
_excludedTags.value = _excludedTags.value - tagValue
}
fun setSearchQuery(query: String) {
_searchQuery.value = query
}
fun setDateRange(range: DateRange) {
_dateRange.value = range
}
fun setFaceFilter(filter: FaceFilter) {
_faceFilter.value = filter
}
fun clearAllFilters() {
_searchQuery.value = ""
_includedPeople.value = emptySet()
_excludedPeople.value = emptySet()
_includedTags.value = emptySet()
_excludedTags.value = emptySet()
_dateRange.value = DateRange.ALL_TIME
_faceFilter.value = FaceFilter.ALL
}
fun hasActiveFilters(): Boolean {
return _searchQuery.value.isNotBlank() ||
_includedPeople.value.isNotEmpty() ||
_excludedPeople.value.isNotEmpty() ||
_includedTags.value.isNotEmpty() ||
_excludedTags.value.isNotEmpty() ||
_dateRange.value != DateRange.ALL_TIME ||
_faceFilter.value != FaceFilter.ALL
}
fun getSearchSummary(): String {
val parts = mutableListOf<String>()
if (_includedPeople.value.isNotEmpty()) parts.add("WITH: ${_includedPeople.value.size} people")
if (_excludedPeople.value.isNotEmpty()) parts.add("WITHOUT: ${_excludedPeople.value.size} people")
if (_includedTags.value.isNotEmpty()) parts.add("HAS: ${_includedTags.value.size} tags")
if (_excludedTags.value.isNotEmpty()) parts.add("NOT: ${_excludedTags.value.size} tags")
if (_dateRange.value != DateRange.ALL_TIME) parts.add(_dateRange.value.displayName)
return parts.joinToString("")
}
private fun isInDateRange(timestamp: Long, range: DateRange): Boolean = when (range) {
DateRange.ALL_TIME -> true
DateRange.TODAY -> isToday(timestamp)
DateRange.THIS_WEEK -> isThisWeek(timestamp)
DateRange.THIS_MONTH -> isThisMonth(timestamp)
DateRange.THIS_YEAR -> isThisYear(timestamp)
}
private fun isToday(timestamp: Long): Boolean {
val today = Calendar.getInstance()
val date = Calendar.getInstance().apply { timeInMillis = timestamp }
return today.get(Calendar.YEAR) == date.get(Calendar.YEAR) &&
today.get(Calendar.DAY_OF_YEAR) == date.get(Calendar.DAY_OF_YEAR)
}
private fun isThisWeek(timestamp: Long): Boolean {
val today = Calendar.getInstance()
val date = Calendar.getInstance().apply { timeInMillis = timestamp }
return today.get(Calendar.YEAR) == date.get(Calendar.YEAR) &&
today.get(Calendar.WEEK_OF_YEAR) == date.get(Calendar.WEEK_OF_YEAR)
}
private fun isThisMonth(timestamp: Long): Boolean {
val today = Calendar.getInstance()
val date = Calendar.getInstance().apply { timeInMillis = timestamp }
return today.get(Calendar.YEAR) == date.get(Calendar.YEAR) &&
today.get(Calendar.MONTH) == date.get(Calendar.MONTH)
}
private fun isThisYear(timestamp: Long): Boolean {
val today = Calendar.getInstance()
val date = Calendar.getInstance().apply { timeInMillis = timestamp }
return today.get(Calendar.YEAR) == date.get(Calendar.YEAR)
}
}
private data class SearchCriteria(
val query: String,
val includedPeople: Set<String>,
val excludedPeople: Set<String>,
val includedTags: Set<String>,
val excludedTags: Set<String>,
val dateRange: DateRange,
val faceFilter: FaceFilter
)
data class ImageWithFaceTags(
val image: ImageEntity,
val faceTags: List<PhotoFaceTagEntity>,
val persons: List<PersonEntity>
)
enum class DateRange(val displayName: String) {
ALL_TIME("All Time"),
TODAY("Today"),
THIS_WEEK("This Week"),
THIS_MONTH("This Month"),
THIS_YEAR("This Year")
}
enum class FaceFilter(val displayName: String) {
ALL("All Photos"),
HAS_FACES("Has Faces"),
NO_FACES("No Faces")
}
@Deprecated("No longer used")
enum class DisplayMode { SIMPLE, VERBOSE }

View File

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package com.placeholder.sherpai2.ui.search.components
import androidx.compose.foundation.Image
import androidx.compose.foundation.layout.aspectRatio
import androidx.compose.foundation.layout.fillMaxWidth
import androidx.compose.runtime.Composable
import androidx.compose.ui.Modifier
import coil.compose.rememberAsyncImagePainter
import com.placeholder.sherpai2.data.local.entity.ImageEntity
/**
* ImageGridItem
*
* Minimal thumbnail preview.
* No click handling yet.
*/
@Composable
fun ImageGridItem(
image: ImageEntity,
modifier: Modifier = Modifier,
onClick: (() -> Unit)? = null
) {
Image(
painter = rememberAsyncImagePainter(image.imageUri),
contentDescription = null,
modifier = Modifier
.fillMaxWidth()
.aspectRatio(1f)
)
}

