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--- |
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license: mit |
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language: |
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- en |
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base_model: |
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- Ultralytics/YOLO11 |
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pipeline_tag: object-detection |
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tags: |
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- Ultralytics |
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- YOLO11 |
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- YOLO11-Seg |
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--- |
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# YOLO11-Seg |
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This version of YOLO11-Seg has been converted to run on the Axera NPU using **w8a16** quantization. |
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This model has been optimized with the following LoRA: |
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Compatible with Pulsar2 version: 3.4 |
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## Convert tools links: |
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For those who are interested in model conversion, you can try to export axmodel through |
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- [The repo of AXera Platform](https://github.com/AXERA-TECH/ax-samples), which you can get the detial of guide |
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- [Pulsar2 Link, How to Convert ONNX to axmodel](https://pulsar2-docs.readthedocs.io/en/latest/pulsar2/introduction.html) |
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## Support Platform |
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- AX650 |
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- [M4N-Dock(爱芯派Pro)](https://wiki.sipeed.com/hardware/zh/maixIV/m4ndock/m4ndock.html) |
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- [M.2 Accelerator card](https://axcl-docs.readthedocs.io/zh-cn/latest/doc_guide_hardware.html) |
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- AX630C |
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- [爱芯派2](https://axera-pi-2-docs-cn.readthedocs.io/zh-cn/latest/index.html) |
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- [Module-LLM](https://docs.m5stack.com/zh_CN/module/Module-LLM) |
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- [LLM630 Compute Kit](https://docs.m5stack.com/zh_CN/core/LLM630%20Compute%20Kit) |
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|Chips|YOLO11x-Seg| |
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|--|--| |
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|AX650| 34 ms | |
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|AX630C| TBD ms | |
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## How to use |
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Download all files from this repository to the device |
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``` |
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root@ax650:~/YOLO11-Pose# tree |
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. |
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|-- ax650 |
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| `-- yolo11x-seg.axmodel |
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|-- ax_yolo11_seg |
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|-- football.jpg |
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`-- yolo11_seg_out.jpg |
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``` |
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### Inference |
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Input image: |
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 |
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#### Inference with AX650 Host, such as M4N-Dock(爱芯派Pro) |
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``` |
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root@ax650:~/samples/AXERA-TECH/YOLO11-Seg# ./ax_yolo11_seg -m ax650/yolo11x-seg.axmodel -i football.jpg |
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-------------------------------------- |
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model file : ax650/yolo11x-seg.axmodel |
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image file : football.jpg |
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img_h, img_w : 640 640 |
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-------------------------------------- |
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Engine creating handle is done. |
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Engine creating context is done. |
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Engine get io info is done. |
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Engine alloc io is done. |
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Engine push input is done. |
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-------------------------------------- |
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input size: 1 |
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name: images [UINT8] [BGR] |
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1 x 640 x 640 x 3 |
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output size: 7 |
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name: /model.23/Concat_1_output_0 [FLOAT32] |
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1 x 80 x 80 x 144 |
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name: /model.23/Concat_2_output_0 [FLOAT32] |
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1 x 40 x 40 x 144 |
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name: /model.23/Concat_3_output_0 [FLOAT32] |
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1 x 20 x 20 x 144 |
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name: /model.23/cv4.0/cv4.0.2/Conv_output_0 [FLOAT32] |
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1 x 80 x 80 x 32 |
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name: /model.23/cv4.1/cv4.1.2/Conv_output_0 [FLOAT32] |
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1 x 40 x 40 x 32 |
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name: /model.23/cv4.2/cv4.2.2/Conv_output_0 [FLOAT32] |
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1 x 20 x 20 x 32 |
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name: output1 [FLOAT32] |
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1 x 32 x 160 x 160 |
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post process cost time:16.90 ms |
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-------------------------------------- |
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Repeat 1 times, avg time 34.59 ms, max_time 34.59 ms, min_time 34.59 ms |
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-------------------------------------- |
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detection num: 9 |
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0: 94%, [ 757, 220, 1127, 1154], person |
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0: 94%, [ 0, 357, 314, 1112], person |
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0: 93%, [1353, 339, 1629, 1037], person |
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0: 91%, [ 494, 476, 659, 1001], person |
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32: 86%, [1231, 877, 1281, 922], sports ball |
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32: 73%, [ 774, 887, 828, 938], sports ball |
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32: 66%, [1012, 882, 1051, 927], sports ball |
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0: 54%, [ 0, 543, 83, 1000], person |
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0: 46%, [1837, 696, 1877, 814], person |
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-------------------------------------- |
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``` |
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Output image: |
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#### Inference with M.2 Accelerator card |
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``` |
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(base) axera@raspberrypi:~/lhj/YOLO11-Seg $ ./axcl_aarch64/axcl_yolo11_seg -m ax650/yolo11x-seg.axmodel -i football.jpg |
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-------------------------------------- |
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model file : ax650/yolo11x-seg.axmodel |
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image file : football.jpg |
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img_h, img_w : 640 640 |
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-------------------------------------- |
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axclrtEngineCreateContextt is done. |
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axclrtEngineGetIOInfo is done. |
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grpid: 0 |
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input size: 1 |
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name: images |
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1 x 640 x 640 x 3 |
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output size: 7 |
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name: /model.23/Concat_1_output_0 |
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1 x 80 x 80 x 144 |
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name: /model.23/Concat_2_output_0 |
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1 x 40 x 40 x 144 |
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name: /model.23/Concat_3_output_0 |
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1 x 20 x 20 x 144 |
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name: /model.23/cv4.0/cv4.0.2/Conv_output_0 |
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1 x 80 x 80 x 32 |
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name: /model.23/cv4.1/cv4.1.2/Conv_output_0 |
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1 x 40 x 40 x 32 |
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name: /model.23/cv4.2/cv4.2.2/Conv_output_0 |
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1 x 20 x 20 x 32 |
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name: output1 |
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1 x 32 x 160 x 160 |
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================================================== |
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Engine push input is done. |
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-------------------------------------- |
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post process cost time:3.47 ms |
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-------------------------------------- |
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Repeat 1 times, avg time 34.89 ms, max_time 34.89 ms, min_time 34.89 ms |
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-------------------------------------- |
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detection num: 9 |
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0: 94%, [ 757, 220, 1127, 1154], person |
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0: 94%, [ 0, 357, 314, 1112], person |
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0: 93%, [1353, 339, 1629, 1037], person |
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0: 91%, [ 494, 476, 659, 1001], person |
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32: 86%, [1231, 877, 1281, 922], sports ball |
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32: 73%, [ 774, 887, 828, 938], sports ball |
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32: 66%, [1012, 882, 1051, 927], sports ball |
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0: 54%, [ 0, 543, 83, 1000], person |
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0: 46%, [1837, 696, 1877, 814], person |
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-------------------------------------- |
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``` |
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Output image: |
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