Initial clean project import

2026-06-19 18:41:41 +08:00
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+## 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
+    ```