Preparing Diving48¶

Introduction¶

@inproceedings{li2018resound,
  title={Resound: Towards action recognition without representation bias},
  author={Li, Yingwei and Li, Yi and Vasconcelos, Nuno},
  booktitle={Proceedings of the European Conference on Computer Vision (ECCV)},
  pages={513--528},
  year={2018}
}

For basic dataset information, you can refer to the official dataset website.

MIM supports downloading from OpenDataLab and preprocessing Diving48 dataset with one command line.

# install OpenDataLab CLI tools
pip install -U opendatalab
# log in OpenDataLab
odl login
# download and preprocess by MIM
mim download mmaction2 --dataset diving48

Step 1. Prepare Annotations

You can run the following script to download annotations (considering the correctness of annotation files, we only download V2 version here). Before we start, please make sure that the directory is located at $MMACTION2/tools/data/diving48/.

bash download_annotations.sh

Step 2. Prepare Videos

You can run the following script to download videos.

bash download_videos.sh

Step 3. Prepare RGB and Flow

This part is optional if you only want to use the video loader.

The frames provided in official compressed file are not complete. You may need to go through the following extraction steps to get the complete frames.

Before extracting, please refer to install.md for installing 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.

# execute these two line (Assume the SSD is mounted at "/mnt/SSD/")
mkdir /mnt/SSD/diving48_extracted/
ln -s /mnt/SSD/diving48_extracted/ ../../../data/diving48/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.

cd $MMACTION2/tools/data/diving48/
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.

cd $MMACTION2/tools/data/diving48/
bash extract_rgb_frames_opencv.sh

If both are required, run the following script to extract frames.

cd $MMACTION2/tools/data/diving48/
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.

bash generate_videos_filelist.sh
bash generate_rawframes_filelist.sh

Check Directory Structure¶

After the whole data process for Diving48 preparation, you will get the rawframes (RGB + Flow), videos and annotation files for Diving48.

In the context of the whole project (for Diving48 only), the folder structure will look like:

mmaction2
├── mmaction
├── tools
├── configs
├── data
│   ├── diving48
│   │   ├── diving48_{train,val}_list_rawframes.txt
│   │   ├── diving48_{train,val}_list_videos.txt
│   │   ├── annotations (optinonal)
│   |   |   ├── Diving48_V2_train.json
│   |   |   ├── Diving48_V2_test.json
│   |   |   ├── Diving48_vocab.json
│   |   ├── videos
│   |   |   ├── _8Vy3dlHg2w_00000.mp4
│   |   |   ├── _8Vy3dlHg2w_00001.mp4
│   |   |   ├── ...
│   |   ├── rawframes (optional)
│   |   |   ├── 2x00lRzlTVQ_00000
│   |   |   |   ├── img_00001.jpg
│   |   |   |   ├── img_00002.jpg
│   |   |   |   ├── ...
│   |   |   |   ├── flow_x_00001.jpg
│   |   |   |   ├── flow_x_00002.jpg
│   |   |   |   ├── ...
│   |   |   |   ├── flow_y_00001.jpg
│   |   |   |   ├── flow_y_00002.jpg
│   |   |   |   ├── ...
│   |   |   ├── 2x00lRzlTVQ_00001
│   |   |   ├── ...

For training and evaluating on Diving48, please refer to Training and Test Tutorial.