50 lines
1.7 KiB
Markdown
50 lines
1.7 KiB
Markdown
# Active Context
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## Current Status
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- Screen capture module implemented
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- Pattern recognition-based board detection implemented
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- Coordinate-based detection retained as fallback
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- SwiftUI interface for capture controls added
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- Proper resource cleanup implemented
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- Error handling system in place
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## Recent Changes
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- Refined pattern recognition approach for chess board detection:
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1. Modified rectangle detection parameters:
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- Using 0.3-0.5 aspect ratio for taller rectangles
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- Increased minimum size to 0.4
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- Single observation for precision
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2. Improved board extraction:
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- Using detected width as reference
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- Positioning square board at top of detected area
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- Using offsetBy for vertical positioning
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3. Simplified coordinate handling:
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- Direct rectangle detection with Vision framework
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- Proper coordinate system transformations
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- Maintained pattern matching for accuracy
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## Current Challenges
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- Board detection still not capturing full height
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- Need to investigate if issue is with:
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1. Detection parameters
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2. Coordinate transformations
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3. View rendering constraints
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4. Window/display configuration
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## Next Steps
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1. Further refine board detection:
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- Test different aspect ratios
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- Validate coordinate transformations
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- Review view constraints
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2. Add board position analysis
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3. Implement move detection
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4. Create visual overlay system
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5. Integrate Stockfish engine
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## Known Issues
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- Board detection showing only bottom portion
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- Need to validate pattern detection accuracy
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- Need to handle multiple display configurations
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- Requires testing with different screen resolutions
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- Need to add proper error recovery
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- Requires additional permission handling for production
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