A GPU-accelerated library that enables random frame access and efficient video decoding for data loading.

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  • License: MIT License (MIT)
  • Author: genie
  • Tags dataset , nvcodec , serious-scaffold , video
  • Requires: Python >=3.10
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Project description

VideoDataset

A GPU-accelerated library that enables random frame access and efficient video decoding for data loading.

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[!WARNING] VideoDataset is in the Alpha phase. Frequent changes and instability should be anticipated. Any feedback, comments, suggestions and contributions are welcome!

Overview

VideoDataset is a high-performance video decoding multi-framework supporting library. It aims to provide framework-integrated solutions for working with video decoding tasks.

Key Features:

  • GPU-accelerated video decoding using NvCodec library
  • Support for common video formats (H.264, H.265, etc.)
  • Easy integration with multi-frameworks and multi-formats.

Documentation

Full documentation is available at: Documentation.

Also, a sphinx-based documentation can be generated by running the following command:

make dev-doc doc-coverage

It will generate the documentation in the docs/_build/html directory and serve it on http://localhost:8000.

License

MIT License, for more details, see the LICENSE file.

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  • License: MIT License (MIT)
  • Author: genie
  • Tags dataset , nvcodec , serious-scaffold , video
  • Requires: Python >=3.10
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0.1.5

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