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PyTorch video dataset library

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A PyTorch library for video-based computer vision tasks. torchvideo provides dataset loaders specialised for video, video frame samplers, and transformations specifically for video.

Get started

Set up an accelerated environment in conda

$ conda env create -f environment.yml -n torchvideo
$ conda activate torchvideo

# The following steps are taken from

$ conda uninstall -y --force pillow pil jpeg libtiff
$ pip uninstall -y pillow pil jpeg libtiff
$ conda install -y -c conda-forge libjpeg-turbo
$ CFLAGS="${CFLAGS} -mavx2" pip install --upgrade --no-cache-dir --force-reinstall --no-binary :all: --compile pillow-simd
$ conda install -y jpeg libtiff

NOTE: If the installation of pillow-simd fails, you can try installing GCC from conda-forge and trying the install again:

$ conda install -y gxx_linux-64
$ export CXX=x86_64-conda_cos6-linux-gnu-g++
$ export CC=x86_64-conda_cos6-linux-gnu-gcc
$ CFLAGS="${CFLAGS} -mavx2" pip install --upgrade --no-cache-dir --force-reinstall --no-binary :all: --compile pillow-simd
$ conda install -y jpeg libtiff

If you install any new packages, check that pillow-simd hasn't be overwritten by an alternate pillow install by running:

$ python -c "from PIL import Image; print(Image.PILLOW_VERSION)"

You should see something like


Pillow doesn't release with post suffixes, so if you have post in the version name, it's likely you have pillow-simd installed.

Install torchvideo

$ pip install git+

Learn how to use torchvideo

Check out the example notebooks, you can launch these on binder without having to install anything locally!


Thanks to the following people and projects

  • yjxiong for his work on TSN and publicly available pytorch implementation from which many of the transforms in this project started from.
  • dukebw for his excellent lintel FFmpeg video loading library.
  • hypothesis and the team behind it. This has been used heavily in testing the project.

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torchvideo-0.0.1.tar.gz (48.3 kB view hashes)

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