dkomura/deeptexture repository overview

⁠Introduction

The Deep Texture Histology Docker image provides a convenient way to use the deeptexture library, a Python package for histological image analysis, without the need to install dependencies or configure your system. The deeptexture library is accessible on GitHub at https://github.com/dakomura/deep_texture_histology⁠, and the complete documentation is available at https://deep-texture-histology.readthedocs.io/en/latest/⁠.

⁠System Requirements

The docker image is available for various platforms. Please select the appropriate tag based on your operating system:

• For Linux: linux_latest
• For macOS (Intel-based): linux_latest
• For macOS (Apple Silicon/ARM64): mac_arm64-latest
• For Windows: win_64-latest

⁠Running the Docker Image:

To run the Docker image, first ensure that you have Docker installed on your system. Then, use the following command, replacing <your_tag> with the appropriate tag for your operating system:

docker run -p 8888:8888 --rm dakomura/deep_texture_histology:<your_tag>

For example, if you are using macOS with Apple Silicon, you would use:

docker run -p 8888:8888 --rm dakomura/deep_texture_histology:mac_arm64-latest

This command will start a JupyterLab instance within the Docker container, which will be accessible through your web browser at http://localhost:8888⁠.

⁠Using the JupyterLab Interface:

Once JupyterLab is running, you can create new Jupyter Notebooks or edit existing ones to utilize the deeptexture library for your histological image analysis tasks. The library's documentation at https://deep-texture-histology.readthedocs.io/en/latest/⁠ will guide you through the various functionalities available, allowing you to process, analyze, and visualize histological image data efficiently.