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[Docs] Add keypoints order images in zh_cn doc #2128

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32 changes: 32 additions & 0 deletions docs/zh_cn/dataset_zoo/2d_animal_keypoint.md
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Expand Up @@ -33,6 +33,10 @@ MMPose supported datasets:

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227796953-95ae1e30-5323-43f8-9a19-c4c2326e9835.png" height="200px">
</div>

For [Animal-Pose](https://sites.google.com/view/animal-pose/) dataset, we prepare the dataset as follows:

1. Download the images of [PASCAL VOC2012](http://host.robots.ox.ac.uk/pascal/VOC/voc2012/#data), especially the five categories (dog, cat, sheep, cow, horse), which we use as trainval dataset.
Expand Down Expand Up @@ -118,6 +122,10 @@ Those images from other sources (1000 images with 1000 annotations) are used for

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227797151-091dc21a-d944-49c9-8b62-cc47fa89e69f.png" height="200px">
</div>

For [AP-10K](https://github.com/AlexTheBad/AP-10K/) dataset, images and annotations can be downloaded from [download](https://drive.google.com/file/d/1-FNNGcdtAQRehYYkGY1y4wzFNg4iWNad/view?usp=sharing).
Note, this data and annotation data is for non-commercial use only.

Expand Down Expand Up @@ -170,6 +178,10 @@ The annotation files in 'annotation' folder contains 50 labeled animal species.

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227797934-32bc1b2c-7957-4a29-94df-8e431842ab3b.png" height="200px">
</div>

For [Horse-10](http://www.mackenziemathislab.org/horse10) dataset, images can be downloaded from [download](http://www.mackenziemathislab.org/horse10).
Please download the annotation files from [horse10_annotations](https://download.openmmlab.com/mmpose/datasets/horse10_annotations.tar). Note, this data and annotation data is for non-commercial use only, per the authors (see http://horse10.deeplabcut.org for more information).
Extract them under {MMPose}/data, and make them look like this:
Expand Down Expand Up @@ -216,6 +228,10 @@ mmpose

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227799576-f10f8469-9432-4139-beb4-195037dee72c.png" height="200px">
</div>

For [MacaquePose](http://www.pri.kyoto-u.ac.jp/datasets/macaquepose/index.html) dataset, images can be downloaded from [download](http://www.pri.kyoto-u.ac.jp/datasets/macaquepose/index.html).
Please download the annotation files from [macaque_annotations](https://download.openmmlab.com/mmpose/datasets/macaque_annotations.tar).
Extract them under {MMPose}/data, and make them look like this:
Expand Down Expand Up @@ -266,6 +282,10 @@ Since the official dataset does not provide the test set, we randomly select 125

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227802774-bb4e4ef2-2ade-42ad-80f1-97f2a7faa9e2.png" height="200px">
</div>

For [Vinegar Fly](https://github.com/jgraving/DeepPoseKit-Data) dataset, images can be downloaded from [vinegar_fly_images](https://download.openmmlab.com/mmpose/datasets/vinegar_fly_images.tar).
Please download the annotation files from [vinegar_fly_annotations](https://download.openmmlab.com/mmpose/datasets/vinegar_fly_annotations.tar).
Extract them under {MMPose}/data, and make them look like this:
Expand Down Expand Up @@ -314,6 +334,10 @@ Since the official dataset does not provide the test set, we randomly select 90%

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227802779-09d0ec8c-8971-4c67-a315-e2d1355f7f72.png" height="200px">
</div>

For [Desert Locust](https://github.com/jgraving/DeepPoseKit-Data) dataset, images can be downloaded from [locust_images](https://download.openmmlab.com/mmpose/datasets/locust_images.tar).
Please download the annotation files from [locust_annotations](https://download.openmmlab.com/mmpose/datasets/locust_annotations.tar).
Extract them under {MMPose}/data, and make them look like this:
Expand Down Expand Up @@ -362,6 +386,10 @@ Since the official dataset does not provide the test set, we randomly select 90%

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227802783-ace952bb-1ff9-4720-80a8-c63cc9e714b6.png" height="200px">
</div>