View File

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package com.placeholder.sherpai2.ui.tags
import androidx.compose.animation.AnimatedVisibility
import androidx.compose.animation.expandVertically
import androidx.compose.animation.fadeIn
import androidx.compose.animation.fadeOut
import androidx.compose.animation.shrinkVertically
import androidx.compose.foundation.background
import androidx.compose.foundation.clickable
import androidx.compose.foundation.layout.*
import androidx.compose.foundation.lazy.LazyColumn
import androidx.compose.foundation.lazy.items
import androidx.compose.foundation.shape.RoundedCornerShape
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.filled.*
import androidx.compose.material3.*
import androidx.compose.runtime.*
import androidx.compose.ui.Alignment
import androidx.compose.ui.Modifier
import androidx.compose.ui.graphics.Brush
import androidx.compose.ui.graphics.vector.ImageVector
import androidx.compose.ui.text.font.FontWeight
import androidx.compose.ui.unit.dp
import androidx.hilt.navigation.compose.hiltViewModel
import com.placeholder.sherpai2.data.local.entity.TagWithUsage
/**
* CLEANED TagManagementScreen - No Scaffold wrapper
*
* Removed:
* - Scaffold wrapper (line 38)
* - Moved FAB inline as part of content
*
* Features:
* - Tag list with usage counts
* - Search functionality
* - Scanning progress
* - Delete tags
* - System/User tag distinction
*/
@Composable
fun TagManagementScreen(
viewModel: TagManagementViewModel = hiltViewModel(),
modifier: Modifier = Modifier
) {
val uiState by viewModel.uiState.collectAsState()
val scanningState by viewModel.scanningState.collectAsState()
var showAddTagDialog by remember { mutableStateOf(false) }
var showScanMenu by remember { mutableStateOf(false) }
var searchQuery by remember { mutableStateOf("") }
Box(modifier = modifier.fillMaxSize()) {
Column(modifier = Modifier.fillMaxSize()) {
// Stats Bar
StatsBar(uiState)
// Search Bar
SearchBar(
searchQuery = searchQuery,
onSearchChange = {
searchQuery = it
viewModel.searchTags(it)
}
)
// Scanning Progress
AnimatedVisibility(
visible = scanningState !is TagManagementViewModel.TagScanningState.Idle,
enter = expandVertically() + fadeIn(),
exit = shrinkVertically() + fadeOut()
) {
ScanningProgress(scanningState, viewModel)
}
// Tag List
when (val state = uiState) {
is TagManagementViewModel.TagUiState.Loading -> {
Box(
modifier = Modifier.fillMaxSize(),
contentAlignment = Alignment.Center
) {
CircularProgressIndicator()
}
}
is TagManagementViewModel.TagUiState.Success -> {
if (state.tags.isEmpty()) {
EmptyTagsView()
} else {
TagList(
tags = state.tags,
onDeleteTag = { viewModel.deleteTag(it) }
)
}
}
is TagManagementViewModel.TagUiState.Error -> {
Box(
modifier = Modifier.fillMaxSize(),
contentAlignment = Alignment.Center
) {
Column(
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.spacedBy(8.dp)
) {
Icon(
Icons.Default.Error,
contentDescription = null,
modifier = Modifier.size(48.dp),
tint = MaterialTheme.colorScheme.error
)
Text(
text = state.message,
color = MaterialTheme.colorScheme.error
)
}
}
}
}
}
// FAB (inline, positioned over content)
ScanFAB(
showMenu = showScanMenu,
onToggleMenu = { showScanMenu = !showScanMenu },
onScanAll = {
viewModel.scanForAllTags()
showScanMenu = false
},
onScanBase = {
viewModel.scanForBaseTags()
showScanMenu = false
},
onScanRelationships = {
viewModel.scanForRelationshipTags()
showScanMenu = false
},
modifier = Modifier
.align(Alignment.BottomEnd)
.padding(16.dp)
)
}
// Add Tag Dialog
if (showAddTagDialog) {
AddTagDialog(
onDismiss = { showAddTagDialog = false },
onConfirm = { tagName ->
viewModel.createUserTag(tagName)
showAddTagDialog = false
}
)
}
}
/**
* Stats bar at top
*/
@Composable
private fun StatsBar(uiState: TagManagementViewModel.TagUiState) {
val (totalTags, totalPhotos) = when (uiState) {
is TagManagementViewModel.TagUiState.Success -> {
val photoCount: Int = uiState.tags.sumOf { it.usageCount }
uiState.tags.size to photoCount
}
else -> 0 to 0
}
Surface(
modifier = Modifier.fillMaxWidth(),
color = MaterialTheme.colorScheme.primaryContainer.copy(alpha = 0.3f)
) {
Row(
modifier = Modifier
.fillMaxWidth()
.padding(16.dp),
horizontalArrangement = Arrangement.SpaceEvenly
) {
StatItem(
icon = Icons.Default.Label,
value = totalTags.toString(),
label = "Tags"
)
VerticalDivider(
modifier = Modifier.height(48.dp),
color = MaterialTheme.colorScheme.outline.copy(alpha = 0.3f)
)
StatItem(
icon = Icons.Default.Photo,
value = totalPhotos.toString(),
label = "Tagged Photos"
)
}
}
}
@Composable
private fun StatItem(icon: ImageVector, value: String, label: String) {
Column(
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.spacedBy(4.dp)
) {
Icon(
icon,
contentDescription = null,
modifier = Modifier.size(24.dp),
tint = MaterialTheme.colorScheme.primary
)
Text(
value,
style = MaterialTheme.typography.headlineSmall,
fontWeight = FontWeight.Bold
)
Text(
label,
style = MaterialTheme.typography.labelMedium,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
/**
* Search bar
*/
@Composable
private fun SearchBar(
searchQuery: String,
onSearchChange: (String) -> Unit
) {
OutlinedTextField(
value = searchQuery,
onValueChange = onSearchChange,
modifier = Modifier
.fillMaxWidth()
.padding(16.dp),
placeholder = { Text("Search tags...") },
leadingIcon = { Icon(Icons.Default.Search, contentDescription = null) },
trailingIcon = {
if (searchQuery.isNotEmpty()) {
IconButton(onClick = { onSearchChange("") }) {
Icon(Icons.Default.Clear, "Clear")
}
}
},
singleLine = true,
shape = RoundedCornerShape(16.dp)
)
}
/**
* Scanning progress indicator
*/
@Composable
private fun ScanningProgress(
scanningState: TagManagementViewModel.TagScanningState,
viewModel: TagManagementViewModel
) {
when (scanningState) {
is TagManagementViewModel.TagScanningState.Scanning -> {
Card(
modifier = Modifier
.fillMaxWidth()
.padding(horizontal = 16.dp, vertical = 8.dp),
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.primaryContainer.copy(alpha = 0.5f)
)
) {
Column(
modifier = Modifier.padding(16.dp),
verticalArrangement = Arrangement.spacedBy(8.dp)
) {
Row(
modifier = Modifier.fillMaxWidth(),
horizontalArrangement = Arrangement.SpaceBetween,
verticalAlignment = Alignment.CenterVertically
) {
Text(
"Scanning: ${scanningState.scanType}",
style = MaterialTheme.typography.titleSmall,
fontWeight = FontWeight.SemiBold
)
Text(
"${scanningState.progress}/${scanningState.total}",
style = MaterialTheme.typography.bodySmall
)
}
LinearProgressIndicator(
progress = {
if (scanningState.total > 0) {
scanningState.progress.toFloat() / scanningState.total.toFloat()
} else {
0f
}
},
modifier = Modifier.fillMaxWidth()
)
Text(
"Tags applied: ${scanningState.tagsApplied}",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.primary
)
if (scanningState.currentImage.isNotEmpty()) {
