This commit introduces new API endpoints for retrieving a list of people for auto-matching and fetching matches for specific individuals. The frontend has been updated to utilize these endpoints, allowing for lazy loading of matches and improved state management. The AutoMatch component now supports caching of matches and session storage for user settings, enhancing performance and user experience. Documentation has been updated to reflect these changes.
This commit refactors the tag management system by removing the linkage type parameter from various components, including the API and frontend. The changes streamline the process of adding and removing tags, allowing for both single and bulk tags to be handled uniformly. The UI has been updated to reflect these changes, enhancing user experience and simplifying the codebase. Documentation has been updated accordingly.
This commit introduces a favorites feature for photos, allowing users to mark and manage their favorite images. The API has been updated with new endpoints for toggling favorite status, checking if a photo is a favorite, and bulk adding/removing favorites. The frontend has been enhanced to include favorite management in the PhotoViewer and Search components, with UI elements for adding/removing favorites and displaying favorite status. Documentation has been updated to reflect these changes.
This commit enhances the PhotoViewer component by introducing zoom and pan capabilities, allowing users to adjust the view of photos interactively. Additionally, a slideshow feature has been implemented, enabling automatic photo transitions with adjustable intervals. The user interface has been updated to include controls for zooming and starting/stopping the slideshow, improving the overall photo browsing experience. Documentation has been updated to reflect these changes.
This commit introduces a new PhotoViewer component that allows users to view photos in a full-screen mode with navigation controls. The component supports preloading adjacent images for smoother transitions and includes keyboard navigation for improved accessibility. Additionally, the Search page has been updated to integrate the PhotoViewer, enabling users to load and display all photos seamlessly. Documentation has been updated to reflect these changes.
This commit introduces several enhancements to the photo identification and tagging functionalities. The Identify component now supports filtering by photo IDs, allowing users to view faces from specific photos. Additionally, the Tags component has been updated to include an unidentified face count for each photo, improving user awareness of untagged faces. The API has been modified to accommodate these new parameters, ensuring seamless integration with the frontend. Documentation has been updated to reflect these changes.
This commit introduces a new Help page to the PunimTag application, providing users with detailed guidance on various features and workflows. The navigation has been updated to include the Help page, improving accessibility to support resources. Additionally, the user guide has been refined to remove outdated workflow examples, ensuring clarity and relevance. The Dashboard page has also been streamlined for a cleaner interface. Documentation has been updated to reflect these changes.
This commit introduces a new user guide in the documentation, providing detailed instructions on using the PunimTag web application. The guide includes sections on getting started, navigation overview, page-by-page usage, workflow examples, and tips for best practices. This addition aims to enhance user experience by offering clear guidance on application features and functionalities.
This commit updates the TagSelectedPhotosDialog to allow both single and bulk tags to be managed more effectively. The logic for determining removable tags has been refined, ensuring that users can see which tags are common across selected photos and whether they can be removed. Additionally, the photo date extraction method in PhotoManager has been improved to include a fallback to file modification time, enhancing reliability. The photo service now also utilizes this updated method for date extraction, ensuring consistency across the application. Documentation has been updated to reflect these changes.
This commit introduces a new Faces Maintenance page in the frontend, allowing users to view, sort, and delete face items based on quality and person information. The API has been updated to include endpoints for retrieving and deleting faces, enhancing the management capabilities of the application. Additionally, new data models and schemas for maintenance face items have been added to support these features. Documentation has been updated to reflect these changes.
This commit introduces new search options for processed and unprocessed photos in the Search component, enhancing the photo management capabilities. The Identify component has been updated to clear sessionStorage settings on logout and authentication failure, improving user experience by ensuring a clean state. Additionally, the API has been modified to support these new search parameters, ensuring seamless integration with the frontend. Documentation has been updated to reflect these changes.
This commit introduces a new date processed filter in the Identify component, allowing users to filter faces based on the date they were processed. The API has been updated to support this new parameter, ensuring seamless integration with the frontend. Additionally, the date filters for date taken have been renamed for clarity. Documentation has been updated to reflect these changes.
This commit updates the AutoMatch component to include a new criterion for auto-matching faces based on picture quality, requiring a minimum quality score of 50%. The Identify component has been modified to persist user settings in localStorage, improving user experience by retaining preferences across sessions. Additionally, the Modify component introduces functionality for selecting and unmatching faces in bulk, enhancing the management of face items. Documentation has been updated to reflect these changes.
