(Image from https://pixabay.com/ja/photos/%E5%A5%B3%E3%81%AE%E5%AD%90-%E7%BE%8E%E3%81%97%E3%81%84-%E8%8B%A5%E3%81%84-%E3%83%9B%E3%83%AF%E3%82%A4%E3%83%88-5204299/)

• input shape: (1, 256, 256, 3)

Automatically downloads the onnx and prototxt files on the first run. It is necessary to be connected to the Internet while downloading.

For the sample image,

$ python3 blazepose-fullbody.py 

If you want to specify the input image, put the image path after the --input option.
You can use --savepath option to change the name of the output file to save.

$ python3 blazepose-fullbody.py --input IMAGE_PATH --savepath SAVE_IMAGE_PATH

By adding the --video option, you can input the video.
If you pass 0 as an argument to VIDEO_PATH, you can use the webcam input instead of the video file.

$ python3 blazepose-fullbody.py --video VIDEO_PATH --savepath SAVE_VIDEO_PATH

By adding the --model option, you can specify model type which is selected from "lite", "full", "heavy".
(default is full)

$ python3 blazepose-fullbody.py --model full

MediaPipe

TensorFlow Lite

ONNX opset = 11

pose_detection.onnx.prototxt
pose_landmark_lite.onnx.prototxt
pose_landmark_full.onnx.prototxt
pose_landmark_heavy.onnx.prototxt