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 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 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 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 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.
