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Dataset Preparation

Kinetics

The Kinetics Dataset could be downloaded via the code released by ActivityNet:

  1. Download the videos via the official scripts.

  2. After all the videos were downloaded, resize the video to the short edge size of 256, then prepare the csv files for training, validation, and testing set as train.csv, val.csv, test.csv. The format of the csv file is:

path_to_video_1 label_1
path_to_video_2 label_2
path_to_video_3 label_3
...
path_to_video_N label_N

All the Kinetics models in the Model Zoo are trained and tested with the same data as Non-local Network. For dataset specific issues, please reach out to the dataset provider.

Charades-Ego

  1. Download RGB frames of Charades-Ego from the offical website.

  2. Download the frame list from the following links: (train, val).

Please set DATA.PATH_TO_DATA_DIR to point to the folder containing the frame lists, and DATA.PATH_PREFIX to the folder containing RGB frames. For example, we set the symlinks as follow:

mkdir -p data/charades-ego
ln -s /path/to/Charades-Ego/CharadesEgo_v1_rgb data/charades-ego/rgb
ln -s /path/to/Charades-Ego/charades_ego_split data/charades-ego/split

Epic-Kitchen-55

  1. Download the RGB frames from EPIC Kitchens 55.

  2. Download the frame list from the following links: (train, val, trainval. Note that the train/val split is following temporal-binding-network

Please set DATA.PATH_TO_DATA_DIR to point to the folder containing the frame lists, and DATA.PATH_PREFIX to the folder containing RGB frames. For example, we set the symlinks as follow:

mkdir -p data/epic-55/split
ln -s /path/to/epic-kitchen-55/rgb_extracted/train data/epic-55/train_rgb_frames
ln -s /path/to/ego-exo/dataset_split_files/epic_55_split/ data/epic-55/split

Epic-Kitchen-100

  1. Download the RGB frames and annotations from EPIC Kitchens 100.

  2. Please set DATA.PATH_TO_DATA_DIR to point to the folder containing the frame lists, and DATA.PATH_PREFIX to the folder containing RGB frames. For example, we set the symlinks as follow:

mkdir -p data/epic-100/
ln -s  /path/to/EPIC-KITCHENS-100 data/epic-100/dataset
ln -s /path/to/epic-kitchens-100-annotations data/epic-100/annotations