A Python application for 2D image stitching and stage movement registration using the arkitekt-next framework and ashlarUC2. This repository includes a Dockerized setup for running the application seamlessly.
- Image stitching with Ashlar UC2
- Stage movement simulation
- Integration with
arkitekt-nextfor server-based workflows - Docker support for easy deployment
- Docker (for containerized deployment)
- Python 3.10+ (for local development)
- Dependencies listed in
requirements.txt
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Clone the repository:
git clone https://github.com/your-username/ashlar-stitcher.git cd ashlar-stitcher -
Build the Docker image:
docker build -t ashlar-stitcher . -
Run the container:
docker run -p 8000:8000 ashlar-stitcher
-
Clone the repository:
git clone https://github.com/your-username/ashlar-stitcher.git cd ashlar-stitcher -
Create a virtual environment:
python -m venv venv source venv/bin/activate # On Windows, use venv\Scripts\activate
-
Install dependencies:
pip install -r requirements.txt
-
Run the script:
python test_ashlar_numpy.py
The stitch2D function simulates stitching tiles of images with provided position lists and parameters:
pixel_size: Size of a pixel in microns.position_list: List of x-y positions for the tiles.arrays: Image arrays in[tiles, colour, channels, height, width]format.
The move_stage function logs axis movements:
axis: The axis to move (default is"X").position: The position to move to.
The script registers these functions with an arkitekt-next server for remote interaction. Ensure the server URL is correctly set in the easy context manager.
ashlar-stitcher/
├── Dockerfile # Docker setup
├── requirements.txt # Python dependencies
├── test_ashlar_numpy.py # Main script
├── README.md # Documentation
Contributions are welcome! Please follow these steps:
- Fork the repository.
- Create a feature branch.
- Commit changes and push to your fork.
- Open a pull request.
This project is licensed under the MIT License. See LICENSE for details.