Text(
"Current: ${scanningState.currentImage}",
style = MaterialTheme.typography.labelSmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
}
}
is TagManagementViewModel.TagScanningState.Complete -> {
Card(
modifier = Modifier
.fillMaxWidth()
.padding(horizontal = 16.dp, vertical = 8.dp),
colors = CardDefaults.cardColors(
containerColor = MaterialTheme.colorScheme.primaryContainer
)
) {
Row(
modifier = Modifier.padding(16.dp),
horizontalArrangement = Arrangement.spacedBy(12.dp),
verticalAlignment = Alignment.CenterVertically
) {
Icon(
Icons.Default.CheckCircle,
contentDescription = null,
tint = MaterialTheme.colorScheme.primary
)
Column {
Text(
"Scan Complete!",
style = MaterialTheme.typography.titleSmall,
fontWeight = FontWeight.Bold
)
Text(
"Processed: ${scanningState.imagesProcessed} images",
style = MaterialTheme.typography.bodySmall
)
Text(
"Applied: ${scanningState.tagsApplied} tags",
style = MaterialTheme.typography.bodySmall
)
if (scanningState.newTagsCreated > 0) {
Text(
"Created: ${scanningState.newTagsCreated} new tags",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.primary
)
}
}
}
}
}
else -> {}
}
}
/**
* Tag list
*/
@Composable
private fun TagList(
tags: List<TagWithUsage>,
onDeleteTag: (String) -> Unit
) {
LazyColumn(
modifier = Modifier.fillMaxSize(),
contentPadding = PaddingValues(16.dp),
verticalArrangement = Arrangement.spacedBy(8.dp)
) {
items(tags) { tagWithUsage ->
TagCard(
tagWithUsage = tagWithUsage,
onDelete = { onDeleteTag(tagWithUsage.tagId) }
)
}
}
}
/**
* Individual tag card
*/
@Composable
private fun TagCard(
tagWithUsage: TagWithUsage,
onDelete: () -> Unit
) {
val isSystemTag = tagWithUsage.type == "SYSTEM"
Card(
modifier = Modifier.fillMaxWidth(),
elevation = CardDefaults.cardElevation(defaultElevation = 2.dp)
) {
Row(
modifier = Modifier.padding(16.dp),
horizontalArrangement = Arrangement.SpaceBetween,
verticalAlignment = Alignment.CenterVertically
) {
Row(
modifier = Modifier.weight(1f),
horizontalArrangement = Arrangement.spacedBy(12.dp),
verticalAlignment = Alignment.CenterVertically
) {
// Tag icon
Surface(
modifier = Modifier.size(40.dp),
shape = RoundedCornerShape(8.dp),
color = if (isSystemTag)
MaterialTheme.colorScheme.primaryContainer
else
MaterialTheme.colorScheme.secondaryContainer
) {
Box(contentAlignment = Alignment.Center) {
Icon(
if (isSystemTag) Icons.Default.AutoAwesome else Icons.Default.Label,
contentDescription = null,
modifier = Modifier.size(20.dp),
tint = if (isSystemTag)
MaterialTheme.colorScheme.onPrimaryContainer
else
MaterialTheme.colorScheme.onSecondaryContainer
)
}
}
// Tag info
Column {
Row(
horizontalArrangement = Arrangement.spacedBy(8.dp),
verticalAlignment = Alignment.CenterVertically
) {
Text(
text = tagWithUsage.value,
style = MaterialTheme.typography.titleMedium,
fontWeight = FontWeight.SemiBold
)
if (isSystemTag) {
Surface(
shape = RoundedCornerShape(4.dp),
color = MaterialTheme.colorScheme.primary.copy(alpha = 0.1f)
) {
Text(
"SYSTEM",
modifier = Modifier.padding(horizontal = 6.dp, vertical = 2.dp),
style = MaterialTheme.typography.labelSmall,
color = MaterialTheme.colorScheme.primary
)
}
}
}
Text(
text = "${tagWithUsage.usageCount} ${if (tagWithUsage.usageCount == 1) "photo" else "photos"}",
style = MaterialTheme.typography.bodySmall,
color = MaterialTheme.colorScheme.onSurfaceVariant
)
}
}
// Delete button (only for user tags)
if (!isSystemTag) {
IconButton(onClick = onDelete) {
Icon(
Icons.Default.Delete,
contentDescription = "Delete",
tint = MaterialTheme.colorScheme.error
)
}
}
}
}
}
/**
* Empty state
*/
@Composable
private fun EmptyTagsView() {
Box(
modifier = Modifier
.fillMaxSize()
.padding(32.dp),
contentAlignment = Alignment.Center
) {
Column(
horizontalAlignment = Alignment.CenterHorizontally,
verticalArrangement = Arrangement.spacedBy(16.dp)
) {
Icon(
Icons.Default.LabelOff,
contentDescription = null,
modifier = Modifier.size(64.dp),
tint = MaterialTheme.colorScheme.onSurfaceVariant.copy(alpha = 0.6f)
)
Text(
"No Tags Yet",
style = MaterialTheme.typography.titleLarge,
fontWeight = FontWeight.Bold
)
Text(
"Scan your photos to generate tags automatically",
style = MaterialTheme.typography.bodyMedium,
color = MaterialTheme.colorScheme.onSurfaceVariant,
textAlign = androidx.compose.ui.text.style.TextAlign.Center
)
}
}
}
/**
* Floating Action Button with scan menu
*/
@Composable
private fun ScanFAB(
showMenu: Boolean,
onToggleMenu: () -> Unit,
onScanAll: () -> Unit,
onScanBase: () -> Unit,
onScanRelationships: () -> Unit,
modifier: Modifier = Modifier
) {
Column(
modifier = modifier,
horizontalAlignment = Alignment.End,
verticalArrangement = Arrangement.spacedBy(8.dp)
) {
// Menu options
AnimatedVisibility(visible = showMenu) {
Column(
horizontalAlignment = Alignment.End,
verticalArrangement = Arrangement.spacedBy(8.dp)
) {
SmallFAB(
icon = Icons.Default.AutoFixHigh,
text = "Scan All",
onClick = onScanAll
)
SmallFAB(
icon = Icons.Default.PhotoCamera,
text = "Base Tags",
onClick = onScanBase
)
SmallFAB(
icon = Icons.Default.People,
text = "Relationships",
onClick = onScanRelationships
)
}
}
// Main FAB
ExtendedFloatingActionButton(
onClick = onToggleMenu,
icon = {
Icon(
if (showMenu) Icons.Default.Close else Icons.Default.AutoFixHigh,
"Scan"
)
},
text = { Text(if (showMenu) "Close" else "Scan Tags") },
containerColor = MaterialTheme.colorScheme.primaryContainer,
contentColor = MaterialTheme.colorScheme.onPrimaryContainer
)
}
}
@Composable
private fun SmallFAB(
icon: ImageVector,
text: String,
onClick: () -> Unit
) {
Row(
verticalAlignment = Alignment.CenterVertically,
horizontalArrangement = Arrangement.spacedBy(8.dp)
) {
Surface(
shape = RoundedCornerShape(8.dp),
color = MaterialTheme.colorScheme.surface,
shadowElevation = 2.dp
) {
Text(
text,
modifier = Modifier.padding(horizontal = 12.dp, vertical = 8.dp),
style = MaterialTheme.typography.bodySmall,
fontWeight = FontWeight.Medium
)
}
FloatingActionButton(
onClick = onClick,
modifier = Modifier.size(48.dp),
containerColor = MaterialTheme.colorScheme.secondaryContainer,
contentColor = MaterialTheme.colorScheme.onSecondaryContainer
) {
Icon(icon, contentDescription = text, modifier = Modifier.size(20.dp))
}
}
}
/**
* Add tag dialog
*/
@Composable
private fun AddTagDialog(
onDismiss: () -> Unit,
onConfirm: (String) -> Unit
) {
var tagName by remember { mutableStateOf("") }
AlertDialog(
onDismissRequest = onDismiss,
icon = { Icon(Icons.Default.Add, contentDescription = null) },
title = { Text("Add Custom Tag") },
text = {
OutlinedTextField(
value = tagName,
onValueChange = { tagName = it },
label = { Text("Tag Name") },
singleLine = true,
modifier = Modifier.fillMaxWidth()
)
},
confirmButton = {
Button(
onClick = { onConfirm(tagName) },
enabled = tagName.isNotBlank()
) {
Text("Add")
}
},
dismissButton = {
TextButton(onClick = onDismiss) {
Text("Cancel")
}
}
)
}

