mirror of https://github.com/ZHKKKe/MODNet.git
31 lines
1.5 KiB
Markdown
31 lines
1.5 KiB
Markdown
## MODNet - ONNX Model
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This ONNX version of MODNet is provided by [@manthan3C273](https://github.com/manthan3C273) from the community.
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Please note that the PyTorch version required for this ONNX export function is higher than the official MODNet code (torch==1.7.1 is recommended).
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You can try **MODNet - Image Matting Demo (ONNX version)** in [this Colab](https://colab.research.google.com/drive/1P3cWtg8fnmu9karZHYDAtmm1vj1rgA-f?usp=sharing).
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You can also download the ONNX version of the official **Image Matting Model** from [this link](https://drive.google.com/file/d/1cgycTQlYXpTh26gB9FTnthE7AvruV8hd/view?usp=sharing).
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To export the ONNX version of MODNet (assuming you are currently in project root directory):
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1. Download the pre-trained **Image Matting Model** from this [link](https://drive.google.com/drive/folders/1umYmlCulvIFNaqPjwod1SayFmSRHziyR?usp=sharing) and put the model into the folder `MODNet/pretrained/`.
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2. Install all dependencies by:
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```
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pip install -r onnx/requirements.txt
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```
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3. Export the ONNX version of MODNet by:
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```shell
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python -m onnx.export_onnx \
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--ckpt-path=pretrained/modnet_photographic_portrait_matting.ckpt \
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--output-path=pretrained/modnet_photographic_portrait_matting.onnx
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```
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4. Inference the ONNX model by:
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```shell
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python -m onnx.inference_onnx \
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--image-path=$FILENAME_OF_INPUT_IMAGE$ \
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--output-path=$FILENAME_OF_OUTPUT_MATTE$ \
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--model-path=pretrained/modnet_photographic_portrait_matting.onnx
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```
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