TopDown Pose Estimation on iOS and PureSwift.
- BBox: Yolov7-tiny
- Pose Estimation: ViTPose
$ git clone https://github.com/otmb/TopDownPoseEstimation.git
$ cd TopDownPoseEstimation/TopDownPoseEstimation
$ curl -OL https://github.com/mbotsu/KeypointDecoder/releases/download/0.0.1/vitpose-b256x192_fp16.mlmodel
$ curl -OL https://github.com/mbotsu/KeypointDecoder/releases/download/0.0.1/yolov7-tiny_fp16.mlmodel
Models | AP |
---|---|
yolov7-tiny_fp16 + vitpose-b256x192_fp16.mlmodel | 0.589 |
yolov7-tiny_fp16 + vitpose_s256x192_wholebody_fp16.mlmodel | 0.579 |
yolov7-tiny_fp16 + vitpose_b256x192_wholebody_fp16.mlmodel | 0.600 |
Models | Size | Keypoint |
---|---|---|
vitpose-b256x192_fp16.mlmodel | 172MB | 17 |
vitpose_s256x192_wholebody_fp16.mlmodel | 46.5MB | 133 |
vitpose_b256x192_wholebody_fp16.mlmodel | 172MB | 133 |
yolov7-tiny_fp16.mlmodel | 12.1MB | - |
COCO-Wholebody 133 When using Keypoint, change the following after introducing the model to the project.
Edit: PoseEstimation.swift
- keypointsNumber
- modelName
- ViTPose to CoreML
- Yolov7 to CoreML
- microsoft/human-pose-estimation.pytorch
- PaddlePaddle/PaddleDetection
- ViTAE-Transformer/ViTPose
- ViTPose to CoreML
- WongKinYiu/yolov7
- Yolov7 to CoreML
- AffineTransform
- Drawing processing