ImSwtitch

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.

Features

• Image stitching with Ashlar UC2
• Stage movement simulation
• Integration with arkitekt-next for server-based workflows
• Docker support for easy deployment

Requirements

• Docker (for containerized deployment)
• Python 3.10+ (for local development)
• Dependencies listed in requirements.txt

Installation

Using Docker

1. Clone the repository:

   git clone https://github.com/your-username/ashlar-stitcher.git
   cd ashlar-stitcher

2. Build the Docker image:

   docker build -t ashlar-stitcher .

3. Run the container:

   docker run -p 8000:8000 ashlar-stitcher

Local Development

1. Clone the repository:

   git clone https://github.com/your-username/ashlar-stitcher.git
   cd ashlar-stitcher

2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows, use venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

4. Run the script:

   python test_ashlar_numpy.py

Usage

Image Stitching

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.

Stage Movement

The move_stage function logs axis movements:

• axis: The axis to move (default is "X").
• position: The position to move to.

Server Interaction

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.

File Structure

ashlar-stitcher/
├── Dockerfile          # Docker setup
├── requirements.txt    # Python dependencies
├── test_ashlar_numpy.py # Main script
├── README.md           # Documentation

Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository.
2. Create a feature branch.
3. Commit changes and push to your fork.
4. Open a pull request.

License

This project is licensed under the MIT License. See LICENSE for details.