View File

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package com.placeholder.sherpai2.ui.tags
import android.app.Application
import android.graphics.BitmapFactory
import android.net.Uri
import androidx.lifecycle.AndroidViewModel
import androidx.lifecycle.viewModelScope
import com.google.mlkit.vision.common.InputImage
import com.google.mlkit.vision.face.FaceDetection
import com.google.mlkit.vision.face.FaceDetectorOptions
import com.placeholder.sherpai2.data.local.dao.ImageTagDao
import com.placeholder.sherpai2.data.local.dao.TagDao
import com.placeholder.sherpai2.data.local.entity.TagEntity
import com.placeholder.sherpai2.data.local.entity.TagWithUsage
import com.placeholder.sherpai2.data.repository.DetectedFace
import com.placeholder.sherpai2.data.service.AutoTaggingService
import com.placeholder.sherpai2.domain.repository.ImageRepository
import com.placeholder.sherpai2.util.DiagnosticLogger
import dagger.hilt.android.lifecycle.HiltViewModel
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.flow.MutableStateFlow
import kotlinx.coroutines.flow.StateFlow
import kotlinx.coroutines.flow.asStateFlow
import kotlinx.coroutines.flow.first
import kotlinx.coroutines.launch
import kotlinx.coroutines.withContext
import kotlinx.coroutines.tasks.await
import javax.inject.Inject
@HiltViewModel
class TagManagementViewModel @Inject constructor(
application: Application,
private val tagDao: TagDao,
private val imageTagDao: ImageTagDao,
private val imageRepository: ImageRepository,
private val autoTaggingService: AutoTaggingService
) : AndroidViewModel(application) {
private val _uiState = MutableStateFlow<TagUiState>(TagUiState.Loading)
val uiState: StateFlow<TagUiState> = _uiState.asStateFlow()
private val _scanningState = MutableStateFlow<TagScanningState>(TagScanningState.Idle)
val scanningState: StateFlow<TagScanningState> = _scanningState.asStateFlow()
private val faceDetector by lazy {
val options = FaceDetectorOptions.Builder()
.setPerformanceMode(FaceDetectorOptions.PERFORMANCE_MODE_ACCURATE)
.setLandmarkMode(FaceDetectorOptions.LANDMARK_MODE_NONE)
.setClassificationMode(FaceDetectorOptions.CLASSIFICATION_MODE_NONE)
.setMinFaceSize(0.10f)
.build()
FaceDetection.getClient(options)
}
sealed class TagUiState {
object Loading : TagUiState()
data class Success(
val tags: List<TagWithUsage>,
val totalTags: Int,
val systemTags: Int,
val userTags: Int
) : TagUiState()
data class Error(val message: String) : TagUiState()
}
sealed class TagScanningState {
object Idle : TagScanningState()
data class Scanning(
val scanType: ScanType,
val progress: Int,
val total: Int,
val tagsApplied: Int,
val currentImage: String = ""
) : TagScanningState()
data class Complete(
val scanType: ScanType,
val imagesProcessed: Int,
val tagsApplied: Int,
val newTagsCreated: Int = 0
) : TagScanningState()
data class Error(val message: String) : TagScanningState()
}
enum class ScanType {
BASE_TAGS, // Face count, orientation, resolution, time-of-day
RELATIONSHIP_TAGS, // Family, friend, colleague from person entities
BIRTHDAY_TAGS, // Birthday tags for DOB matches
SCENE_TAGS, // Indoor/outdoor estimation
ALL // Run all scans
}
init {
loadTags()
}
fun loadTags() {
viewModelScope.launch {
try {
_uiState.value = TagUiState.Loading
val tagsWithUsage = tagDao.getMostUsedTags(1000) // Get all tags
val systemTags = tagsWithUsage.count { it.type == "SYSTEM" }
val userTags = tagsWithUsage.count { it.type == "GENERIC" }
_uiState.value = TagUiState.Success(
tags = tagsWithUsage,
totalTags = tagsWithUsage.size,
systemTags = systemTags,
userTags = userTags
)
} catch (e: Exception) {
_uiState.value = TagUiState.Error(
e.message ?: "Failed to load tags"
)
}
}
}
fun createUserTag(tagName: String) {
viewModelScope.launch {
try {
val trimmedName = tagName.trim().lowercase()
if (trimmedName.isEmpty()) {
_uiState.value = TagUiState.Error("Tag name cannot be empty")
return@launch
}
// Check if tag already exists
val existing = tagDao.getByValue(trimmedName)
if (existing != null) {
_uiState.value = TagUiState.Error("Tag '$trimmedName' already exists")
return@launch
}
val newTag = TagEntity.createUserTag(trimmedName)
tagDao.insert(newTag)
loadTags()
} catch (e: Exception) {
_uiState.value = TagUiState.Error(
"Failed to create tag: ${e.message}"
)
}
}
}
fun deleteTag(tagId: String) {
viewModelScope.launch {
try {
tagDao.delete(tagId)
loadTags()
} catch (e: Exception) {
_uiState.value = TagUiState.Error(
"Failed to delete tag: ${e.message}"
)
}
}
}
fun searchTags(query: String) {
viewModelScope.launch {
try {
val results = if (query.isBlank()) {
tagDao.getMostUsedTags(1000)
} else {
tagDao.searchTagsWithUsage(query, 100)
}
val systemTags = results.count { it.type == "SYSTEM" }
val userTags = results.count { it.type == "GENERIC" }
_uiState.value = TagUiState.Success(
tags = results,
totalTags = results.size,
systemTags = systemTags,
userTags = userTags
)
} catch (e: Exception) {
_uiState.value = TagUiState.Error("Search failed: ${e.message}")
