tanyar09
d300eb1122
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.
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PunimTag - Project Overview
Mission Statement
PunimTag is a desktop photo management application that leverages facial recognition AI to help users organize, tag, and search their photo collections efficiently.
Core Capabilities
- Automated face detection and recognition
- Person identification and management
- Custom tagging system
- Advanced search functionality
- Batch processing
Current Status
- Version: 1.0 (Development)
- Stage: Active Development
- Next Major Feature: DeepFace Migration
Key Technologies
- Python 3.12+
- Tkinter (GUI)
- SQLite (Database)
- face_recognition (Current - to be replaced)
- DeepFace (Planned migration)
Project Goals
- Make photo organization effortless
- Provide accurate face recognition
- Enable powerful search capabilities
- Maintain user privacy (local-only by default)
- Scale to large photo collections (50K+ photos)
Success Metrics
- Face recognition accuracy > 95%
- Process 1000+ photos per hour
- Search response time < 1 second
- Zero data loss
- User-friendly interface
Links
- Architecture:
docs/ARCHITECTURE.md - Main README:
docs/README.md - Demo Guide:
docs/DEMO.md