WHENet - ONNX, OpenVINO, TFLite, TensorRT, EdgeTPU, CoreML, TFJS, YOLOv4/YOLOv4-tiny-3L
BSD-3-CLAUSE License
ONNX, OpenVINO, TFLite, TensorRT, EdgeTPU, CoreML, TFJS, YOLOv4/YOLOv4-tiny-3L
PINTO Special Custom Model https://github.com/PINTO0309/DMHead
$ git clone https://github.com/PINTO0309/HeadPoseEstimation-WHENet-yolov4-onnx-openvino
$ cd HeadPoseEstimation-WHENet-yolov4-onnx-openvino
$ wget https://github.com/PINTO0309/HeadPoseEstimation-WHENet-yolov4-onnx-openvino/releases/download/v1.0.3/saved_model_224x224.tar.gz
$ tar -zxvf saved_model_224x224.tar.gz && rm saved_model_224x224.tar.gz
$ wget https://github.com/PINTO0309/HeadPoseEstimation-WHENet-yolov4-onnx-openvino/releases/download/v1.0.4/whenet_1x3x224x224_prepost.onnx
$ mv whenet_1x3x224x224_prepost.onnx saved_model_224x224/
$ python3 demo_video.py
usage: demo_video.py \
[-h] \
[--whenet_mode {onnx,openvino}] \
[--device DEVICE] \
[--height_width HEIGHT_WIDTH]
optional arguments:
-h, --help
show this help message and exit
--whenet_mode {onnx,openvino}
Choose whether to infer WHENet with ONNX or OpenVINO. Default: onnx
--device DEVICE
Path of the mp4 file or device number of the USB camera. Default: 0
--height_width HEIGHT_WIDTH
{H}x{W} Default: 480x640