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.
This commit adds a quality filtering feature to the Identify Panel, allowing users to filter faces based on a quality score (0-100%). The `_get_unidentified_faces()` method has been updated to accept a `min_quality_score` parameter, and the SQL query now includes a WHERE clause for quality filtering. All relevant call sites have been modified to utilize this new feature, improving the user experience during face identification. The unique checkbox default state has also been confirmed to be unchecked, ensuring consistency in the UI behavior.
This commit introduces a quality filtering feature in the Identify Panel, allowing users to filter faces based on a quality score (0-100%). The panel now includes a slider for adjusting the quality threshold and displays the current quality percentage. Additionally, navigation functions have been updated to skip to the next or previous face that meets the quality criteria, improving the user experience during identification. The README has been updated to reflect these new features and enhancements.
This commit introduces several new documents summarizing the completion of Phase 6, which focused on testing and validation of the DeepFace integration. Key deliverables include a detailed testing guide, validation checklist, test results report, and a quick reference guide. All automated tests have passed, confirming the functionality and performance of the integration. The documentation provides insights into the testing process, results, and next steps for manual GUI testing and user acceptance validation, ensuring clarity and thoroughness for future development and deployment.
This commit finalizes the migration from face_recognition to DeepFace across all phases. It includes updates to the database schema, core processing, GUI integration, and comprehensive testing. All features are now powered by DeepFace technology, providing superior accuracy and enhanced metadata handling. The README and documentation have been updated to reflect these changes, ensuring clarity on the new capabilities and production readiness of the PunimTag system. All tests are passing, confirming the successful integration.
This commit introduces several new files to enhance project organization and developer onboarding. The `.cursorignore` and `.cursorrules` files provide guidelines for Cursor AI, while `CONTRIBUTING.md` outlines contribution procedures. Additionally, `IMPORT_FIX_SUMMARY.md`, `RESTRUCTURE_SUMMARY.md`, and `STATUS.md` summarize recent changes and project status. The `README.md` has been updated to reflect the new project focus and structure, ensuring clarity for contributors and users. These additions aim to improve maintainability and facilitate collaboration within the PunimTag project.
This commit deletes the `photo_tagger_refactored.py`, `run.sh`, and test files (`test_basic.py`, `test_deepface_gui.py`, `test_face_recognition.py`) that are no longer in use. The removal of these files streamlines the project structure and eliminates legacy code, paving the way for future enhancements and a cleaner codebase. The README has been updated to reflect these changes, ensuring clarity on the current state of the project.
This commit enhances the Dashboard GUI by adding a progress bar and status label to provide real-time feedback during photo processing. The processing button is now disabled during the operation, and the progress updates are simulated to reflect various stages of the process. Additionally, error handling has been improved to reset the progress state in case of failures, ensuring a smoother user experience. The README has been updated to include these new features, emphasizing the improved interactivity and user feedback during processing tasks.
This commit introduces a compact home icon for quick navigation to the welcome screen, improving user experience across all panels. Additionally, all exit buttons now navigate to the home screen instead of closing the application, ensuring a consistent exit behavior. The README has been updated to reflect these enhancements, emphasizing the improved navigation and user experience in the unified dashboard.
This commit introduces the TagManagerPanel class into the Dashboard GUI, providing a fully integrated interface for managing photo tags. Users can now view, add, edit, and delete tags directly within the dashboard, enhancing the overall tagging experience. The panel includes features for bulk operations, responsive layout, and a detailed preview of tag management capabilities. The README has been updated to reflect these new functionalities, emphasizing the improved user experience in managing photo tags and their associations.
This commit introduces the ModifyPanel class into the Dashboard GUI, providing a fully integrated interface for editing identified faces. Users can now view and modify person details, unmatch faces, and perform bulk operations with visual confirmation. The panel includes a responsive layout, search functionality for filtering people by last name, and a calendar interface for date selection. The README has been updated to reflect the new capabilities of the Modify Panel, emphasizing its full functionality and improved user experience in managing photo identifications.
This commit introduces the AutoMatchPanel class into the Dashboard GUI, providing a fully integrated interface for automatic face matching. The new panel allows users to start the auto-match process, configure tolerance settings, and visually confirm matches between identified and unidentified faces. It includes features for bulk selection of matches, smart navigation through matched individuals, and a search filter for large databases. The README has been updated to reflect the new functionality and improvements in the auto-match workflow, enhancing the overall user experience in managing photo identifications.
This commit updates the Dashboard GUI to support automatic full screen mode across platforms, ensuring optimal viewing experiences. It introduces a responsive layout that dynamically adjusts components during window resizing, improving usability. Additionally, typography has been enhanced with larger fonts for better readability. The README has been updated to reflect these new features, emphasizing the unified dashboard's capabilities and user experience improvements.
This commit introduces the IdentifyPanel class into the Dashboard GUI, allowing for a fully integrated face identification interface. The Dashboard now requires a database manager and face processor to create the Identify panel, which includes features for face browsing, identification, and management. Additionally, the DatabaseManager has been updated to support case-insensitive person additions, improving data consistency. The PhotoTagger class has also been modified to accommodate these changes, ensuring seamless interaction between components.
This commit transforms the Dashboard GUI into a unified interface designed for web migration, featuring a single window with a menu bar for easy access to all functionalities. Key enhancements include the addition of a content area for seamless panel switching, improved panel management, and real-time status updates. The README has also been updated to reflect these changes, providing a comprehensive overview of the new dashboard features and system requirements.
This commit updates the SearchGUI class to include a new "Processed" column, displaying the processing status of photos. The results area now features a header with item count, and sorting functionality has been added for the processed status. Additionally, the treeview has been enhanced with a vertical scrollbar for better navigation. The logic for displaying and sorting results has been updated to accommodate these changes, improving the overall user experience in managing photo collections.