For [Grévy’s Zebra](https://github.com/jgraving/DeepPoseKit-Data) dataset, images can be downloaded from [zebra_images](https://download.openmmlab.com/mmpose/datasets/zebra_images.tar).
Please download the annotation files from [zebra_annotations](https://download.openmmlab.com/mmpose/datasets/zebra_annotations.tar).
Extract them under {MMPose}/data, and make them look like this:
Expand Down Expand Up @@ -408,6 +436,10 @@ Since the official dataset does not provide the test set, we randomly select 90%

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227797386-fce99241-8a0e-4a40-a179-dad013e6c5a4.png" height="200px">
</div>

ATRW captures images of the Amur tiger (also known as Siberian tiger, Northeast-China tiger) in the wild.
For [ATRW](https://cvwc2019.github.io/challenge.html) dataset, please download images from
[Pose_train](https://lilablobssc.blob.core.windows.net/cvwc2019/train/atrw_pose_train.tar.gz),
Expand Down
36 changes: 36 additions & 0 deletions docs/zh_cn/dataset_zoo/2d_body_keypoint.md
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Expand Up @@ -37,6 +37,10 @@ MMPose supported datasets:

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227864552-489d03de-e1b8-4ca2-8ac1-80dd99826cb7.png" height="300px">
</div>

For [COCO](http://cocodataset.org/) data, please download from [COCO download](http://cocodataset.org/#download), 2017 Train/Val is needed for COCO keypoints training and validation.
[HRNet-Human-Pose-Estimation](https://github.com/HRNet/HRNet-Human-Pose-Estimation) provides person detection result of COCO val2017 to reproduce our multi-person pose estimation results.
Please download from [OneDrive](https://1drv.ms/f/s!AhIXJn_J-blWzzDXoz5BeFl8sWM-) or [GoogleDrive](https://drive.google.com/drive/folders/1fRUDNUDxe9fjqcRZ2bnF_TKMlO0nB_dk?usp=sharing).
Expand Down Expand Up @@ -91,6 +95,10 @@ mmpose

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227864660-e5f51e7d-deca-41d8-9725-8b5432bcc0e6.png" height="300px">
</div>

For [MPII](http://human-pose.mpi-inf.mpg.de/) data, please download from [MPII Human Pose Dataset](http://human-pose.mpi-inf.mpg.de/).
We have converted the original annotation files into json format, please download them from [mpii_annotations](https://download.openmmlab.com/mmpose/datasets/mpii_annotations.tar).
Extract them under {MMPose}/data, and make them look like this:
Expand Down Expand Up @@ -147,6 +155,10 @@ python tools/dataset/mat2json work_dirs/res50_mpii_256x256/pred.mat data/mpii/an

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227864382-ab722299-6806-4ae4-babb-7bcc5fb09662.png" height="300px">
</div>

For [MPII-TRB](https://github.com/kennymckormick/Triplet-Representation-of-human-Body) data, please download from [MPII Human Pose Dataset](http://human-pose.mpi-inf.mpg.de/).
Please download the annotation files from [mpii_trb_annotations](https://download.openmmlab.com/mmpose/datasets/mpii_trb_annotations.tar).
Extract them under {MMPose}/data, and make them look like this:
Expand Down Expand Up @@ -187,6 +199,10 @@ mmpose

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227864755-dd19644e-fccb-458b-a8c0-de55920261f5.png" height="300px">
</div>

For [AIC](https://github.com/AIChallenger/AI_Challenger_2017) data, please download from [AI Challenger 2017](https://github.com/AIChallenger/AI_Challenger_2017), 2017 Train/Val is needed for keypoints training and validation.
Please download the annotation files from [aic_annotations](https://download.openmmlab.com/mmpose/datasets/aic_annotations.tar).
Download and extract them under $MMPOSE/data, and make them look like this:
Expand Down Expand Up @@ -233,6 +249,10 @@ mmpose

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227864868-54a98493-df3a-44d8-acbc-6ec22043dfb9.png" height="300px">
</div>

For [CrowdPose](https://github.com/Jeff-sjtu/CrowdPose) data, please download from [CrowdPose](https://github.com/Jeff-sjtu/CrowdPose).
Please download the annotation files and human detection results from [crowdpose_annotations](https://download.openmmlab.com/mmpose/datasets/crowdpose_annotations.tar).
For top-down approaches, we follow [CrowdPose](https://arxiv.org/abs/1812.00324) to use the [pre-trained weights](https://pjreddie.com/media/files/yolov3.weights) of [YOLOv3](https://github.com/eriklindernoren/PyTorch-YOLOv3) to generate the detected human bounding boxes.
Expand Down Expand Up @@ -280,6 +300,10 @@ mmpose

