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### (5) Inference
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### (5) Inference
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Download the pre-trained weights (for fair academic comparisons only, the optimized model for engineering or common use will be released soon) ```isnet.pth``` from [(Google Drive)](https://drive.google.com/file/d/1KyMpRjewZdyYfxHPYcd-ZbanIXtin0Sn/view?usp=sharing) or [(Baidu Pan 提取码:xbfk)](https://pan.baidu.com/s/1-X2WutiBkWPt-oakuvZ10w?pwd=xbfk) and store ```isnet.pth``` in ```saved_models/IS-Net``` <br>
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Download the pre-trained weights (for fair academic comparisons) ```isnet.pth``` from [(Google Drive)](https://drive.google.com/file/d/1KyMpRjewZdyYfxHPYcd-ZbanIXtin0Sn/view?usp=sharing) or [(Baidu Pan 提取码:xbfk)](https://pan.baidu.com/s/1-X2WutiBkWPt-oakuvZ10w?pwd=xbfk) or the optimized model weights ```isnet-general-use.pth``` (for general use) from [(Google Drive)](https://drive.google.com/file/d/1nV57qKuy--d5u1yvkng9aXW1KS4sOpOi/view?usp=sharing) or [(Baidu Pan 提取码:6jh2)](https://pan.baidu.com/s/111MqmwnUc8Z4Wsq2Pc4bhQ?pwd=6jh2), and store them in ```saved_models/IS-Net``` <br>
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## I. Simple inference code for your own dataset without ground truth:
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## I. Simple inference code for your own dataset without ground truth:
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(a) Open ```\ISNet\inference.py``` and configure your input and output directories
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(a) Open ```\ISNet\inference.py``` and configure your input and output directories
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