69 lines
1.4 KiB
Markdown
69 lines
1.4 KiB
Markdown
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English | [简体中文](readme_CN.md)
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# Overall process
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## 1.Pytorch->TensorRT
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```shell
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python export.py --weights "torch's path" --onnx2trt --fp16_trt
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```
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## 2.TensorRT inference
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```shell
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python torch2trt/main.py --trt_path "trt's path"
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```
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Image preprocessing -> TensorRT inference -> visualization
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# Time-consuming comparison
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| Backbone |Pytorch(ms) |TensorRT_FP16(ms) |
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|:---:|:----:|:----:|
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|yolov5n-0.5| 7.7 | 2.1 |
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|yolov5n-face| 7.7 | 2.4 |
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|yolov5s-face| 5.6 | 2.2 |
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|yolov5m-face| 9.9 | 3.3 |
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|yolov5l-face| 15.9 | 4.5 |
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> Pytorch=1.10.0+cu102 TensorRT=8.2.0.6 Hardware=rtx2080ti
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```shell
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python torch2trt/speed.py --torch_path "torch's path" --trt_path "trt's path"
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```
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# Visualization
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<table>
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<tr>
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<th>yolov5n-0.5</th>
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<th>yolov5n-face</th>
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</tr>
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<tr>
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<td><img src="./imgs/yolov5n-0.5.jpg" /></td>
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<td><img src="./imgs/yolov5n-face.jpg" /></td>
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</tr>
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</table>
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<table>
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<tr>
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<th>yolov5s-face</th>
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<th>yolov5m-face</th>
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<th>yolov5l-face</th>
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</tr>
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<tr>
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<td><img src="./imgs/yolov5s-face.jpg" /></td>
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<td><img src="./imgs/yolov5m-face.jpg" /></td>
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<td><img src="./imgs/yolov5l-face.jpg" /></td>
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</tr>
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</table>
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