Data Preparation

Kinetics

For more information about Kinetics dataset, please refer the official website. You can take the following steps to prepare the dataset:

1. Download the videos via the official scripts.

2. Preprocess the downloaded videos by resizing to the short edge size of 256.

3. 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 and PySlowFast. For dataset specific issues, please reach out to the dataset provider.

Charades

We follow PySlowFast to prepare the Charades dataset as follow:

1. Download the Charades RGB frames from official website.

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

Something-Something V2

We follow PySlowFast to prepare the Something-Something V2 dataset as follow:

1. Download the dataset and annotations from official website.

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

3. Extract the frames from downloaded videos at 30 FPS. We used ffmpeg-4.1.3 with command:

   ffmpeg -i "${video}" -r 30 -q:v 1 "${out_name}"
   

4. The extracted frames should be organized to be consistent with the paths in frame lists.