}
}
}
// ======================
// AUTO-TAGGING SCANS
// ======================
/**
* Scan library for base tags (face count, orientation, time, quality, scene)
*/
fun scanForBaseTags() {
performScan(ScanType.BASE_TAGS)
}
/**
* Scan for relationship tags (family, friend, colleague)
*/
fun scanForRelationshipTags() {
performScan(ScanType.RELATIONSHIP_TAGS)
}
/**
* Scan for birthday tags
*/
fun scanForBirthdayTags() {
performScan(ScanType.BIRTHDAY_TAGS)
}
/**
* Scan for scene tags (indoor/outdoor)
*/
fun scanForSceneTags() {
performScan(ScanType.SCENE_TAGS)
}
/**
* Scan for ALL tags
*/
fun scanForAllTags() {
performScan(ScanType.ALL)
}
private fun performScan(scanType: ScanType) {
viewModelScope.launch {
try {
DiagnosticLogger.i("=== STARTING TAG SCAN: $scanType ===")
_scanningState.value = TagScanningState.Scanning(
scanType = scanType,
progress = 0,
total = 0,
tagsApplied = 0
)
val allImages = imageRepository.getAllImages().first()
var tagsApplied = 0
var newTagsCreated = 0
DiagnosticLogger.i("Processing ${allImages.size} images")
allImages.forEachIndexed { index, imageWithEverything ->
val image = imageWithEverything.image
_scanningState.value = TagScanningState.Scanning(
scanType = scanType,
progress = index + 1,
total = allImages.size,
tagsApplied = tagsApplied,
currentImage = image.imageId.take(8)
)
when (scanType) {
ScanType.BASE_TAGS -> {
tagsApplied += scanImageForBaseTags(image.imageUri, image)
}
ScanType.SCENE_TAGS -> {
tagsApplied += scanImageForSceneTags(image.imageUri, image)
}
ScanType.RELATIONSHIP_TAGS -> {
// Handled at person level, not per-image
}
ScanType.BIRTHDAY_TAGS -> {
// Handled at person level, not per-image
}
ScanType.ALL -> {
tagsApplied += scanImageForBaseTags(image.imageUri, image)
tagsApplied += scanImageForSceneTags(image.imageUri, image)
}
}
}
// Handle person-level scans
if (scanType == ScanType.RELATIONSHIP_TAGS || scanType == ScanType.ALL) {
DiagnosticLogger.i("Scanning relationship tags...")
tagsApplied += autoTaggingService.autoTagAllRelationships()
}
if (scanType == ScanType.BIRTHDAY_TAGS || scanType == ScanType.ALL) {
DiagnosticLogger.i("Scanning birthday tags...")
tagsApplied += autoTaggingService.autoTagAllBirthdays(daysRange = 3)
}
DiagnosticLogger.i("=== SCAN COMPLETE ===")
DiagnosticLogger.i("Images processed: ${allImages.size}")
DiagnosticLogger.i("Tags applied: $tagsApplied")
_scanningState.value = TagScanningState.Complete(
scanType = scanType,
imagesProcessed = allImages.size,
tagsApplied = tagsApplied,
newTagsCreated = newTagsCreated
)
loadTags()
} catch (e: Exception) {
DiagnosticLogger.e("Scan failed", e)
_scanningState.value = TagScanningState.Error(
"Scan failed: ${e.message}"
)
}
}
}
private suspend fun scanImageForBaseTags(
imageUri: String,
image: com.placeholder.sherpai2.data.local.entity.ImageEntity
): Int = withContext(Dispatchers.Default) {
try {
val uri = Uri.parse(imageUri)
val inputStream = getApplication<Application>().contentResolver.openInputStream(uri)
val bitmap = BitmapFactory.decodeStream(inputStream)
inputStream?.close()
if (bitmap == null) return@withContext 0
// Detect faces
val detectedFaces = detectFaces(bitmap)
// Auto-tag with base tags
autoTaggingService.autoTagImage(image, bitmap, detectedFaces)
} catch (e: Exception) {
DiagnosticLogger.e("Base tag scan failed for $imageUri", e)
0
}
}
private suspend fun scanImageForSceneTags(
imageUri: String,
image: com.placeholder.sherpai2.data.local.entity.ImageEntity
): Int = withContext(Dispatchers.Default) {
try {
val uri = Uri.parse(imageUri)
val inputStream = getApplication<Application>().contentResolver.openInputStream(uri)
val bitmap = BitmapFactory.decodeStream(inputStream)
inputStream?.close()
if (bitmap == null) return@withContext 0
// Only auto-tag scene tags (indoor/outdoor already included in autoTagImage)
// This is a subset of base tags, so we don't need separate logic
0
} catch (e: Exception) {
DiagnosticLogger.e("Scene tag scan failed for $imageUri", e)
0
}
}
private suspend fun detectFaces(bitmap: android.graphics.Bitmap): List<DetectedFace> = withContext(Dispatchers.Default) {
try {
val image = InputImage.fromBitmap(bitmap, 0)
val faces = faceDetector.process(image).await()
faces.mapNotNull { face ->
val boundingBox = face.boundingBox
val croppedFace = try {
val left = boundingBox.left.coerceAtLeast(0)
val top = boundingBox.top.coerceAtLeast(0)
val width = boundingBox.width().coerceAtMost(bitmap.width - left)
val height = boundingBox.height().coerceAtMost(bitmap.height - top)
if (width > 0 && height > 0) {
android.graphics.Bitmap.createBitmap(bitmap, left, top, width, height)
} else {
null
}
} catch (e: Exception) {
null
}
if (croppedFace != null) {
DetectedFace(
croppedBitmap = croppedFace,
boundingBox = boundingBox
)
} else {
null
}
}
} catch (e: Exception) {
emptyList()
}
}
fun resetScanningState() {
_scanningState.value = TagScanningState.Idle
}
override fun onCleared() {
super.onCleared()
faceDetector.close()
}
}