This commit introduces new features for tag filtering in the Identify and AutoMatch components. Users can now filter unidentified faces by tags, with options to match all or any specified tags. The UI has been updated to include tag selection and management, enhancing user experience. Additionally, developer mode options have been added to display tolerance and auto-accept threshold settings conditionally. The API has been updated to support these new parameters, ensuring seamless integration. Documentation has been updated to reflect these changes.
This commit enhances the user interface of the Process, Scan, Search, and Tags components. The input fields for batch size and button styles have been adjusted for better usability and consistency. The Search component now includes improved logic for handling removable tags, ensuring only single tags can be deleted. Additionally, a new dialog for tagging selected photos has been introduced, allowing users to manage tags more effectively. Documentation has been updated to reflect these changes.
This commit introduces a new API endpoint for browsing folders, utilizing tkinter for a native folder picker dialog. The Scan component has been updated to integrate this functionality, allowing users to select folders more easily. If the native picker is unavailable, a browser-based fallback is implemented, ensuring a seamless user experience. Additionally, the input field for batch size has been modified to restrict input to numeric values only, improving data validation. Documentation has been updated to reflect these changes.
This commit deletes the Alembic migration files and configuration, including the alembic.ini file, env.py, and various migration scripts. This cleanup is part of the transition to a new database management approach, ensuring that outdated migration artifacts do not interfere with future development. The requirements.txt file has also been updated to remove the Alembic dependency. No functional changes to the application are introduced in this commit.
This commit enhances the Layout component by fixing the sidebar position for better usability and adjusting the main content layout accordingly. The Search component has been updated to improve tag selection and management, including the addition of new state variables for handling selected tags and loading photo tags. A confirmation dialog for tag deletion has been introduced, along with improved error handling and user feedback. The overall user interface has been refined for a more cohesive experience. Documentation has been updated to reflect these changes.
This commit refines the Modify and Tags components by implementing better state management for person selection and tag handling. In the Modify component, the logic for checking if a selected person still exists has been optimized to prevent unnecessary state updates. The Tags component has been updated to support immediate saving of tags and includes confirmation dialogs for tag removals, enhancing user experience. Additionally, error handling for tag creation and deletion has been improved, ensuring a more robust interaction with the API. Documentation has been updated to reflect these changes.
This commit improves the Identify component by adding a loading progress bar to provide user feedback during face loading and similarity calculations. The date filters have been updated for consistency, simplifying the date selection process. Additionally, the API has been adjusted to support the new date parameters, ensuring a seamless user experience. The CSS has been modified to style the scrollbar for the similar faces container, enhancing the overall UI. Documentation has been updated to reflect these changes.
This commit introduces new date filters for the face identification process, allowing users to filter faces based on the date taken and date processed. The API has been updated to support these new parameters, ensuring backward compatibility with legacy date filters. Additionally, the Identify component has been modified to incorporate these new filters in the user interface, enhancing the overall functionality and user experience. Documentation has been updated to reflect these changes.
This commit introduces a new batch similarity API endpoint to efficiently calculate similarities between multiple faces in a single request. The frontend has been updated to utilize this endpoint, enhancing the Identify component by replacing individual similarity checks with a batch processing approach. Progress indicators have been added to provide user feedback during similarity calculations, improving the overall user experience. Additionally, new data models for batch similarity requests and responses have been defined, ensuring a structured and efficient data flow. Documentation has been updated to reflect these changes.
This commit introduces a new column for storing facial landmarks in the database schema, enhancing the face processing capabilities. The FaceProcessor class has been updated to extract and serialize landmarks during face detection, improving pose classification accuracy. Additionally, the Identify and AutoMatch components have been modified to support loading progress indicators and provide user feedback during face loading operations. Documentation has been updated to reflect these changes, ensuring a better user experience and improved functionality.
This commit adds a new command-line interface (CLI) and graphical user interface (GUI) components for the PunimTag desktop application. The `photo_tagger.py` script serves as the CLI entry point, enabling users to scan, process, and manage photos with facial recognition capabilities. The GUI includes a unified dashboard with various panels for identifying, modifying, and managing tags for photos. Additionally, comprehensive documentation has been created to guide users through installation and usage, ensuring a smooth experience. This update enhances the overall functionality and accessibility of the PunimTag application.
