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