@misc{goyal2017something,
title={The "something something" video database for learning and evaluating visual common sense},
author={Raghav Goyal and Samira Ebrahimi Kahou and Vincent Michalski and Joanna Materzyńska and Susanne Westphal and Heuna Kim and Valentin Haenel and Ingo Fruend and Peter Yianilos and Moritz Mueller-Freitag and Florian Hoppe and Christian Thurau and Ingo Bax and Roland Memisevic},
year={2017},
eprint={1706.04261},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
For basic dataset information, you can refer to the dataset website.
````{group-tab} Download by MIM
MIM supports downloading from OpenDataLab and preprocessing Something-Something V2 dataset with one command line.
```Bash
# install OpenXlab CLI tools
pip install -U openxlab
# log in OpenXLab
openxlab login
# download and preprocess by MIM
mim download mmaction2 --dataset sthv2
```
````
## Step 1. Prepare Annotations
First of all, you have to sign in and download annotations to `$MMACTION2/data/sthv2/annotations` on the official [website](https://20bn.com/datasets/something-something/v2).
Before we start, please make sure that the directory is located at `$MMACTION2/tools/data/sthv2/`.
## Step 2. Prepare Videos
Then, you can download all data parts to `$MMACTION2/data/sthv2/` and use the following command to uncompress.
```shell
cd $MMACTION2/data/sthv2/
cat 20bn-something-something-v2-?? | tar zx
cd $MMACTION2/tools/data/sthv2/
```
## Step 3. Extract RGB and Flow
This part is **optional** if you only want to use the video loader.
Before extracting, please refer to [install.md](/docs/en/get_started/installation.md) for installing [denseflow](https://github.com/open-mmlab/denseflow).
If you have plenty of SSD space, then we recommend extracting frames there for better I/O performance.
You can run the following script to soft link SSD.
```shell
# execute these two line (Assume the SSD is mounted at "/mnt/SSD/")
mkdir /mnt/SSD/sthv2_extracted/
ln -s /mnt/SSD/sthv2_extracted/ ../../../data/sthv2/rawframes
```
If you only want to play with RGB frames (since extracting optical flow can be time-consuming), consider running the following script to extract **RGB-only** frames using denseflow.
```shell
cd $MMACTION2/tools/data/sthv2/
bash extract_rgb_frames.sh
```
If you didn't install denseflow, you can still extract RGB frames using OpenCV by the following script, but it will keep the original size of the images.
```shell
cd $MMACTION2/tools/data/sthv2/
bash extract_rgb_frames_opencv.sh
```
If both are required, run the following script to extract frames.
```shell
cd $MMACTION2/tools/data/sthv2/
bash extract_frames.sh
```
## Step 4. Generate File List
you can run the follow script to generate file list in the format of rawframes and videos.
```shell
cd $MMACTION2/tools/data/sthv2/
bash generate_{rawframes, videos}_filelist.sh
```
````
After the whole data process for Something-Something V2 preparation, you will get the rawframes (RGB + Flow), videos and annotation files for Something-Something V2.
In the context of the whole project (for Something-Something V2 only), the folder structure will look like:
mmaction2
├── mmaction
├── tools
├── configs
├── data
│ ├── sthv2
│ │ ├── sthv2_{train,val}_list_rawframes.txt(Optional)
│ │ ├── sthv2_{train,val}_list_videos.txt
│ │ ├── annotations(Optional)
│ | ├── videos
│ | | ├── 1.mp4
│ | | ├── 2.mp4
│ | | ├──...
│ | ├── rawframes(Optional)
│ | | ├── 1
│ | | | ├── img_00001.jpg
│ | | | ├── img_00002.jpg
│ | | | ├── ...
│ | | | ├── flow_x_00001.jpg
│ | | | ├── flow_x_00002.jpg
│ | | | ├── ...
│ | | | ├── flow_y_00001.jpg
│ | | | ├── flow_y_00002.jpg
│ | | | ├── ...
│ | | ├── 2
│ | | ├── ...
For training and evaluating on Something-Something V2, please refer to Training and Test Tutorial.