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| import os | |
| import gradio as gr | |
| from PIL import Image | |
| import torch | |
| os.system( | |
| 'wget https://github.com/FanChiMao/CMFNet/releases/download/v0.0/deblur_GoPro_CMFNet.pth -P experiments/pretrained_models') | |
| def inference(img): | |
| os.system('mkdir test') | |
| basewidth = 512 | |
| wpercent = (basewidth / float(img.size[0])) | |
| hsize = int((float(img.size[1]) * float(wpercent))) | |
| img = img.resize((basewidth, hsize), Image.BILINEAR) | |
| img.save("test/1.png", "PNG") | |
| os.system( | |
| 'python main_test_CMFNet.py --input_dir test --weights experiments/pretrained_models/deblur_GoPro_CMFNet.pth') | |
| return 'results/1.png' | |
| title = "Compound Multi-branch Feature Fusion for Image Restoration (Deblur)" | |
| description = "Gradio demo for CMFNet. CMFNet achieves competitive performance on three tasks: image deblurring, image dehazing and image deraindrop. Here, we provide a demo for image deblur. To use it, simply upload your image, or click one of the examples to load them. Reference from: https://huggingface.co/akhaliq" | |
| article = "<p style='text-align: center'><a href='https://' target='_blank'>Compound Multi-branch Feature Fusion for Real Image Restoration</a> | <a href='https://github.com/FanChiMao/CMFNet' target='_blank'>Github Repo</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=52Hz_CMFNet_deblurring' alt='visitor badge'></center>" | |
| examples = [['images/Blur1.png'], ['images/Blur2.png'], ['images/Blur5.png'],] | |
| gr.Interface( | |
| inference, | |
| [gr.inputs.Image(type="pil", label="Input")], | |
| gr.outputs.Image(type="filepath", label="Output"), | |
| title=title, | |
| description=description, | |
| article=article, | |
| allow_flagging=False, | |
| allow_screenshot=False, | |
| examples=examples | |
| ).launch(debug=True) |