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227864552-489d03de-e1b8-4ca2-8ac1-80dd99826cb7.png" height="300px">
</div>

For [OCHuman](https://github.com/liruilong940607/OCHumanApi) data, please download the images and annotations from [OCHuman](https://github.com/liruilong940607/OCHumanApi),
Move them under $MMPOSE/data, and make them look like this:

Expand Down Expand Up @@ -322,6 +346,10 @@ mmpose

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227865030-2fd33ade-2cc2-4b67-aca0-6dea2124b63c.png" height="300px">
</div>

For [MHP](https://lv-mhp.github.io/dataset) data, please download from [MHP](https://lv-mhp.github.io/dataset).
Please download the annotation files from [mhp_annotations](https://download.openmmlab.com/mmpose/datasets/mhp_annotations.tar.gz).
Please download and extract them under $MMPOSE/data, and make them look like this:
Expand Down Expand Up @@ -377,6 +405,10 @@ mmpose

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227865114-3f98c673-f6d0-4518-ae99-653f475f9fc8.png" height="300px">
</div>

For [PoseTrack18](https://posetrack.net/users/download.php) data, please download from [PoseTrack18](https://posetrack.net/users/download.php).
Please download the annotation files from [posetrack18_annotations](https://download.openmmlab.com/mmpose/datasets/posetrack18_annotations.tar).
We have merged the video-wise separated official annotation files into two json files (posetrack18_train & posetrack18_val.json). We also generate the [mask files](https://download.openmmlab.com/mmpose/datasets/posetrack18_mask.tar) to speed up training.
Expand Down Expand Up @@ -469,6 +501,10 @@ pip install git+https://github.com/svenkreiss/poseval.git

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227865619-d65f64ae-991d-4693-99c2-caecd1beb1fc.png" height="300px">
</div>

For [sub-JHMDB](http://jhmdb.is.tue.mpg.de/dataset) data, please download the [images](<(http://files.is.tue.mpg.de/jhmdb/Rename_Images.tar.gz)>) from [JHMDB](http://jhmdb.is.tue.mpg.de/dataset),
Please download the annotation files from [jhmdb_annotations](https://download.openmmlab.com/mmpose/datasets/jhmdb_annotations.tar).
Move them under $MMPOSE/data, and make them look like this:
Expand Down
16 changes: 16 additions & 0 deletions docs/zh_cn/dataset_zoo/2d_face_keypoint.md
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Expand Up @@ -32,6 +32,10 @@ MMPose supported datasets:

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227780043-e557acc3-5966-48ba-ac9e-b6c5916f1e55.jpg" height="200px">
</div>

For 300W data, please download images from [300W Dataset](https://ibug.doc.ic.ac.uk/resources/300-W/).
Please download the annotation files from [300w_annotations](https://download.openmmlab.com/mmpose/datasets/300w_annotations.tar).
Extract them under {MMPose}/data, and make them look like this:
Expand Down Expand Up @@ -108,6 +112,10 @@ mmpose

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227785100-4b3d1e39-0d64-47c0-9e55-c947ce70866e.png" height="200px">
</div>

For WFLW data, please download images from [WFLW Dataset](https://wywu.github.io/projects/LAB/WFLW.html).
Please download the annotation files from [wflw_annotations](https://download.openmmlab.com/mmpose/datasets/wflw_annotations.tar).
Extract them under {MMPose}/data, and make them look like this:
Expand Down Expand Up @@ -215,6 +223,10 @@ mmpose

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227786792-06604943-c062-4bcd-bb2d-a2f78d80115b.png" height="200px">
</div>

For COFW data, please download from [COFW Dataset (Color Images)](http://www.vision.caltech.edu/xpburgos/ICCV13/Data/COFW_color.zip).
Move `COFW_train_color.mat` and `COFW_test_color.mat` to `data/cofw/` and make them look like:

Expand Down Expand Up @@ -274,6 +286,10 @@ mmpose

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227787217-2f226dc0-e5d7-4d0b-9ab8-68b53a5467c2.png" height="200px">
</div>

