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https://github.com/pinto0309/headposeestimation-whenet-yolov4-onnx-openvino
WHENet - ONNX, OpenVINO, TFLite, TensorRT, EdgeTPU, CoreML, TFJS, YOLOv4/YOLOv4-tiny-3L
https://github.com/pinto0309/headposeestimation-whenet-yolov4-onnx-openvino
coreml edgetpu onnx tensorflow tensorrt tfjs tflite
Last synced: 24 days ago
JSON representation
WHENet - ONNX, OpenVINO, TFLite, TensorRT, EdgeTPU, CoreML, TFJS, YOLOv4/YOLOv4-tiny-3L
- Host: GitHub
- URL: https://github.com/pinto0309/headposeestimation-whenet-yolov4-onnx-openvino
- Owner: PINTO0309
- License: bsd-3-clause
- Created: 2021-11-15T09:39:13.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2023-02-04T13:38:50.000Z (almost 2 years ago)
- Last Synced: 2024-10-04T11:54:09.787Z (about 1 month ago)
- Topics: coreml, edgetpu, onnx, tensorflow, tensorrt, tfjs, tflite
- Language: Python
- Homepage:
- Size: 149 KB
- Stars: 66
- Watchers: 4
- Forks: 9
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# HeadPoseEstimation-WHENet-yolov4-onnx-openvino
ONNX, OpenVINO, TFLite, TensorRT, EdgeTPU, CoreML, TFJS, YOLOv4/YOLOv4-tiny-3L
- PINTO Special Custom Model
https://github.com/PINTO0309/DMHead
https://user-images.githubusercontent.com/33194443/216770749-be03a5ee-cdc9-4390-aeea-2aa2908cb6a4.mp4
## 1. Usage
```bash
$ 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
```
```bash
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
```
## 2. Reference
1. https://github.com/Ascend-Research/HeadPoseEstimation-WHENet
2. https://github.com/AlexeyAB/darknet
3. https://github.com/jkjung-avt/yolov4_crowdhuman
4. https://github.com/linghu8812/tensorrt_inference/tree/master/Yolov4
5. https://github.com/Tianxiaomo/pytorch-YOLOv4
6. https://github.com/PINTO0309/PINTO_model_zoo
7. https://github.com/PINTO0309/openvino2tensorflow
8. [Exporting WHENet](https://zenn.dev/pinto0309/scraps/1849b6909db13b)
9. [Darknet to ONNX to OpenVINO to TensorFlow to TFLite and Others](https://zenn.dev/pinto0309/scraps/b33883e3951605)
10. [Dual model head pose estimation. Fusion of SOTA models. 360° 6D HeadPose detection. All pre-processing and post-processing are fused together, allowing end-to-end processing in a single inference. 6DRepNet+WHENet](https://github.com/PINTO0309/DMHead)
## 3. Special Custom Model Structure
