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Update Pose docs with keypoint explanations (#14248)

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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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JF Chen 2024-07-08 06:09:07 +08:00 • committed by GitHub
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@ -39,6 +39,26 @@ The output of a pose estimation model is a set of points that represent the keyp
YOLOv8 _pose_ models use the `-pose` suffix, i.e. `yolov8n-pose.pt`. These models are trained on the [COCO keypoints](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco-pose.yaml) dataset and are suitable for a variety of pose estimation tasks.
In the default YOLOv8 pose model, there are 17 keypoints, each representing a different part of the human body. Here is the mapping of each index to its respective body joint:
0: Nose
1: Left Eye
2: Right Eye
3: Left Ear
4: Right Ear
5: Left Shoulder
6: Right Shoulder
7: Left Elbow
8: Right Elbow
9: Left Wrist
10: Right Wrist
11: Left Hip
12: Right Hip
13: Left Knee
14: Right Knee
15: Left Ankle
16: Right Ankle
## [Models](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/cfg/models/v8)
YOLOv8 pretrained Pose models are shown here. Detect, Segment and Pose models are pretrained on the [COCO](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco.yaml) dataset, while Classify models are pretrained on the [ImageNet](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/ImageNet.yaml) dataset.