This commit introduces a comprehensive analysis of pose modes and face width detection to enhance profile classification accuracy. New scripts have been added to analyze pose data in the database, check identified faces for pose information, and validate yaw angles. The PoseDetector class has been updated to calculate face width from landmarks, which serves as an additional indicator for profile detection. The frontend and API have been modified to include pose mode in responses, ensuring better integration with existing functionalities. Documentation has been updated to reflect these changes, improving user experience and accuracy in face processing.
This commit enhances the photo processing workflow in the FaceService by ensuring that cancellation checks occur after completing the current photo's processing, including pose detection and database commits. It introduces robust error handling during progress updates, allowing for graceful cancellation and improved user feedback. Documentation has been updated to reflect these changes, enhancing the overall user experience and reliability of the photo processing feature.
This commit introduces a comprehensive auto-match automation plan that automates the face matching process in the application. Key features include the ability to automatically identify faces based on pose and similarity thresholds, with configurable options for auto-acceptance. The API has been updated to support new parameters for auto-acceptance and pose filtering, while the frontend has been enhanced to allow users to set an auto-accept threshold and view results. Documentation has been updated to reflect these changes, improving user experience and functionality.
This commit enhances the AutoMatch component by implementing an auto-start feature for the auto-match process when the component mounts or when the tolerance value changes. Additionally, it improves the user interface by allowing users to click on face images to open the full photo in a new tab, enhancing the overall user experience. Documentation has been updated to reflect these changes.
This commit introduces a comprehensive face pose detection system utilizing the RetinaFace library to automatically classify face poses (yaw, pitch, roll) during image processing. The database schema has been updated to store pose information, including pose mode and angles. The face processing pipeline has been modified to integrate pose detection with graceful fallback mechanisms, ensuring compatibility with existing functionality. Additionally, new utility functions for pose detection have been added, along with unit tests to validate the implementation. Documentation has been updated to reflect these changes, enhancing the overall user experience and accuracy in face matching.
This commit introduces new navigation buttons in the AutoMatch component, allowing users to easily move between persons being matched. Additionally, the Identify component has been updated to include a collapsible filters section, improving the user interface for managing face identification. The unique faces filter is now enabled by default, enhancing the identification process. Documentation and tests have been updated to reflect these changes, ensuring a reliable user experience.
This commit introduces several new features for tag management, including the ability to retrieve tags for specific photos, update tag names, and delete tags through new API endpoints. The frontend has been updated to support these functionalities, allowing users to manage tags more effectively with a user-friendly interface. Additionally, new components for managing photo tags and bulk tagging have been added, improving overall usability. Documentation and tests have been updated to reflect these changes, ensuring reliability and user satisfaction.
This commit introduces the Modify Identified workflow, allowing users to edit person information, view associated faces, and unmatch faces from identified people. The API has been updated with new endpoints for unmatching faces and retrieving faces for specific persons. The frontend includes a new Modify page with a user-friendly interface for managing identified persons, including search and edit functionalities. Documentation and tests have been updated to reflect these changes, ensuring reliability and usability.
This commit introduces a new feature that allows users to open the folder containing a selected photo in their system's file manager. The API has been updated with a new endpoint to handle folder opening requests, supporting various operating systems. The frontend has been enhanced to include a button for this action, providing user feedback and error handling. Documentation and tests have been updated to reflect these changes, ensuring reliability and usability.
This commit introduces a comprehensive photo search feature in the application, allowing users to search photos by various criteria including name, date, and tags. The API has been updated to support these search parameters, returning results that match the specified filters. Additionally, new endpoints for managing tags have been added, enabling users to add and remove tags from multiple photos. The frontend has been enhanced with a user-friendly interface for search inputs and results display, improving overall usability. Documentation and tests have been updated to reflect these new features and ensure reliability.
This commit introduces a new feature in the Identify component that allows users to filter for unique faces only, hiding duplicates with ≥60% match confidence. The API has been updated to log calls to the get_similar_faces endpoint, including warnings for non-existent faces and information on the number of results returned. Additionally, the SimilarFaceItem schema has been updated to include the filename, improving data handling and user experience. Documentation and tests have been updated accordingly.
This commit enhances the README with detailed instructions on the automatic database initialization and schema compatibility between the web and desktop versions. It also introduces new API endpoints for managing unidentified faces and people, including listing, creating, and identifying faces. The schemas for these operations have been updated to reflect the new data structures. Additionally, tests have been added to ensure the functionality of the new API features, improving overall coverage and reliability.
