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[examples] adding the references for the new video API #2770

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1 change: 1 addition & 0 deletions .gitignore
Original file line number Diff line number Diff line change
Expand Up @@ -23,3 +23,4 @@ gen.yml
.mypy_cache
.vscode/
*.orig
*-checkpoint.ipynb
5 changes: 5 additions & 0 deletions examples/python/README.md
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Expand Up @@ -2,6 +2,9 @@

- [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pytorch/vision/blob/master/examples/python/tensor_transforms.ipynb)
[Examples of Tensor Images transformations](https://github.com/pytorch/vision/blob/master/examples/python/tensor_transforms.ipynb)
- [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pytorch/vision/blob/master/examples/python/video_api.ipynb)
[Example of VideoAPI](https://github.com/pytorch/vision/blob/master/examples/python/video_api.ipynb)


Prior to v0.8.0, transforms in torchvision have traditionally been PIL-centric and presented multiple limitations due to
that. Now, since v0.8.0, transforms implementations are Tensor and PIL compatible and we can achieve the following new
Expand All @@ -11,3 +14,5 @@ features:
- support for GPU acceleration
- batched transformation such as for videos
- read and decode data directly as torch tensor with torchscript support (for PNG and JPEG image formats)

Furthermore, previously we used to provide a very high-level API for video decoding which left little control to the user. We're now expanding that API (and replacing it in the future) with a lower-level API that allows the user a frame-based access to a video.
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