flats-raster-vector-converter

A Python tool for transforming bitmap images into optimized SVG paths, suitable for various NC machines, including CNC milling and laser cutters. Key features:

• Versatile Application: Ideal for CNC milling G-code generation and adaptable for use with laser cutters and other NC machines.
• Advanced Image Processing: Implements image skeletonization and other techniques for precise vector conversion.
• Graph Theory Optimization: Utilizes graph theory for efficient path planning.
• TSP Solver Integration: Incorporates OR-Tools' TSP solver for optimal routing.

Designed for professionals and DIY enthusiasts seeking efficient machining and creative applications.

Installation and Dependencies

To use the flats-raster-vector-converter, ensure you have Python installed on your system. This tool has been tested on Python 3.11.6. Follow these steps:

1. Clone the repository:

git clone https://github.com/KasHir/flats-raster-vector-converter

2. Navigate to the project directory:

cd flats-raster-vector-converter

3. Install the required third-party libraries. While requirements.txt is not yet available, you can manually install the necessary libraries using pip or conda. Here are the commands to install each library with pip:

pip install opencv-python-headless matplotlib networkx numpy scikit-image svgwrite

If you prefer to use conda, you can use the following commands:

conda install -c conda-forge opencv matplotlib networkx numpy scikit-image svgwrite

Note: The library sknw may need to be updated manually for the best results. If you encounter issues with skeletonized graphs, download the latest version of sknw and include it in the ./external/sknw directory of this repository.

4. Ensure you have the OR-Tools library installed, which may require a separate installation step:

With pip:

pip install ortools

Or, if you're using conda, refer to the OR-Tools documentation for the specific installation command, as it may vary depending on your operating system and conda configuration.

A requirements.txt file will be provided in the future to simplify this process.

Example Use

Input

• File Format: PNG (raster image)
• Example Command: python converter.py input.png output.svg

The ideal input is a line-art style raster image, which can be prepared using image processing tools such as the ControlNet processor with Canny edge detection or line-art conversions.

Output

• File Format: SVG (vector image)
• Details: The output SVG file will contain the optimized vector paths suitable for CNC milling and other NC machines.

Limitations and Known Issues

• Currently supports only PNG format for input. Future updates aim to include more formats.
• Performance may vary with very large images or complex patterns.
• requirements.txt will be prepared in the future.
• [List any other known issues or limitations here]

Acknowledgments

Special thanks to the creators of the example images used in this project. These images are instrumental for demonstrating the capabilities of the flats-raster-vector-converter:

• img_line/sample.png: [https://elshaddai.jp/freedeta.html]
• img_line/zunda.png : [https://seiga.nicovideo.jp/seiga/im10788496]

Contact

For more information, feedback, or questions, feel free to reach out:

• Website: f/ats
• X (Twitter): @flatsCircle
• X (Twitter): @fish_meat

We welcome your input and contributions to this project!

License

This project is licensed under the MIT License - see the LICENSE file for details. The MIT License is a permissive license that is short and to the point. It lets people do anything they want with your code as long as they provide attribution back to you and don’t hold you liable.