This commit introduces a new Alembic migration to add a 'processed' column to the 'photos' table, enhancing the database schema to track photo processing status. Additionally, it includes new utility scripts for dropping and recreating all tables in the web database, as well as a script to display all tables and their structures. These changes improve database management and facilitate a fresh start for the web application, ensuring alignment with the updated schema.
This commit introduces the DeepFace integration for face processing, allowing users to configure detector backends and models through the new Process tab in the GUI. Key features include batch processing, job cancellation support, and real-time progress tracking. The README has been updated to reflect these enhancements, including instructions for automatic model downloads and handling of processing-intensive tasks. Additionally, the API has been expanded to support job management for face processing tasks, ensuring a robust user experience.
This commit enhances the README with detailed instructions for installing and starting Redis, including commands for various operating systems. It clarifies the automatic startup of the RQ worker with the FastAPI server and updates the project status for Phase 2 features. Additionally, a new script `run_api_with_worker.sh` is introduced to streamline the process of starting the FastAPI server alongside the RQ worker, ensuring a smoother setup for users. The worker now has a unique name to prevent conflicts during execution.
This commit introduces a new confidence calibration system that converts DeepFace distance values into actual match probabilities, addressing previous misleading confidence percentages. Key changes include the addition of calibration methods in `FaceProcessor`, updates to the `IdentifyPanel` and `AutoMatchPanel` to utilize calibrated confidence, and new configuration settings in `config.py`. The README has been updated to document these enhancements, ensuring users see more realistic match probabilities throughout the application.
This commit modifies the `AutoMatchPanel` class to enable search entry and buttons when the auto-match process starts. The search controls are disabled when there is only one matched person, and the help label text is updated accordingly. Additionally, the search controls are disabled when clearing the search, improving user experience by providing clear feedback on search functionality status.
This commit introduces a new method `_calculate_face_canvas_size` in the `IdentifyPanel` class to calculate a responsive size for the face canvas based on the available window space. Additionally, the `_update_face_canvas_size` method has been implemented to dynamically adjust the canvas size during window resize events. The dashboard GUI has also been updated to improve layout consistency by fixing the width of the folder input text box. These changes enhance the user experience by ensuring that the face canvas adapts to different screen sizes and resolutions.
This commit modifies the `process_faces` method in both the `PhotoTagger` and `FaceProcessor` classes to accept an optional `limit` parameter. If `None`, all unprocessed photos will be processed, enhancing flexibility in face processing. Additionally, the `get_unprocessed_photos` method in `DatabaseManager` is updated to handle the optional limit, ensuring consistent behavior across the application. Docstrings have been updated to reflect these changes, improving code documentation and clarity.
This commit introduces a comprehensive EXIF orientation handling system to improve face processing accuracy. Key changes include the addition of an `exif_orientation` field in the database schema, updates to the `FaceProcessor` class for applying orientation corrections before face detection, and the implementation of a new `EXIFOrientationHandler` utility for managing image orientation. The README has been updated to document these enhancements, including recent fixes for face orientation issues and improved face extraction logic. Additionally, tests for EXIF orientation handling have been added to ensure functionality and reliability.
This commit refactors the handling of face location data to exclusively use the DeepFace format ({x, y, w, h}) instead of the legacy tuple format (top, right, bottom, left). Key changes include updating method signatures, modifying internal logic for face quality score calculations, and ensuring compatibility in the GUI components. Additionally, configuration settings for face detection have been adjusted to allow for smaller face sizes and lower confidence thresholds, enhancing the system's ability to detect faces in various conditions. All relevant tests have been updated to reflect these changes, ensuring continued functionality and performance.
This commit introduces significant enhancements to the face detection system, addressing false positives by updating configuration settings and validation logic. Key changes include stricter confidence thresholds, increased minimum face size, and improved aspect ratio requirements. A new script for cleaning up existing false positives from the database has also been added, successfully removing 199 false positive faces. Documentation has been updated to reflect these changes and provide usage instructions for the cleanup process.
This commit adds final notes to the migration documentation and quickstart files, confirming readiness for DeepFace implementation across all phases. The updates include completion confirmations in `DEEPFACE_MIGRATION_COMPLETE.md`, `PHASE1_COMPLETE.md`, `PHASE2_COMPLETE.md`, and `PHASE3_COMPLETE.md`, as well as quickstart notes in `.notes/phase1_quickstart.md` and `.notes/phase2_quickstart.md`. These changes ensure clarity on the project's progress and readiness for the next steps in the DeepFace integration.
