Build from Source

1. Clone the repository:

   # https
   git clone https://github.com/paidiver/paidiverpy.git
   cd paidiverpy

2. (Optional) Create a Python virtual environment to manage dependencies separately from other projects. For example, using conda:

   conda env create -f environment.yml
   conda activate Paidiverpy

3. Install the paidiverpy package:

   pip install -e .

Python Package

Install the package and utilize it in your Python scripts.

# Import the Pipeline class
from paidiverpy.pipeline import Pipeline

# Instantiate the Pipeline class with the configuration file path
# Please refer to the documentation for the configuration file format
pipeline = Pipeline(config_file_path="../examples/config_files/config_simple2.yml")

# Run the pipeline
pipeline.run()

You can export the output images to the specified output directory:

pipeline.save_images(image_format="png")

Command Line Interface (CLI)

Pipelines can be executed via command-line arguments. For example:

paidiverpy -c "examples/config_files/config_simple.yml"

This runs the pipeline according to the configuration file, saving output images to the directory defined in the output_path.

Docker

You can run Paidiverpy using Docker by pulling a pre-built image from GitHub Container Registry (GHCR) or Docker Hub.

docker pull ghcr.io/paidiver/paidiverpy:latest
docker tag ghcr.io/paidiver/paidiverpy:latest paidiverpy:latest

To run the container, use the following command:

docker run --rm \
  -v <INPUT_PATH>:/app/input/ \
  -v <OUTPUT_PATH>:/app/output/ \
  -v <METADATA_PATH>:/app/metadata/ \
  -v <CONFIG_DIR>:/app/config_files/ \
  paidiverpy -c /app/examples/config_files/<CONFIG_FILE>