View File

@@ -0,0 +1,77 @@
// TourScreen.kt
package com.placeholder.sherpai2.ui.tour
import androidx.compose.foundation.background
import androidx.compose.foundation.layout.*
import androidx.compose.foundation.lazy.LazyColumn
import androidx.compose.foundation.lazy.items
import androidx.compose.foundation.rememberScrollState
import androidx.compose.foundation.verticalScroll
import androidx.compose.material3.*
import androidx.compose.runtime.*
import androidx.compose.ui.Modifier
import androidx.compose.ui.unit.dp
import androidx.hilt.navigation.compose.hiltViewModel
import com.placeholder.sherpai2.data.local.model.ImageWithEverything
@Composable
fun TourScreen(tourViewModel: TourViewModel = hiltViewModel(), onImageClick: (String) -> Unit) {
val images by tourViewModel.recentImages.collectAsState()
Column(modifier = Modifier.fillMaxSize()) {
// Header with image count
Text(
text = "Gallery (${images.size} images)",
style = MaterialTheme.typography.titleLarge,
modifier = Modifier.padding(16.dp)
)
LazyColumn(
modifier = Modifier.fillMaxSize(),
contentPadding = PaddingValues(16.dp)
) {
items(images) { image ->
ImageCard(image)
Spacer(modifier = Modifier.height(12.dp))
}
}
}
}
@Composable
fun ImageCard(image: ImageWithEverything) {
Card(modifier = Modifier.fillMaxWidth(), elevation = CardDefaults.cardElevation(4.dp)) {
Column(modifier = Modifier.padding(12.dp)) {
Text(text = image.tags.toString(), style = MaterialTheme.typography.bodyMedium)
// Tags row with placeholders if fewer than 3
Row(modifier = Modifier.padding(top = 8.dp)) {
val tags = image.tags.map { it.tagId } // adjust depending on your entity
tags.forEach { tag ->
TagComposable(tag)
}
repeat(3 - tags.size.coerceAtMost(3)) {
TagComposable("") // empty placeholder
}
}
}
}
}
@Composable
fun TagComposable(tag: String) {
Box(
modifier = Modifier
.padding(end = 4.dp)
.height(24.dp)
.widthIn(min = 40.dp)
.background(MaterialTheme.colorScheme.primaryContainer, MaterialTheme.shapes.small),
contentAlignment = androidx.compose.ui.Alignment.Center
) {
Text(
text = if (tag.isNotBlank()) tag else " ",
style = MaterialTheme.typography.labelSmall,
modifier = Modifier.padding(horizontal = 6.dp)
)
}
}

View File

@@ -0,0 +1,39 @@
// TourViewModel.kt
package com.placeholder.sherpai2.ui.tour
import androidx.lifecycle.ViewModel
import androidx.lifecycle.viewModelScope
import com.placeholder.sherpai2.domain.repository.ImageRepository
import com.placeholder.sherpai2.data.local.model.ImageWithEverything
import dagger.hilt.android.lifecycle.HiltViewModel
import kotlinx.coroutines.flow.*
import kotlinx.coroutines.launch
import javax.inject.Inject
@HiltViewModel
class TourViewModel @Inject constructor(
private val imageRepository: ImageRepository
) : ViewModel() {
// Expose recent images as StateFlow
private val _recentImages = MutableStateFlow<List<ImageWithEverything>>(emptyList())
val recentImages: StateFlow<List<ImageWithEverything>> = _recentImages.asStateFlow()
init {
loadRecentImages()
}
private fun loadRecentImages(limit: Int = 100) {
viewModelScope.launch {
imageRepository.getRecentImages(limit)
.catch { e ->
println("TourViewModel: error fetching images: $e")
_recentImages.value = emptyList()
}
.collect { images ->
println("TourViewModel: fetched ${images.size} images")
_recentImages.value = images
}
}
}
}

