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A library for interacting with the Datamint API, designed for efficient data management, processing and Deep Learning workflows.

Project description

Datamint Python API

Build Status Python 3.10+

A comprehensive Python SDK for interacting with the Datamint platform, providing seamless integration for medical imaging workflows, dataset management, and machine learning experiments.

📋 Table of Contents

🚀 Features

  • Dataset Management: Download, upload, and manage medical imaging datasets
  • Annotation Tools: Create, upload, and manage annotations (segmentations, labels, measurements)
  • Experiment Tracking: Integrated MLflow support for experiment management
  • PyTorch Lightning Integration: Streamlined ML workflows with Lightning DataModules and callbacks
  • DICOM Support: Native handling of DICOM files with anonymization capabilities
  • Multi-format Support: PNG, JPEG, NIfTI, and other medical imaging formats

See the full documentation at https://sonanceai.github.io/datamint-python-api/

📦 Installation

[!NOTE] We recommend using a virtual environment to avoid package conflicts.

From PyPI

pip install -U datamint

Virtual Environment Setup

Click to expand virtual environment setup instructions

We recommend that you install Datamint in a dedicated virtual environment, to avoid conflicting with your system packages. For instance, create the enviroment once with python3 -m venv datamint-env and then activate it whenever you need it with:

  1. Create the environment (one-time setup):

    python3 -m venv datamint-env
    
  2. Activate the environment (run whenever you need it):

    Platform Command
    Linux/macOS source datamint-env/bin/activate
    Windows CMD datamint-env\Scripts\activate.bat
    Windows PowerShell datamint-env\Scripts\Activate.ps1
  3. Install the package:

    pip install datamint
    

⚙ Setup API key

To use the Datamint API, you need to setup your API key (ask your administrator if you don't have one). Use one of the following methods to setup your API key:

Method 1: Command-line tool (recommended)

Run datamint-config in the terminal and follow the instructions. See command_line_tools for more details.

Method 2: Environment variable

Specify the API key as an environment variable.

Bash:

export DATAMINT_API_KEY="my_api_key"
# run your commands (e.g., `datamint-upload`, `python script.py`)

Python:

import os
os.environ["DATAMINT_API_KEY"] = "my_api_key"

📚 Documentation

Resource Description
🚀 Getting Started Step-by-step setup and basic usage
📖 API Reference Complete API documentation
🔥 PyTorch Integration ML workflow integration
💡 Examples Practical usage examples

🛠️ Command Line Tools

Full documentation at command_line_tools.

Upload Resources

Upload DICOM files with anonymization:

datamint-upload /path/to/dicoms --recursive --channel "training-data" --publish --tag "my_data_tag"

It anonymizes by default.

Configuration Management

# Interactive setup
datamint-config

# Set API key
datamint-config --api-key "your-key"

🆘 Support

Full Documentation
GitHub Issues

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