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Cursor Auto Accept - MVP Integration Scope

Overview

Integration plan for the improved calibration and button detection system into the main clickbot application.

Core Components

1. UI Components

  • Calibration Section

    • Calibrate button
    • Debug Matches button (runs analyze_hover_results.py)
    • Last calibration timestamp
    • Status indicators per button type

  • Monitoring Section

    • Start/Stop button
    • Live status display
    • Match confidence display
    • Current click rate
    • Active monitor indicator

  • Debug Section

    • View Latest Matches button
    • Match history log
    • Error rate tracking
    • Button match statistics

2. Core Features

  • Button Group Detection

    • X-axis position grouping (±20px)
    • Confidence + Y-axis position prioritization
    • Match history tracking

  • Enhanced Calibration

    • Pre/post click image capture
    • Calibration coordinate storage
    • Match validation against calibration data

  • Debug Visualization

    • Real-time match visualization
    • Color-coded button states (Green/Yellow/Red)
    • Confidence score overlay

3. File Structure

cursor-auto-accept/
├── src/
│   ├── ui/
│   │   ├── main_window.py      # Main UI
│   │   ├── calibration_tab.py  # Calibration UI
│   │   └── debug_tab.py        # Debug UI
│   ├── core/
│   │   ├── button_detector.py  # New detection logic
│   │   ├── calibrator.py       # New calibration logic
│   │   └── visualizer.py       # Debug visualization
│   └── utils/
│       ├── config.py           # Configuration
│       └── logging.py          # Enhanced logging
├── assets/
│   └── monitor_0/             # Calibration data
├── debug/                     # Debug output
└── logs/                     # Application logs

4. Configuration System

class ClickBotConfig:
    # Detection Settings
    MATCH_CONFIDENCE_THRESHOLD = 0.9
    X_AXIS_GROUP_THRESHOLD = 20
    MIN_Y_POSITION_DELTA = 5

    # Visualization Settings
    BUTTON_COLORS = {
        'accept': (0, 255, 0),    # Green
        'suggest': (0, 255, 255), # Yellow
        'cancel': (0, 0, 255)     # Red
    }

    # Debug Settings
    SAVE_DEBUG_IMAGES = True
    MAX_DEBUG_HISTORY = 100
    VISUALIZATION_UPDATE_RATE = 1.0  # seconds

Implementation Phases

Phase 1: Core Integration

  1. Port improved button detection algorithm
  2. Implement match grouping logic
  3. Add match validation system
  4. Set up configuration system

Phase 2: UI Development

  1. Create new calibration workflow
  2. Add debug visualization panel
  3. Implement match statistics display
  4. Add real-time status updates

Phase 3: Testing & Validation

  1. Unit tests for new components
  2. Integration tests for full workflow
  3. Visualization system tests
  4. Performance benchmarking

Phase 4: Documentation & Deployment

  1. Update README with new features
  2. Add debug visualization guide
  3. Document configuration options
  4. Create user guide for new features

Success Criteria

  • Successful button detection rate > 95%
  • False positive rate < 1%
  • Match confidence threshold ≥ 0.9
  • Response time < 200ms
  • Stable operation across multiple monitors

Timeline

  • Phase 1: 1 week
  • Phase 2: 1 week
  • Phase 3: 3 days
  • Phase 4: 2 days

Total estimated time: 2.5 weeks