| # Dataset Preparation | |
| ## Kinetics | |
| The Kinetics Dataset could be downloaded from the following [link](https://github.com/cvdfoundation/kinetics-dataset): | |
| 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 | |
| ``` | |
| ## Something-Something V2 | |
| 1. Please download the dataset and annotations from [dataset provider](https://20bn.com/datasets/something-something). | |
| 2. Download the *frame list* from the following links: ([train](https://dl.fbaipublicfiles.com/pyslowfast/dataset/ssv2/frame_lists/train.csv), [val](https://dl.fbaipublicfiles.com/pyslowfast/dataset/ssv2/frame_lists/val.csv)). | |
| 3. Extract the frames at 30 FPS. (We used ffmpeg-4.1.3 with command | |
| `ffmpeg -i "${video}" -r 30 -q:v 1 "${out_name}"` | |
| in experiments.) Please put the frames in a structure consistent with the frame lists. | |
| Please put all annotation json files and the frame lists in the same folder, and set `DATA.PATH_TO_DATA_DIR` to the path. Set `DATA.PATH_PREFIX` to be the path to the folder containing extracted frames. | |