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A library to preprocess image data.

Project description

Paidiverpy

lifecycle License Documentation DOI Pypi

Paidiverpy is a Python package designed to create pipelines for preprocessing image data for biodiversity analysis.

IMPORTANT: This package is still in active development, and frequent updates and changes are expected. The API and features may evolve as we continue improving it.

Documentation

The official documentation is hosted on ReadTheDocs.org: https://paidiverpy.readthedocs.io/

IMPORTANT: Comprehensive documentation is under construction.

Installation

To install paidiverpy, run:

pip install paidiverpy

Build from Source

  1. Clone the repository:

    # ssh
    git clone git@github.com:paidiver/paidiverpy.git
    
    # 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 .

Usage

You can run your preprocessing pipeline using Paidiverpy in several ways, typically requiring just one to three lines of code:

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)

Execute the package via the command line.

paidiverpy -c "../examples/config_files/config_simple2.yml"

Docker

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

  1. Build the container locally:

    git clone git@github.com:paidiver/paidiverpy.git
    cd paidiverpy
    docker build -t paidiverpy .
  2. Pull from GitHub Container Registry (GHCR):

    docker pull ghcr.io/paidiver/paidiverpy:latest
    docker tag ghcr.io/paidiver/paidiverpy:latest paidiverpy:latest
  3. Pull from Docker Hub:

    docker pull soutobias/paidiverpy:latest
    docker tag soutobias/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>

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