human_segmentation_pphumanseg

PPHumanSeg

This model is ported from PaddleHub using this script from OpenCV.

Note:

• human_segmentation_pphumanseg_2023mar_int8bq.onnx represents the block-quantized version in int8 precision and is generated using block_quantize.py with block_size=64.

Demo

Python

Run the following command to try the demo:

# 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:

# 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

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Results of accuracy evaluation with 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'.

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License

All files in this directory are licensed under Apache 2.0 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