| ## MODNet - ONNX Model | |
| This ONNX version of MODNet is provided by [@manthan3C273](https://github.com/manthan3C273) from the community. | |
| 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). | |
| You can try **MODNet - Image Matting Demo (ONNX version)** in [this Colab](https://colab.research.google.com/drive/1P3cWtg8fnmu9karZHYDAtmm1vj1rgA-f?usp=sharing). | |
| 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). | |
| To export the ONNX version of MODNet (assuming you are currently in project root directory): | |
| 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/`. | |
| 2. Install all dependencies by: | |
| ``` | |
| pip install -r onnx/requirements.txt | |
| ``` | |
| 3. Export the ONNX version of MODNet by: | |
| ```shell | |
| python -m onnx.export_onnx \ | |
| --ckpt-path=pretrained/modnet_photographic_portrait_matting.ckpt \ | |
| --output-path=pretrained/modnet_photographic_portrait_matting.onnx | |
| ``` | |
| 4. Inference the ONNX model by: | |
| ```shell | |
| python -m onnx.inference_onnx \ | |
| --image-path=$FILENAME_OF_INPUT_IMAGE$ \ | |
| --output-path=$FILENAME_OF_OUTPUT_MATTE$ \ | |
| --model-path=pretrained/modnet_photographic_portrait_matting.onnx | |
| ``` | |