A Python GUI application for automating pixel art creation on wplace.live canvases. The bot analyzes canvas regions, detects available colors, and automatically paints pixels to match your target image.

This tool is intended for personal use and experimentation on wplace.live. Use responsibly and respect the platform's rules and guidelines. Any use of this tool is at your own risk.

Ban Status: 0 reports

Requirements: wplace.live, Blue Marble setup, and template image went through blue marble color converting.

1. Download the latest release from Releases
2. Extract the files (should include app.exe and colors.json)
3. Run app.exe
4. Allow through Windows Defender/antivirus if prompted
5. Follow the in-app instructions

Requirements: Python 3.8+

1. Clone the repository:

   git clone https://github.com/ciguliaz/wplace_bot.git
   cd wplace_bot

2. Install dependencies:

   pip install -r requirements.txt

3. Run the application:

   python app.py

• Smart Color Detection - Automatically detects available colors from palette
• Visual Region Selection - Drag-to-select canvas and palette areas
• Customizable Settings - Adjustable tolerance, delays, and pixel limits
• Precision Painting - Finds and paints only pixels that need changes
• Real-time Monitoring - Progress tracking and debug visualization
• Persistent Settings - Saves your preferences and region selections
• Centralized Logging - File and console logging with GUI feedback
• Modular Architecture - Clean separation of GUI, core logic, and workers

• Click "Select Canvas" → Drag to select the drawing area
• Click "Select Palette" → Drag to select the color palette
• Adjust color tolerance and click delay settings
• Click "Analyze Canvas & Palette"

• Enable/disable colors you want to use
• Mark premium colors as "bought" if you own them
• Use quick buttons: "Enable All", "Free Colors", etc.

• Set pixel limit (stops after painting X pixels)
• Click "Start Painting" to begin automation
• Monitor progress in real-time
• Click "Stop" to halt immediately

• View analysis results and debug images
• Check detected pixel sizes and color mappings

1. Analysis: Screenshots your selected regions and detects canvas patterns
2. Planning: Compares current state with target to find pixels needing changes
3. Execution: Systematically paints required pixels with appropriate colors
4. Monitoring: Real-time feedback with respect for user-defined limits

Settings auto-save to user_settings.json:

• Regions: Canvas and palette coordinates
• Preferences: Tolerance, delays, pixel limits
• Colors: Enabled status and premium ownership

• Pixel Limits: Prevents runaway painting
• Emergency Stop: Manual halt button
• Tolerance Control: Avoids unnecessary repainting
• Speed Control: Configurable delays for stealth

1. Fork this repository
2. Clone your fork:

   git clone https://github.com/yourusername/wplace_bot.git

3. Create feature branch:

   git checkout -b feature/amazing-feature

4. Install dependencies:

   pip install -r requirements.txt

wplace_bot/
├── app.py                   # Main GUI application entry point
├── main.py                  # Terminal interface for command-line usage
├── core/                    # Core business logic and workers
│   ├── __init__.py          # Core module exports
│   ├── data_manager.py      # Settings and data persistence
│   ├── analysis_worker.py   # Canvas analysis in separate thread
│   ├── bot_worker.py        # Painting automation in separate thread
│   ├── logger.py            # Centralized logging system
│   ├── screen_capture.py    # Screenshot functionality
│   ├── image_analysis.py    # Computer vision and pixel detection
│   ├── color_detection.py   # Palette color detection
│   ├── automation.py        # Mouse click automation
│   └── pixel_mapping.py     # Pixel mapping and painting logic
└── gui/                     # User interface components
    ├── __init__.py          # GUI module exports
    ├── region_selector.py   # Interactive screen region selection
    └── tabs/                # Individual tab implementations
        ├── __init__.py      # Tab module exports
        ├── setup_tab.py     # Canvas/palette setup and analysis
        ├── colors_tab.py    # Color enable/disable controls
        ├── control_tab.py   # Bot control and logging
        └── preview_tab.py   # Analysis results and debug info

• Clean Code: Descriptive names, docstrings, single responsibility
• Separation: UI logic separate from business logic
• Error Handling: User-friendly error messages
• Testing: Thoroughly test before submitting

1. Test thoroughly
2. Document changes
3. Commit clearly: git commit -m "Add: feature description"
4. Push: git push origin feature/amazing-feature
5. PR: Create Pull Request with detailed description

• GitHub Issues with clear reproduction steps
• Screenshots for UI problems
• System info (OS, Python version)
• Check existing issues first

• DataManager: Handles settings persistence, color palette loading, and analysis data storage
• AnalysisWorker: Performs canvas analysis in background thread to avoid GUI blocking
• BotWorker: Executes painting automation in background thread with progress reporting
• Logger: Centralized logging with file output, console output, and GUI callback support

• Screen Capture: Uses pyautogui for cross-platform screenshot functionality
• Pixel Detection: OpenCV-based computer vision for detecting canvas grid patterns
• Color Matching: Tolerance-based color comparison for robust palette detection
• Pixel Mapping: Builds comprehensive map of canvas pixels and their current colors

• Modular Tabs: Each tab is a separate class for maintainability
• Message Queue: Thread-safe communication between workers and GUI
• Event-Driven: Responsive UI with proper cleanup and resource management

• Multiple Outputs: Console, file, and GUI logging simultaneously
• Log Levels: DEBUG, INFO, WARNING, ERROR, CRITICAL with appropriate filtering
• Structured Events: Specific logging methods for different application events
• File Rotation: Daily log files with timestamps for debugging

This project is licensed under the MIT License - see the LICENSE file for details.

If you find this tool useful, consider supporting its development:

Other ways to support:

• Star this repository
• Report bugs and issues
• Suggest new features
• Share with others who might find it useful
• Contribute code improvements

Every bit of support helps maintain and improve this project!