Running Bilayers Docker Images

Bilayers provides ready-to-use Docker images with Gradio or Jupyter Notebook interfaces for bioimage analysis algorithms. This guide explains how to pull and run these images via CLI (Command Line Interface) or Docker Desktop (GUI).

1. Pull the Docker Image (CLI or Docker Desktop)¶

Available Docker Images:

• classical_segmentation X Gradio :

  docker pull bilayer/classical_segmentation:1.0.0-gradio

• classical_segmentation X Jupyter_Notebook :

  docker pull bilayer/classical_segmentation:1.0.0-jupyter

• cellpose_inference X Gradio :

  docker pull bilayer/cellpose:1.0.1-gradio

• cellpose_inference X Jupyter_Notebook :

  docker pull bilayer/cellpose:1.0.0-jupyter

• instanseg_inference X Gradio :

  docker pull bilayer/instanseg:1.0.2_pixi_gradio

• instanseg_inference X Jupyter :

  docker pull bilayer/instanseg:1.0.2_pixi_jupyter

Using CLI:

• Open a terminal and run:

docker pull bilayer/<repo_name>:<tag>

Using Docker Desktop (GUI):

• Open Docker Desktop, go to the Images tab, and search for bilayer
• Pull the image directly from DockerHub

2. Run the Docker Container (CLI or Docker Desktop)¶

Using CLI:

• Gradio Interface (No Volume Mount):

docker run -it --rm bilayer/<repo_name>:<tag>

• Jupyter Interface (Requires Volume Mount):

docker run -it --rm -v /path/to/your/data:/bilayers/input_images bilayer/<repo_name>:<tag>

Using Docker Desktop (GUI):

• Gradio: Start the Image as-is, assign it a name, and select an available port (e.g., 8000 for Gradio)

• Jupyter: Use the Volume option to mount your data directory to /bilayers/input_images