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2D Wholebody Keypoint Datasets

It is recommended to symlink the dataset root to $MMPOSE/data. If your folder structure is different, you may need to change the corresponding paths in config files.

MMPose supported datasets:

COCO-WholeBody

COCO-WholeBody (ECCV'2020)
@inproceedings{jin2020whole,
  title={Whole-Body Human Pose Estimation in the Wild},
  author={Jin, Sheng and Xu, Lumin and Xu, Jin and Wang, Can and Liu, Wentao and Qian, Chen and Ouyang, Wanli and Luo, Ping},
  booktitle={Proceedings of the European Conference on Computer Vision (ECCV)},
  year={2020}
}

For COCO-WholeBody dataset, images can be downloaded from COCO download, 2017 Train/Val is needed for COCO keypoints training and validation. Download COCO-WholeBody annotations for COCO-WholeBody annotations for Train / Validation (Google Drive). Download person detection result of COCO val2017 from OneDrive or GoogleDrive. Download and extract them under $MMPOSE/data, and make them look like this:

mmpose
├── mmpose
├── docs
├── tests
├── tools
├── configs
`── data
    │── coco
        │-- annotations
        │   │-- coco_wholebody_train_v1.0.json
        │   |-- coco_wholebody_val_v1.0.json
        |-- person_detection_results
        |   |-- COCO_val2017_detections_AP_H_56_person.json
        │-- train2017
        │   │-- 000000000009.jpg
        │   │-- 000000000025.jpg
        │   │-- 000000000030.jpg
        │   │-- ...
        `-- val2017
            │-- 000000000139.jpg
            │-- 000000000285.jpg
            │-- 000000000632.jpg
            │-- ...

Please also install the latest version of Extended COCO API (version>=1.5) to support COCO-WholeBody evaluation:

pip install xtcocotools

Halpe

Halpe (CVPR'2020)
@inproceedings{li2020pastanet,
  title={PaStaNet: Toward Human Activity Knowledge Engine},
  author={Li, Yong-Lu and Xu, Liang and Liu, Xinpeng and Huang, Xijie and Xu, Yue and Wang, Shiyi and Fang, Hao-Shu and Ma, Ze and Chen, Mingyang and Lu, Cewu},
  booktitle={CVPR},
  year={2020}
}

For Halpe dataset, please download images and annotations from Halpe download. The images of the training set are from HICO-Det and those of the validation set are from COCO. Download person detection result of COCO val2017 from OneDrive or GoogleDrive. Download and extract them under $MMPOSE/data, and make them look like this:

mmpose
├── mmpose
├── docs
├── tests
├── tools
├── configs
`── data
    │── halpe
        │-- annotations
        │   │-- halpe_train_v1.json
        │   |-- halpe_val_v1.json
        |-- person_detection_results
        |   |-- COCO_val2017_detections_AP_H_56_person.json
        │-- hico_20160224_det
        │   │-- anno_bbox.mat
        │   │-- anno.mat
        │   │-- README
        │   │-- images
        │   │   │-- train2015
        │   │   │   │-- HICO_train2015_00000001.jpg
        │   │   │   │-- HICO_train2015_00000002.jpg
        │   │   │   │-- HICO_train2015_00000003.jpg
        │   │   │   │-- ...
        │   │   │-- test2015
        │   │-- tools
        │   │-- ...
        `-- val2017
            │-- 000000000139.jpg
            │-- 000000000285.jpg
            │-- 000000000632.jpg
            │-- ...

Please also install the latest version of Extended COCO API (version>=1.5) to support Halpe evaluation:

pip install xtcocotools

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