Feature identity recognition 2100793612207388938#154
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This change introduces face recognition capabilities to track specific people across project photos. - Added TensorFlow Lite dependencies and a dummy MobileFaceNet model. - Created `FaceRecognitionHelper` to generate face embeddings. - Updated `ProjectEntity` and database schema to store target embeddings. - Enhanced `ProjectViewModel` to support "Track This Person" and smart re-alignment using cosine similarity. - Updated UI to expose the new tracking feature. - Optimized threading (Dispatchers.Default/IO) and memory management (Bitmap recycling) for heavy TFLite operations. Co-authored-by: harrydbarnes <145344818+harrydbarnes@users.noreply.github.com>
This change introduces face recognition capabilities to track specific people across project photos. - Added TensorFlow Lite dependencies and a dummy MobileFaceNet model. - Created `FaceRecognitionHelper` to generate face embeddings. - Updated `ProjectEntity` and database schema to store target embeddings. - Enhanced `ProjectViewModel` to support "Track This Person" and smart re-alignment using cosine similarity. - Updated UI to expose the new tracking feature. - Optimized threading (Dispatchers.Default/IO) and memory management (Bitmap recycling, single load per photo) for heavy TFLite operations. - Refactored `FaceDetectorHelper` to support bitmap input for efficiency. Co-authored-by: harrydbarnes <145344818+harrydbarnes@users.noreply.github.com>
This change addresses review feedback by fixing a syntax error, preventing memory leaks, optimizing embedding storage, and improving code readability. - Fixed syntax error in `ProjectViewModel.kt` (extra brace). - Implemented `close()` in `FaceRecognitionHelper` and ensured `GpuDelegate` is closed to prevent memory leaks. - Optimized embedding storage: Changed `targetEmbedding` from String to BLOB (ByteArray) in Entity and Database, using `ByteBuffer` for efficient FloatArray conversion. Updated `MIGRATION_4_5`. - Refactored `ProjectViewModel.kt`: Split `processFacesInternal` into `processFacesWithTarget` and `processFacesSpatial` for better readability and maintainability. - Updated `Project` domain model to use `FloatArray` for embeddings. Co-authored-by: harrydbarnes <145344818+harrydbarnes@users.noreply.github.com>
This update addresses critical review feedback by fixing syntax errors, optimizing performance, and ensuring thread safety. - Fixed `ProjectViewModel` syntax (removed extra brace). - Refactored `FaceRecognitionHelper` to include a thread-safe `suspend fun close()` using `Mutex` for proper cleanup of TFLite resources. - Optimized database storage by switching `targetEmbedding` to `BLOB` (ByteArray) using `ByteBuffer`, replacing inefficient String storage. Updated migrations and mappers. - Parallelized face processing in `ProjectViewModel` using `coroutineScope` and `async/awaitAll` for improved performance on large datasets. - Refactored logic into `processFacesWithTarget` and `processFacesSpatial` for better readability. - Corrected status handling to ensure failed photo loads do not mark photos as processed. Co-authored-by: harrydbarnes <145344818+harrydbarnes@users.noreply.github.com>
This update addresses critical review feedback by fixing syntax errors, optimizing performance, and ensuring thread safety. - Fixed `ProjectViewModel` syntax (removed extra brace). - Refactored `FaceRecognitionHelper` to include a thread-safe `suspend fun close()` using `Mutex` for proper cleanup of TFLite resources. - Optimized database storage by switching `targetEmbedding` to `BLOB` (ByteArray) using `ByteBuffer`, replacing inefficient String storage. Updated migrations and mappers. - Parallelized face processing in `ProjectViewModel` using `coroutineScope` and `async/awaitAll` with a `Semaphore(4)` to improve performance on large datasets while preventing OOM. - Refactored logic into `processFacesWithTarget` and `processFacesSpatial` for better readability. - Corrected status handling to ensure failed photo loads do not mark photos as processed. - Removed `@Singleton` from `FaceRecognitionHelper` and implemented cleanup in `ProjectViewModel.onCleared()`. Co-authored-by: harrydbarnes <145344818+harrydbarnes@users.noreply.github.com>
This update addresses critical review feedback by fixing syntax errors, optimizing performance, and ensuring thread safety. - Fixed `ProjectViewModel` syntax (removed extra brace). - Refactored `FaceRecognitionHelper` to include a thread-safe `suspend fun close()` using `Mutex` for proper cleanup of TFLite resources. - Optimized database storage by switching `targetEmbedding` to `BLOB` (ByteArray) using `ByteBuffer`, replacing inefficient String storage. Updated migrations and mappers. - Parallelized face processing in `ProjectViewModel` using `coroutineScope` and `async/awaitAll` with a `Semaphore(4)` to improve performance on large datasets while preventing OOM. - Refactored logic into `processFacesWithTarget` and `processFacesSpatial` for better readability. - Corrected status handling to ensure failed photo loads do not mark photos as processed. - Removed `@Singleton` from `FaceRecognitionHelper` and implemented cleanup in `ProjectViewModel.onCleared()`. - Replaced `semaphore.withPermit` with `acquire`/`release` to support suspending calls. - Fixed `processFacesSpatial` loop compilation error. Co-authored-by: harrydbarnes <145344818+harrydbarnes@users.noreply.github.com>
This update addresses critical review feedback by fixing syntax errors, optimizing performance, and ensuring thread safety. - Fixed `ProjectViewModel` syntax (removed extra brace). - Refactored `FaceRecognitionHelper` to include a thread-safe `suspend fun close()` using `Mutex` for proper cleanup of TFLite resources. - Optimized database storage by switching `targetEmbedding` to `BLOB` (ByteArray) using `ByteBuffer`, replacing inefficient String storage. Updated migrations and mappers. - Parallelized face processing in `ProjectViewModel` using `coroutineScope` and `async/awaitAll` with a `Semaphore(4)` to improve performance on large datasets while preventing OOM. - Refactored logic into `processFacesWithTarget` and `processFacesSpatial` for better readability. - Corrected status handling to ensure failed photo loads do not mark photos as processed. - Removed `@Singleton` from `FaceRecognitionHelper` and implemented cleanup in `ProjectViewModel.onCleared()`. - Replaced `semaphore.withPermit` with `acquire`/`release` to support suspending calls. - Fixed `processFacesSpatial` loop compilation error. - Fixed initialization race condition in `FaceRecognitionHelper`. - Used `runBlocking` in `onCleared` to ensure TFLite cleanup. - Ensured loading state is reset when project data is missing. Co-authored-by: harrydbarnes <145344818+harrydbarnes@users.noreply.github.com>
Summary of ChangesHello @harrydbarnes, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request introduces face recognition capabilities to the app using TensorFlow Lite. It includes adding necessary dependencies, implementing a helper class for face embedding extraction, updating project entities to store target embeddings, and enhancing the face alignment process to track a selected person across frames. This enables a 'smart' face alignment feature that focuses on a specific individual. Highlights
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Code Review
This pull request introduces a significant new feature: identity recognition for tracking a specific person across photos. The implementation is robust, leveraging TensorFlow Lite for face embeddings and coroutines for efficient, parallel processing. The changes are well-structured, with clear separation of concerns in the new FaceRecognitionHelper and updates to the ViewModel, database, and UI. My review focuses on minor refinements to enhance code clarity, improve user experience by preventing potential UI flicker, and adhere to best practices like using string resources and named constants. Overall, this is an excellent contribution.
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