https://github.com/pinto0309/directmhp_yolov7
I just replaced the DirectMHP backend from YOLOv5 to YOLOv7.
https://github.com/pinto0309/directmhp_yolov7
headpose-estimation onnx yolov7
Last synced: 5 months ago
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I just replaced the DirectMHP backend from YOLOv5 to YOLOv7.
- Host: GitHub
- URL: https://github.com/pinto0309/directmhp_yolov7
- Owner: PINTO0309
- License: gpl-3.0
- Created: 2023-06-12T12:56:45.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-06-21T23:52:29.000Z (over 2 years ago)
- Last Synced: 2025-03-31T11:35:39.448Z (6 months ago)
- Topics: headpose-estimation, onnx, yolov7
- Language: Python
- Homepage:
- Size: 252 KB
- Stars: 10
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# DirectMHP_YOLOv7
I just replaced the DirectMHP backend from YOLOv5 to YOLOv7. The reason is that YOLOv5 and YOLOv8 have a problem accepting some input shapes that are multiples of 32.
# Acknowledgments
1. https://github.com/hnuzhy/DirectMHP
2. https://github.com/WongKinYiu/yolov7
- Full ONNX
https://github.com/PINTO0309/DirectMHP_YOLOv7/assets/33194443/263efd13-9b2f-4308-8495-3c0aed531d95
# Data preparation
# Results
## 1. YOLOv7-tiny + CMU-Panoptic 5000 epoch
### RTX3080: 16GB
```
$ python train.py \
--workers 8 \
--device 0 \
--epochs 5000 \
--batch-size 96 \
--data data/cmu_panoptic_coco.yaml \
--img-size 640 640 \
--cfg cfg/training/yolov7-tiny_cmupanoptic_head.yaml \
--weights 'yolov7-tiny.pt' \
--name yolov7_tiny \
--hyp data/hyp.scratch.tiny.yaml \
--mse_conf_thre 0.40 \
--mse_loss_w 0.10
Epoch gpu_mem box obj cls total labels img_size
1199/1199 14.5G 0.01066 0.004235 0 0.01346 409 640
Class Images Labels P R mAP@.5 mAP@.5:.95
all 16216 32738 0.992 0.978 0.994 0.784
left bbox number: 31935 / 32738; MAE: 7.9602, [pitch_err, yaw_err, roll_err]: 8.8929, 7.2529, 7.7348
left backward bbox number: 16067 / 31935; MAE: 8.6401, [pitch_err, yaw_err, roll_err]: 9.3878, 8.3266, 8.2057
left frontal bbox number: 15868 / 31935; MAE: 7.2718, [pitch_err, yaw_err, roll_err]: 8.3917, 6.1657, 7.2581
```
## 2. Single GPU YOLOv7 training
```
# A100 RAM:40GB
# 640x640 training
# --img-size 640 640 -> train_size=640,test_size=640
# --name: save to project/name
python train.py \
--workers 12 \
--device 0 \
--epochs 5000 \
--batch-size 64 \
--data data/cmu_panoptic_coco.yaml \
--img-size 640 640 \
--cfg cfg/training/yolov7_cmupanoptic_head.yaml \
--weights 'yolov7.pt' \
--name yolov7_tiny \
--hyp data/hyp.scratch.tiny.yaml \
--mse_conf_thre 0.40 \
--mse_loss_w 0.10
Epoch gpu_mem box obj cls total labels img_size
596/4999 40.2G 0.01745 0.004293 0 0.03101 257 640
Class Images Labels P R mAP@.5 mAP@.5:.95
all 16216 32738 0.991 0.976 0.994 0.806
left bbox number: 32025 / 32738; MAE: 7.5712, [pitch_error, yaw_error, roll_error]: 8.3896, 6.989, 7.3351
left backward bbox number: 16060 / 32025; MAE: 8.2652, [pitch_err, yaw_err, roll_err]: 8.7852, 8.4, 7.6103
left frontal bbox number: 15965 / 32025; MAE: 6.8732, [pitch_err, yaw_err, roll_err]: 7.9916, 5.5697, 7.0583
```
## 3. ONNX export
```
python export.py \
--weights runs/train/last.pt \
--img-size 480 640 \
--grid
onnxsim runs/train/last.onnx runs/train/last.onnx
onnxsim runs/train/last.onnx runs/train/last.onnx
onnxsim runs/train/last.onnx runs/train/last.onnx
```
## 4. Citation
```
@article{wang2022yolov7,
title={{YOLOv7}: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors},
author={Wang, Chien-Yao and Bochkovskiy, Alexey and Liao, Hong-Yuan Mark},
journal={arXiv preprint arXiv:2207.02696},
year={2022}
}
@article{zhou2023directmhp,
title={DirectMHP: Direct 2D Multi-Person Head Pose Estimation with Full-range Angles},
author={Zhou, Huayi and Jiang, Fei and Lu, Hongtao},
journal={arXiv preprint arXiv:2302.01110},
year={2023}
}
```