View File

@@ -0,0 +1,197 @@
package com.placeholder.sherpai2.ui.trainingprep
import android.os.Build
import android.view.View
import android.view.autofill.AutofillManager
import androidx.annotation.RequiresApi
import androidx.compose.foundation.layout.*
import androidx.compose.foundation.rememberScrollState
import androidx.compose.foundation.shape.RoundedCornerShape
import androidx.compose.foundation.verticalScroll
import androidx.compose.material.icons.Icons
import androidx.compose.material.icons.filled.*
import androidx.compose.material3.*
import androidx.compose.runtime.*
import androidx.compose.ui.Alignment
import androidx.compose.ui.Modifier
import androidx.compose.ui.platform.LocalView
import androidx.compose.ui.text.font.FontWeight
import androidx.compose.ui.text.input.KeyboardCapitalization
import androidx.compose.ui.unit.dp
import androidx.compose.ui.window.Dialog
import androidx.compose.ui.window.DialogProperties
import java.text.SimpleDateFormat
import java.util.*
@RequiresApi(Build.VERSION_CODES.O)
@OptIn(ExperimentalMaterial3Api::class)
@Composable
fun BeautifulPersonInfoDialog(
onDismiss: () -> Unit,
onConfirm: (name: String, dateOfBirth: Long?, relationship: String) -> Unit
) {
var name by remember { mutableStateOf("") }
var dateOfBirth by remember { mutableStateOf<Long?>(null) }
var selectedRelationship by remember { mutableStateOf("Other") }
var showDatePicker by remember { mutableStateOf(false) }
// ✅ Disable autofill for this dialog
val view = LocalView.current
DisposableEffect(Unit) {
val autofillManager = view.context.getSystemService(AutofillManager::class.java)
view.importantForAutofill = View.IMPORTANT_FOR_AUTOFILL_NO_EXCLUDE_DESCENDANTS
onDispose {
view.importantForAutofill = View.IMPORTANT_FOR_AUTOFILL_AUTO
}
}
val relationships = listOf(
"Family" to "👨‍👩‍👧‍👦",
"Friend" to "🤝",
"Partner" to "❤️",
"Parent" to "👪",
"Sibling" to "👫",
"Colleague" to "💼"
)
Dialog(
onDismissRequest = onDismiss,
properties = DialogProperties(usePlatformDefaultWidth = false)
) {
Card(
modifier = Modifier.fillMaxWidth(0.92f).fillMaxHeight(0.85f),
shape = RoundedCornerShape(28.dp),
colors = CardDefaults.cardColors(containerColor = MaterialTheme.colorScheme.surface),
elevation = CardDefaults.cardElevation(defaultElevation = 8.dp)
) {
Column(modifier = Modifier.fillMaxSize()) {
Row(
modifier = Modifier.fillMaxWidth().padding(24.dp),
horizontalArrangement = Arrangement.SpaceBetween,
verticalAlignment = Alignment.CenterVertically
) {
Row(horizontalArrangement = Arrangement.spacedBy(16.dp), verticalAlignment = Alignment.CenterVertically) {
Surface(shape = RoundedCornerShape(16.dp), color = MaterialTheme.colorScheme.primaryContainer, modifier = Modifier.size(64.dp)) {
Box(contentAlignment = Alignment.Center) {
Icon(Icons.Default.Person, contentDescription = null, modifier = Modifier.size(36.dp), tint = MaterialTheme.colorScheme.primary)
}
}
Column {
Text("Person Details", style = MaterialTheme.typography.headlineMedium, fontWeight = FontWeight.Bold)
Text("Help us organize your photos", style = MaterialTheme.typography.bodyMedium, color = MaterialTheme.colorScheme.onSurfaceVariant)
}
}
IconButton(onClick = onDismiss) {
Icon(Icons.Default.Close, contentDescription = "Close", modifier = Modifier.size(24.dp))
}
}
HorizontalDivider(color = MaterialTheme.colorScheme.outlineVariant)
Column(modifier = Modifier.weight(1f).verticalScroll(rememberScrollState()).padding(24.dp), verticalArrangement = Arrangement.spacedBy(24.dp)) {
Column(verticalArrangement = Arrangement.spacedBy(8.dp)) {
Text("Name *", style = MaterialTheme.typography.titleSmall, fontWeight = FontWeight.SemiBold, color = MaterialTheme.colorScheme.primary)
OutlinedTextField(
value = name,
onValueChange = { name = it },
placeholder = { Text("e.g., John Doe") },
leadingIcon = { Icon(Icons.Default.Face, contentDescription = null) },
modifier = Modifier.fillMaxWidth(),
singleLine = true,
shape = RoundedCornerShape(16.dp),
keyboardOptions = androidx.compose.foundation.text.KeyboardOptions(
capitalization = KeyboardCapitalization.Words,
autoCorrect = false
)
)
}
Column(verticalArrangement = Arrangement.spacedBy(8.dp)) {
Text("Birthday", style = MaterialTheme.typography.titleSmall, fontWeight = FontWeight.SemiBold, color = MaterialTheme.colorScheme.primary)
OutlinedTextField(
value = dateOfBirth?.let { SimpleDateFormat("MMM d, yyyy", Locale.getDefault()).format(Date(it)) } ?: "",
onValueChange = {},
readOnly = true,
placeholder = { Text("Select birthday") },
leadingIcon = { Icon(Icons.Default.Cake, contentDescription = null) },
trailingIcon = {
IconButton(onClick = { showDatePicker = true }) {
Icon(Icons.Default.CalendarToday, contentDescription = "Select date")
}
},
modifier = Modifier.fillMaxWidth(),
singleLine = true,
shape = RoundedCornerShape(16.dp)
)
}
Column(verticalArrangement = Arrangement.spacedBy(8.dp)) {
Text("Relationship", style = MaterialTheme.typography.titleSmall, fontWeight = FontWeight.SemiBold, color = MaterialTheme.colorScheme.primary)
var expanded by remember { mutableStateOf(false) }
ExposedDropdownMenuBox(expanded = expanded, onExpandedChange = { expanded = it }) {
OutlinedTextField(
value = selectedRelationship,
onValueChange = {},
readOnly = true,
leadingIcon = { Icon(Icons.Default.People, contentDescription = null) },
trailingIcon = { ExposedDropdownMenuDefaults.TrailingIcon(expanded = expanded) },
modifier = Modifier.fillMaxWidth().menuAnchor(),
singleLine = true,
shape = RoundedCornerShape(16.dp),
colors = ExposedDropdownMenuDefaults.outlinedTextFieldColors()
)
ExposedDropdownMenu(expanded = expanded, onDismissRequest = { expanded = false }) {
relationships.forEach { (relationship, emoji) ->
DropdownMenuItem(text = { Text("$emoji $relationship") }, onClick = { selectedRelationship = relationship; expanded = false })
}
}
}
}
Card(colors = CardDefaults.cardColors(containerColor = MaterialTheme.colorScheme.tertiaryContainer.copy(alpha = 0.3f)), shape = RoundedCornerShape(12.dp)) {
Row(modifier = Modifier.padding(16.dp), horizontalArrangement = Arrangement.spacedBy(12.dp)) {
Icon(Icons.Default.Lock, contentDescription = null, tint = MaterialTheme.colorScheme.tertiary, modifier = Modifier.size(20.dp))
Text("All information stays private on your device", style = MaterialTheme.typography.bodySmall, color = MaterialTheme.colorScheme.onTertiaryContainer)
}
}
}
HorizontalDivider(color = MaterialTheme.colorScheme.outlineVariant)
Row(modifier = Modifier.fillMaxWidth().padding(24.dp), horizontalArrangement = Arrangement.spacedBy(12.dp)) {
OutlinedButton(onClick = onDismiss, modifier = Modifier.weight(1f).height(56.dp), shape = RoundedCornerShape(16.dp)) {
Text("Cancel", style = MaterialTheme.typography.titleMedium)
}
Button(
onClick = { onConfirm(name.trim(), dateOfBirth, selectedRelationship) },
enabled = name.trim().isNotEmpty(),
modifier = Modifier.weight(1f).height(56.dp),
shape = RoundedCornerShape(16.dp)
) {
Icon(Icons.Default.Check, contentDescription = null, modifier = Modifier.size(20.dp))
Spacer(Modifier.width(8.dp))
Text("Continue", style = MaterialTheme.typography.titleMedium, fontWeight = FontWeight.Bold)
}
}
}
}
}
if (showDatePicker) {
val datePickerState = rememberDatePickerState(initialSelectedDateMillis = dateOfBirth ?: System.currentTimeMillis())
DatePickerDialog(
onDismissRequest = { showDatePicker = false },
confirmButton = { TextButton(onClick = { dateOfBirth = datePickerState.selectedDateMillis; showDatePicker = false }) { Text("OK") } },
dismissButton = { TextButton(onClick = { showDatePicker = false }) { Text("Cancel") } }
) {
DatePicker(state = datePickerState)
}
}
}

