Easy inference for ViTPose using ONNX
pip install -r requirements.txt
As you can see in 'requirements.txt', it requires only 5 libraries below
- matplotlib
- numpy
- onnxruntime-gpu
- opencv-python
- yacs
git clone https://github.com/Pukei-Pukei/ViTPose-ONNX.git
cd ViTPose-ONNX
pip install -r requirements.txt
Download vitpose-b-multi-coco.onnx and yolov6m.onnx, then put them in ViTPose-ONNX folder
Run the commands below to start inference
python run.py -img <path_to_image>
python run.py -vid <path_to_video>
python run.py -wc <webcam ID or URL>
python run.py -cfg <config path> -vid <path_to_video>
python run.py -cfg configs/custom_config.py -vid dance.mp4 -s
'-s' for save option
--yolov6-path, -yolo PATH : Path to YOLOv6 onnx file
--vitpose-path, -pose PATH : Path to ViTPose onnx file
--image-path, -img PATH : Image path
--video-path, -vid PATH : Videos path
--webcam, -wc PATH : Webcam id or webcam URL
--no-background, -nobg : Background will be black screen
--no-bbox, -nobx : Don't draw bboxes
--no-skeleton, -nosk : Don't draw skeletons
--dynamic-drawing, -dd : Turn on dynamic drawing, keypoint
radius and skeleton width change
dynamically with bbox size
--result-scale, -rs SIZE : Set a coefficient to scale a size
of result, set None for not
processing
--save, -s : Save drawing result
--save-prediction, -sp : Save the predictions(bbox, pose),
Numpy is needed to read the save
file
--conf-thres, -conf THRES : Set confidence threshold for
non-maximum suppression
--iou-thres, -iou THRES : Set IoU threshold for
non-maximum suppression
--max-detection, -max MAX : Set max detection for non-maximum
suppression
--key-conf-thres, -kconf THRES : Set keypoint confidence threshold
--no-pad : Don't use additional padding
--cpu, -cpu : Use cpu instead of gpu
--pose-batch-size, -pbs SIZE : Set pose batch size
--yolo-batch-size, -ybs SIZE : Set yolo batch size,
it works only in video
--config, -cfg : Config path. use config for easy
usage of options. default config
path is 'configs/base_config.py'
| Model | ONNX | Original Weight for PyTorch |
|---|---|---|
| ViTPose-B | GoogleDrive | Onedrive |
| YOLOv6-M | GoogleDrive | Download |
If you want other versions, refer to Tutorial and get your own ONNX