Installation#

Dependencies#

  • Python (3.10+)

  • Optional: OpenVINO, TensorFlow, PyTorch, MxNet, Caffe, Git

Installation steps#

Optionally, set up a virtual environment:

python -m pip install virtualenv
python -m virtualenv venv
. venv/bin/activate

Install:

  1. From PyPI (recommended)

    pip install datumaro

  2. From the GitHub repository (not recommended, for advanced users)

    Installation from the repository source is not recommended. This is because it requires that C++ and Rust build systems are prepared in your local environment before installation. Datumaro includes C++ and Rust implementations to accelerate some workloads to overcome Python’s innate slowness.

    # Prerequisite (For Unix-like systems)
# Install C++ build system
sudo apt-get install build-essential
# Install Rust build system
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

# Install from the GitHub repository
pip install 'datumaro @ git+https://github.com/open-edge-platform/datumaro'

Plugins#

Datumaro has many plugins, which are responsible for dataset formats, model launchers and other optional components. If a plugin has dependencies, they can require additional installation. You can find the list of all the plugin dependencies in the [plugins](/docs/user-manual/extending) section.

Optional dependencies These components are only required for plugins and not installed by default:

  • TensorFlow

  • PyTorch

  • MxNet

  • Caffe

Customizing installation#

  • When installing directly from the repository, you can change the installation branch with ...@<branch_name>. Also use --force-reinstall parameter in this case. It can be useful for testing of unreleased versions from GitHub pull requests.