View File

@@ -0,0 +1,159 @@
package com.placeholder.sherpai2.ui.trainingprep
import android.content.Context
import android.graphics.Bitmap
import android.graphics.BitmapFactory
import android.net.Uri
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.withContext
import java.io.InputStream
/**
* Helper class for detecting duplicate or near-duplicate images using perceptual hashing
*/
class DuplicateImageDetector(private val context: Context) {
data class DuplicateCheckResult(
val hasDuplicates: Boolean,
val duplicateGroups: List<DuplicateGroup>,
val uniqueImageCount: Int
)
data class DuplicateGroup(
val images: List<Uri>,
val similarity: Double
)
private data class ImageHash(
val uri: Uri,
val hash: Long
)
/**
* Check for duplicate images in the provided list
*/
suspend fun checkForDuplicates(
uris: List<Uri>,
similarityThreshold: Double = 0.95
): DuplicateCheckResult = withContext(Dispatchers.Default) {
if (uris.size < 2) {
return@withContext DuplicateCheckResult(
hasDuplicates = false,
duplicateGroups = emptyList(),
uniqueImageCount = uris.size
)
}
// Compute perceptual hash for each image
val imageHashes = uris.mapNotNull { uri ->
try {
val bitmap = loadBitmap(uri)
bitmap?.let {
val hash = computePerceptualHash(it)
ImageHash(uri, hash)
}
} catch (e: Exception) {
null
}
}
// Find duplicate groups
val duplicateGroups = mutableListOf<DuplicateGroup>()
val processed = mutableSetOf<Uri>()
for (i in imageHashes.indices) {
if (imageHashes[i].uri in processed) continue
val currentGroup = mutableListOf(imageHashes[i].uri)
for (j in i + 1 until imageHashes.size) {
if (imageHashes[j].uri in processed) continue
val similarity = calculateSimilarity(imageHashes[i].hash, imageHashes[j].hash)
if (similarity >= similarityThreshold) {
currentGroup.add(imageHashes[j].uri)
processed.add(imageHashes[j].uri)
}
}
if (currentGroup.size > 1) {
duplicateGroups.add(
DuplicateGroup(
images = currentGroup,
similarity = 1.0
)
)
processed.addAll(currentGroup)
}
}
DuplicateCheckResult(
hasDuplicates = duplicateGroups.isNotEmpty(),
duplicateGroups = duplicateGroups,
uniqueImageCount = uris.size - duplicateGroups.sumOf { it.images.size - 1 }
)
}
/**
* Compute perceptual hash using difference hash (dHash) algorithm
*/
private fun computePerceptualHash(bitmap: Bitmap): Long {
// Resize to 9x8
val resized = Bitmap.createScaledBitmap(bitmap, 9, 8, false)
var hash = 0L
var bitIndex = 0
for (y in 0 until 8) {
for (x in 0 until 8) {
val leftPixel = resized.getPixel(x, y)
val rightPixel = resized.getPixel(x + 1, y)
val leftGray = toGrayscale(leftPixel)
val rightGray = toGrayscale(rightPixel)
if (leftGray > rightGray) {
hash = hash or (1L shl bitIndex)
}
bitIndex++
}
}
resized.recycle()
return hash
}
/**
* Convert RGB pixel to grayscale value
*/
private fun toGrayscale(pixel: Int): Int {
val r = (pixel shr 16) and 0xFF
val g = (pixel shr 8) and 0xFF
val b = pixel and 0xFF
return (0.299 * r + 0.587 * g + 0.114 * b).toInt()
}
/**
* Calculate similarity between two hashes
*/
private fun calculateSimilarity(hash1: Long, hash2: Long): Double {
val xor = hash1 xor hash2
val hammingDistance = xor.countOneBits()
return 1.0 - (hammingDistance / 64.0)
}
/**
* Load bitmap from URI
*/
private fun loadBitmap(uri: Uri): Bitmap? {
return try {
val inputStream: InputStream? = context.contentResolver.openInputStream(uri)
BitmapFactory.decodeStream(inputStream)?.also {
inputStream?.close()
}
} catch (e: Exception) {
null
}
}
}

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