This commit improves the README documentation by detailing the new path handling capabilities, including support for both absolute and relative paths, and automatic path normalization. It also introduces a new section on the Dashboard GUI, highlighting features such as visual folder selection, path validation, and cross-platform compatibility. These updates aim to enhance user experience and clarify the functionality of the photo tagging application.
This commit introduces a folder browsing button in the Dashboard GUI, allowing users to select a folder for photo scanning. It also implements path normalization and validation using new utility functions from the path_utils module, ensuring that folder paths are absolute and accessible before scanning. Additionally, the PhotoManager class has been updated to utilize these path utilities, enhancing the robustness of folder scanning operations. This improves user experience by preventing errors related to invalid paths and streamlining folder management across the application.
This commit updates the README to detail new functionalities in the Search GUI, including the ability to search for photos by name, date, tags, and to identify photos without faces or tags. A collapsible filters area has been added, featuring a folder location filter, browse and clear buttons, and tooltips for user guidance. The results display now includes sortable columns and additional interactive features such as a tag help icon and calendar picker, improving the overall user experience and search capabilities.
This commit enhances the SearchGUI class by introducing a folder filter feature, allowing users to filter search results based on a specified folder path. The GUI now includes an input field for folder location, along with 'Browse' and 'Clear' buttons for easier folder selection and management. Additionally, the search logic has been updated to apply the folder filter across various search types, improving the overall search experience and result accuracy. Tooltip functionality has also been added for better user guidance on available tags and filter options.
This commit enhances the SearchGUI and SearchStats classes by introducing the ability to search for photos within a specified date range. The SearchGUI now includes input fields for users to enter 'From' and 'To' dates, along with calendar buttons for easier date selection. The SearchStats class has been updated to execute database queries that retrieve photos based on the provided date criteria, returning results that include the date taken. This addition improves the overall search capabilities and user experience in managing photo collections.
This commit introduces functionality to search for and display photos that lack associated tags in the SearchGUI and SearchStats classes. The SearchGUI has been updated to manage the visibility of relevant columns based on the selected search type, ensuring a seamless user experience. Additionally, the SearchStats class now retrieves photos without tags from the database, improving the overall search capabilities of the application.
This commit enhances the SearchGUI and SearchStats classes by adding functionality to search for and display photos that do not have detected faces. The SearchGUI now includes logic to handle the visibility of relevant columns based on the selected search type, ensuring a streamlined user experience. Additionally, the SearchStats class has been updated to retrieve photos without faces from the database, improving the overall search capabilities of the application.
This commit updates the DatabaseManager to support case-insensitive tag lookups and additions, ensuring consistent tag handling. The SearchGUI and TagManagerGUI have been modified to reflect these changes, allowing for improved user experience when managing tags. Additionally, the search logic in SearchStats and TagManagement has been adjusted for case-insensitive tag ID retrieval, enhancing overall functionality and reliability in tag management across the application.
This commit updates the SearchGUI class to include a new feature for searching photos by tags, allowing users to input multiple tags and choose match modes (ANY or ALL). The results now display associated tags for each photo, and the GUI has been adjusted to accommodate these changes, including sorting capabilities for the tags column. Additionally, the search logic in the SearchStats class has been implemented to retrieve photos based on the specified tags, enhancing the overall search experience.
This commit enhances the IdentifyGUI class by updating the face identification process to handle similar faces more effectively. The logic for updating the current face index has been streamlined, allowing for better flow when identifying faces. Additionally, new methods have been introduced to manage selected similar faces, ensuring that all identified faces are properly marked and displayed. The form clearing functionality has also been updated to include similar face selections, improving user experience during the identification process.
This commit updates the README to reflect significant enhancements in the Search GUI, including new functionalities for photo selection, tagging, and sorting. Users can now view and manage tags through a dedicated popup, select multiple photos for bulk tagging, and utilize sortable columns for better navigation. The workflow for searching and managing photos has been clarified, providing a comprehensive guide for users to efficiently utilize the updated features.
This commit updates the SearchGUI class to include a checkbox for selecting photos, allowing users to tag multiple photos at once. New buttons for tagging selected photos and clearing selections have been added, improving the user experience in managing photo tags. Additionally, the GUI now displays tags associated with each photo, enhancing the functionality of the search interface. The PhotoTagger class is updated to accommodate these changes, streamlining the tagging process.
This commit enhances the SearchGUI class by introducing sorting capabilities for search results. Users can now sort results by 'Person' and 'Photo path' columns, with visual indicators for sort direction. The sorting state is maintained, allowing for toggling between ascending and descending orders. Additionally, the default sorting is set to 'Person' when results are first loaded, improving the overall user experience in navigating search results.
This commit introduces the DashboardGUI class, providing a user-friendly interface for launching core features of the PunimTag application. The dashboard includes placeholder buttons for scanning, processing, and identifying faces, along with options for folder input and batch processing. The PhotoTagger class is updated to integrate the new dashboard functionality, and the README is revised to include usage instructions for the new dashboard command. This enhancement aims to streamline user interactions and improve overall accessibility to key features.
This commit introduces the SearchGUI class, allowing users to search for photos by name through a user-friendly interface. The new functionality includes options to view search results, open photo locations, and display relevant information about matched individuals. The PhotoTagger class is updated to integrate this feature, and the README is revised to include usage instructions for the new search-gui command. Additionally, the search_faces method in SearchStats is enhanced to return detailed results, improving the overall search experience.
This commit adds a new column, linkage_type, to the phototaglinkage table to distinguish between single and bulk tag additions. Additionally, the previous migration attempts to add date_taken and date_added columns to the photos table have been removed, streamlining the database initialization process. These changes improve the database structure for better tag management.
