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# PPHumanSeg
This model is ported from [PaddleHub](https://github.com/PaddlePaddle/PaddleHub) using [this script from OpenCV](https://github.com/opencv/opencv/blob/master/samples/dnn/dnn_model_runner/dnn_conversion/paddlepaddle/paddle_humanseg.py).
**Note**:
- `human_segmentation_pphumanseg_2023mar_int8bq.onnx` represents the block-quantized version in int8 precision and is generated using [block_quantize.py](../../tools/quantize/block_quantize.py) with `block_size=64`.
## Demo
### Python
Run the following command to try the demo:
```shell
# detect on camera input
python demo.py
# detect on an image
python demo.py --input /path/to/image -v
# get help regarding various parameters
python demo.py --help
```
### C++
Install latest OpenCV and CMake >= 3.24.0 to get started with:
```shell
# A typical and default installation path of OpenCV is /usr/local
cmake -B build -D OPENCV_INSTALLATION_PATH=/path/to/opencv/installation .
cmake --build build
# detect on camera input
./build/opencv_zoo_human_segmentation
# detect on an image
./build/opencv_zoo_human_segmentation -i=/path/to/image
# get help messages
./build/opencv_zoo_human_segmentation -h
```
### Example outputs
---
Results of accuracy evaluation with [tools/eval](../../tools/eval).
| Models | Accuracy | mIoU |
| ------------------ | -------------- | ------------- |
| PPHumanSeg | 0.9656 | 0.9164 |
| PPHumanSeg block | 0.9655 | 0.9162 |
| PPHumanSeg quant | 0.7285 | 0.3642 |
\*: 'quant' stands for 'quantized'.
\*\*: 'block' stands for 'blockwise quantized'.
---
## License
All files in this directory are licensed under [Apache 2.0 License](./LICENSE).
## Reference
- https://arxiv.org/abs/1512.03385
- https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/paddlepaddle
- https://github.com/PaddlePaddle/PaddleHub
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