For [COCO-WholeBody](https://github.com/jin-s13/COCO-WholeBody/) dataset, images can be downloaded from [COCO download](http://cocodataset.org/#download), 2017 Train/Val is needed for COCO keypoints training and validation.
Download COCO-WholeBody annotations for COCO-WholeBody annotations for [Train](https://drive.google.com/file/d/1thErEToRbmM9uLNi1JXXfOsaS5VK2FXf/view?usp=sharing) / [Validation](https://drive.google.com/file/d/1N6VgwKnj8DeyGXCvp1eYgNbRmw6jdfrb/view?usp=sharing) (Google Drive).
Download person detection result of COCO val2017 from [OneDrive](https://1drv.ms/f/s!AhIXJn_J-blWzzDXoz5BeFl8sWM-) or [GoogleDrive](https://drive.google.com/drive/folders/1fRUDNUDxe9fjqcRZ2bnF_TKMlO0nB_dk?usp=sharing).
Expand Down
4 changes: 4 additions & 0 deletions docs/zh_cn/dataset_zoo/2d_fashion_landmark.md
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Expand Up @@ -43,6 +43,10 @@ MMPose supported datasets:

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227774588-443fc5cc-7842-472a-abd5-827f0e3fd27f.png" height="150px">
</div>

For [DeepFashion](http://mmlab.ie.cuhk.edu.hk/projects/DeepFashion/LandmarkDetection.html) dataset, images can be downloaded from [download](http://mmlab.ie.cuhk.edu.hk/projects/DeepFashion/LandmarkDetection.html).
Please download the annotation files from [fld_annotations](https://download.openmmlab.com/mmpose/datasets/fld_annotations.tar).
Extract them under {MMPose}/data, and make them look like this:
Expand Down
24 changes: 24 additions & 0 deletions docs/zh_cn/dataset_zoo/2d_hand_keypoint.md
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Expand Up @@ -34,6 +34,10 @@ MMPose supported datasets:

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227771101-03a27bd8-ccc0-4eb9-a111-660f191a7a16.png" height="200px">
</div>

For [OneHand10K](https://www.yangangwang.com/papers/WANG-MCC-2018-10.html) data, please download from [OneHand10K Dataset](https://www.yangangwang.com/papers/WANG-MCC-2018-10.html).
Please download the annotation files from [onehand10k_annotations](https://download.openmmlab.com/mmpose/datasets/onehand10k_annotations.tar).
Extract them under {MMPose}/data, and make them look like this:
Expand Down Expand Up @@ -81,6 +85,10 @@ mmpose

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227771101-03a27bd8-ccc0-4eb9-a111-660f191a7a16.png" height="200px">
</div>

For [FreiHAND](https://lmb.informatik.uni-freiburg.de/projects/freihand/) data, please download from [FreiHand Dataset](https://lmb.informatik.uni-freiburg.de/resources/datasets/FreihandDataset.en.html).
Since the official dataset does not provide validation set, we randomly split the training data into 8:1:1 for train/val/test.
Please download the annotation files from [freihand_annotations](https://download.openmmlab.com/mmpose/datasets/frei_annotations.tar).
Expand Down Expand Up @@ -129,6 +137,10 @@ mmpose

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227771101-03a27bd8-ccc0-4eb9-a111-660f191a7a16.png" height="200px">
</div>

For [CMU Panoptic HandDB](http://domedb.perception.cs.cmu.edu/handdb.html), please download from [CMU Panoptic HandDB](http://domedb.perception.cs.cmu.edu/handdb.html).
Following [Simon et al](https://arxiv.org/abs/1704.07809), panoptic images (hand143_panopticdb) and MPII & NZSL training sets (manual_train) are used for training, while MPII & NZSL test set (manual_test) for testing.
Please download the annotation files from [panoptic_annotations](https://download.openmmlab.com/mmpose/datasets/panoptic_annotations.tar).
Expand Down Expand Up @@ -183,6 +195,10 @@ year = {2020}

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227771753-5df1d722-59bd-4815-b85f-64a5ef79bbf5.png" height="200px">
</div>

For [InterHand2.6M](https://mks0601.github.io/InterHand2.6M/), please download from [InterHand2.6M](https://mks0601.github.io/InterHand2.6M/).
Please download the annotation files from [annotations](https://drive.google.com/drive/folders/1pWXhdfaka-J0fSAze0MsajN0VpZ8e8tO).
Extract them under {MMPose}/data, and make them look like this:
Expand Down Expand Up @@ -232,6 +248,10 @@ mmpose

