| # Preparing Kinetics-710 | |
| ## Introduction | |
| <!-- [DATASET] --> | |
| ```BibTeX | |
| @misc{li2022uniformerv2, | |
| title={UniFormerV2: Spatiotemporal Learning by Arming Image ViTs with Video UniFormer}, | |
| author={Kunchang Li and Yali Wang and Yinan He and Yizhuo Li and Yi Wang and Limin Wang and Yu Qiao}, | |
| year={2022}, | |
| eprint={2211.09552}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CV} | |
| } | |
| ``` | |
| For basic dataset information, please refer to the [paper](https://arxiv.org/pdf/2211.09552.pdf). The scripts can be used for preparing kinetics-710. MMAction2 supports Kinetics-710 | |
| dataset as a concat dataset, which means only provides a list of annotation files, and makes use of the original data of Kinetics-400/600/700 dataset. You could refer to the [config](/configs/recognition/uniformerv2/uniformerv2-base-p16-res224_clip_u8_kinetics710-rgb.py) | |
| for details, which also provides a template config about how to use concat dataset in MMAction2. | |
| Before we start, please make sure that the directory is located at `$MMACTION2`. | |
| ## Step 1. Download Kinetics 400/600/700 | |
| Kinetics-710 is a video benchmark based on Kinetics-400/600/700, which merges the training set of these Kinetics datasets, and deletes the repeated videos according to Youtube IDs. MMAction2 provides an annotation file based on the Kinetics-400/600/700 on [OpenDataLab](https://opendatalab.com/). So we suggest you download Kinetics-400/600/700 first from OpenDataLab by [MIM](https://github.com/open-mmlab/mim). | |
| ```shell | |
| # install OpenXlab CLI tools | |
| pip install -U openxlab | |
| # log in OpenXLab | |
| openxlab login | |
| # download Kinetics-400/600/700, note that this might take a long time. | |
| mim download mmaction2 --dataset kinetics400 | |
| mim download mmaction2 --dataset kinetics600 | |
| mim download mmaction2 --dataset kinetics700 | |
| ``` | |
| ## Step 2. Download Kinetics-710 Annotations | |
| We provide the annotation list of Kinetics-710 corresponding to OpenDataLab version Kinetics, you could download it from aliyun and unzip it to the `$MMACTION2/data/` | |
| ```shell | |
| wget -P data https://download.openmmlab.com/mmaction/dataset/kinetics710/annotations.zip | |
| cd data && unzip annotations.zip && cd .. | |
| ``` | |
| ## Step 3. Folder Structure | |
| After the whole data pipeline for Kinetics preparation. | |
| you can get the videos and annotation files for Kinetics-710. | |
| In the context of the whole project (for Kinetics only), the *minimal* folder structure will look like: | |
| (*minimal* means that some data are not necessary: for example, you may want to evaluate kinetics using the original video format.) | |
| ``` | |
| mmaction2 | |
| ├── mmaction | |
| ├── tools | |
| ├── configs | |
| ├── data | |
| │ ├── kinetics400 | |
| │ │ ├── videos_train | |
| │ │ ├── videos_val | |
| │ │ │ ├── jf7RDuUTrsQ.mp4 | |
| │ │ │ ├── ... | |
| │ ├── kinetics600 | |
| │ │ ├── videos | |
| │ │ │ ├── vol_00 | |
| │ │ │ │ ├── -A5JFdMXB_k_000018_000028.mp4 | |
| │ │ │ │ ├── ... | |
| │ │ │ ├── ... | |
| │ │ │ ├── vol63 | |
| │ ├── kinetics700 | |
| │ │ ├── videos | |
| │ │ │ ├── vol_00 | |
| │ │ │ │ ├── -Paa0R0tQ1w_000009_000019.mp4 | |
| │ │ │ │ ├── ... | |
| │ │ │ ├── ... | |
| │ │ │ ├── vol63 | |
| │ ├── kinetics710 | |
| │ │ ├── k400_train_list_videos.txt | |
| │ │ ├── k400_val_list_videos.txt | |
| │ │ ├── k600_train_list_videos.txt | |
| │ │ ├── k600_val_list_videos.txt | |
| │ │ ├── k700_train_list_videos.txt | |
| │ │ ├── k700_val_list_videos.txt | |
| ``` | |
| For training and evaluating on Kinetics, please refer to [Training and Test Tutorial](/docs/en/user_guides/train_test.md). | |