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pixano-inference's Introduction

Pixano

Data-centric AI building blocks for computer vision applications

Under active development, subject to API change

GitHub version PyPI version Tests Documentation Python version License


Pixano is an open-source tool by CEA List for exploring and annotating your dataset using AI features:

  • Fast dataset navigation using the the modern storage format Lance
  • Multi-view datasets support for images, and soon for 3D point clouds and videos
  • Import and export support for dataset formats like COCO
  • Semantic search using models like CLIP
  • Smart segmentation using models like SAM

Getting started

Installing Pixano

As Pixano requires specific versions for its dependencies, we recommend creating a new Python virtual environment to install it.

For example, with conda:

conda create -n pixano_env python=3.10
conda activate pixano_env

Then, you can install the Pixano package inside that environment with pip:

pip install pixano

Using your datasets

Please refer to our Jupyter notebooks for importing and exporting your datasets.

Using the Pixano app

Please refer to this link for using the Pixano app.

Contributing

Please refer to the CONTRIBUTING.md for information on running Pixano locally and guidelines on how to publish your contributions.

License

Pixano is licensed under the CeCILL-C license.

pixano-inference's People

Contributors

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Forkers

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pixano-inference's Issues

Update deprecated GitHub actions

Feature description

When a GitHub action like lint.yml runs, GitHub displays the following warning:

Node.js 16 actions are deprecated. Please update the following actions to use Node.js 20: actions/checkout@v3, actions/setup-node@v3, pnpm/action-setup@v2. For more information see: https://github.blog/changelog/2023-09-22-github-actions-transitioning-from-node-16-to-node-20/.

Expected solution

Update the GitHub actions to use the latest stable versions

Additional context

Add SAM alternatives

  • MobileSAM
  • EfficientSAM. Requires re-writing frontend code to use the two ONNX encoder and decoder models instead of using precomputed embeddings.
  • EdgeSAM. Requires re-writing frontend code to use the two ONNX encoder and decoder models instead of using precomputed embeddings.
  • MedSAM. Redefines the segment-anything module and thus does not seem to be usable in the same environment as a regular segment-anything installation.

Update docs deployment

Feature description

With pixano/pixano-project-manager#52, deployment of documentation website is being updated to be easier to manage and to be compatible with GitHub actions

Expected solution

  • Update navigation tabs and color theme of documentation website to be consistent with main website (pixano/pixano.github.io)
  • Add documentation website deployment to GitHub actions

Additional context

Publish Pixano Inference to PyPI

Feature description

With the 0.5.0 release of Pixano, and the 0.3.0 corresponding release of Pixano Inference, Pixano Inference should be published to PyPI to allow for easier installation for users.

Expected solution

Add GitHub action for publish Pixano Inference to PyPI automatically with new releases

Additional context

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