❗This is an unofficial project and is not created, maintained, or in any sense linked to valetudo.cloud
A Python library that converts Valetudo vacuum JSON map data into PIL (Python Imaging Library) images. This package is primarily developed for and used in the MQTT Vacuum Camera project.
- Processes map data from Valetudo-compatible robot vacuums
- Supports both Hypfer and Rand256 vacuum data formats
- Renders comprehensive map visualizations including:
- Walls and obstacles
- Robot position and cleaning path
- Room segments and boundaries
- Cleaning zones
- Virtual restrictions
- LiDAR data
- Provides auto-cropping and dynamic zooming
- Supports image rotation and aspect ratio management
- Enables custom color schemes
- Handles multilingual labels
- Implements thread-safe data sharing
pip install valetudo_map_parser- Python 3.12 or higher
- Dependencies:
- Pillow (PIL) for image processing
- NumPy for array operations
The library is configured using a dictionary format. See our sample code for implementation examples.
Key functionalities:
- Decodes raw data from Rand256 format
- Processes JSON data from compatible vacuums
- Returns Pillow PNG images
- Provides calibration and room property extraction
- Supports asynchronous operations
Current version: 0.1.9.b41
- Full functionality available in versions >= 0.1.9
- Actively maintained and enhanced
- Uses Poetry for dependency management
- Implements comprehensive testing
- Enforces code quality through ruff, isort, and pylint
Contributions are welcome! You can help by:
- Submitting code improvements
- Enhancing documentation
- Reporting issues
- Suggesting new features
This project is provided "as is" without warranty of any kind. Users assume all risks associated with its use.
Apache-2.0
For more information about Valetudo, visit valetudo.cloud Integration with Home Assistant: MQTT Vacuum Camera