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Runtime error
| import gradio as gr | |
| import os | |
| os.system("git clone https://github.com/megvii-research/NAFNet") | |
| os.system("mv NAFNet/* ./") | |
| os.system("mv *.pth experiments/pretrained_models/") | |
| os.system("python3 setup.py develop --no_cuda_ext --user") | |
| def inference(image_l, image_r): | |
| if not os.path.exists('tmp'): | |
| os.system('mkdir tmp') | |
| image_l.save("tmp/lr_l.png", "PNG") | |
| image_r.save("tmp/lr_r.png", "PNG") | |
| os.system("python basicsr/demo_ssr.py -opt options/test/NAFSSR/NAFSSR-L_4x.yml" | |
| +" --input_l_path ./tmp/lr_l.png --input_r_path ./tmp/lr_r.png" | |
| +" --output_l_path ./tmp/image_l.png --output_r_path ./tmp/image_r.png") | |
| return 'tmp/image_l.png', 'tmp/image_r.png' | |
| title = "NAFNet" | |
| description = "Gradio demo for <b>NAFNet: Nonlinear Activation Free Network for Image Restoration</b>. NAFNet achieves state-of-the-art performance on three tasks: image denoising, image debluring and stereo image super-resolution (SR). See the paper and project page for detailed results below. Here, we provide a demo for stereo image super-resolution (SR). To use it, simply upload your left and right view images, or click the examples to load them. Inference needs some time (>100s) since this demo uses CPU." | |
| article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2204.04676' target='_blank'>Simple Baselines for Image Restoration</a> | <a href='https://arxiv.org/abs/2204.08714' target='_blank'>NAFSSR: Stereo Image Super-Resolution Using NAFNet</a> | <a href='https://github.com/megvii-research/NAFNet' target='_blank'> Github Repo</a></p>" | |
| examples = [['demo/lr_img_l.png', 'demo/lr_img_r.png']] | |
| iface = gr.Interface( | |
| inference, | |
| [gr.inputs.Image(type="pil", label="Input (Left View)"), | |
| gr.inputs.Image(type="pil", label="Input (Right View)")], | |
| [gr.outputs.Image(type="file", label="Output (Left View)"), | |
| gr.outputs.Image(type="file", label="Output (Right View)")], | |
| title=title, | |
| description=description, | |
| article=article, | |
| enable_queue=True, | |
| examples=examples | |
| ) | |
| iface.launch(debug=True,enable_queue=True) |