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@@ -15,7 +15,7 @@ Video-Dataset-Loading-Pytorch provides the lowest entry barrier for setting up d
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The VideoFrameDataset class (an implementation of `torch.utils.data.Dataset`) serves to `easily`, `efficiently` and `effectively` load video samples from video datasets in PyTorch.
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1) Easily because this dataset class can be used with custom datasets with minimum effort and no modification. The class merely expects the
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video dataset to have a certain structure on disk and expects a .txt annotation file that enumerates each video sample. Details on this
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can be found below. Pre-made annotation files and preparation scripts are also provided for [Kinetics 400](https://github.com/cvdfoundation/kinetics-dataset), [Something Something V2](https://20bn.com/datasets/something-something) and [EPIC-KITCHENS-100](https://epic-kitchens.github.io/2021).
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can be found below. Pre-made annotation files and preparation scripts are also provided for [Kinetics 400](https://github.com/cvdfoundation/kinetics-dataset), [Something Something V2](https://20bn.com/datasets/something-something) and [Epic Kitchens 100](https://epic-kitchens.github.io/2021).
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2) Efficiently because the video loading pipeline that this class implements is very fast. This minimizes GPU waiting time during training by eliminating input bottlenecks
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that can slow down training time by several folds.
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3) Effectively because the implemented sampling strategy for video frames is very strong. Video training using the entire sequence of
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