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227772014-f7406a2b-2e64-42fb-8081-200d40104553.png" height="200px">
</div>

For [RHD Dataset](https://lmb.informatik.uni-freiburg.de/resources/datasets/RenderedHandposeDataset.en.html), please download from [RHD Dataset](https://lmb.informatik.uni-freiburg.de/resources/datasets/RenderedHandposeDataset.en.html).
Please download the annotation files from [rhd_annotations](https://download.openmmlab.com/mmpose/datasets/rhd_annotations.zip).
Extract them under {MMPose}/data, and make them look like this:
Expand Down Expand Up @@ -288,6 +308,10 @@ mmpose

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227771101-03a27bd8-ccc0-4eb9-a111-660f191a7a16.png" height="200px">
</div>

For [COCO-WholeBody](https://github.com/jin-s13/COCO-WholeBody/) dataset, images can be downloaded from [COCO download](http://cocodataset.org/#download), 2017 Train/Val is needed for COCO keypoints training and validation.
Download COCO-WholeBody annotations for COCO-WholeBody annotations for [Train](https://drive.google.com/file/d/1thErEToRbmM9uLNi1JXXfOsaS5VK2FXf/view?usp=sharing) / [Validation](https://drive.google.com/file/d/1N6VgwKnj8DeyGXCvp1eYgNbRmw6jdfrb/view?usp=sharing) (Google Drive).
Download person detection result of COCO val2017 from [OneDrive](https://1drv.ms/f/s!AhIXJn_J-blWzzDXoz5BeFl8sWM-) or [GoogleDrive](https://drive.google.com/drive/folders/1fRUDNUDxe9fjqcRZ2bnF_TKMlO0nB_dk?usp=sharing).
Expand Down
8 changes: 8 additions & 0 deletions docs/zh_cn/dataset_zoo/2d_wholebody_keypoint.md
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Expand Up @@ -26,6 +26,10 @@ MMPose supported datasets:

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227770977-c8f00355-c43a-467e-8444-d307789cf4b2.png" height="300px">
</div>

For [COCO-WholeBody](https://github.com/jin-s13/COCO-WholeBody/) dataset, images can be downloaded from [COCO download](http://cocodataset.org/#download), 2017 Train/Val is needed for COCO keypoints training and validation.
Download COCO-WholeBody annotations for COCO-WholeBody annotations for [Train](https://drive.google.com/file/d/1thErEToRbmM9uLNi1JXXfOsaS5VK2FXf/view?usp=sharing) / [Validation](https://drive.google.com/file/d/1N6VgwKnj8DeyGXCvp1eYgNbRmw6jdfrb/view?usp=sharing) (Google Drive).
Download person detection result of COCO val2017 from [OneDrive](https://1drv.ms/f/s!AhIXJn_J-blWzzDXoz5BeFl8sWM-) or [GoogleDrive](https://drive.google.com/drive/folders/1fRUDNUDxe9fjqcRZ2bnF_TKMlO0nB_dk?usp=sharing).
Expand Down Expand Up @@ -80,6 +84,10 @@ Please also install the latest version of [Extended COCO API](https://github.com

</details>

<div align="center">
<img src="https://user-images.githubusercontent.com/100993824/227771087-b839ea5b-4461-4ba7-8a9a-823b78e2ca44.png" height="300px">
</div>

For [Halpe](https://github.com/Fang-Haoshu/Halpe-FullBody/) dataset, please download images and annotations from [Halpe download](https://github.com/Fang-Haoshu/Halpe-FullBody).
The images of the training set are from [HICO-Det](https://drive.google.com/open?id=1QZcJmGVlF9f4h-XLWe9Gkmnmj2z1gSnk) and those of the validation set are from [COCO](http://images.cocodataset.org/zips/val2017.zip).
Download person detection result of COCO val2017 from [OneDrive](https://1drv.ms/f/s!AhIXJn_J-blWzzDXoz5BeFl8sWM-) or [GoogleDrive](https://drive.google.com/drive/folders/1fRUDNUDxe9fjqcRZ2bnF_TKMlO0nB_dk?usp=sharing).
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