File size: 3,860 Bytes
d3dbf03 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 | # 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).
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