52Hz/CMFNet_deraindrop

1import os2import gradio as gr3from PIL import Image4import torch5 6os.system(7    'wget https://github.com/FanChiMao/CMFNet/releases/download/v0.0/deraindrop_DeRainDrop_CMFNet.pth -P experiments/pretrained_models')8 9 10def inference(img):11    # os.system('mkdir test')12    os.makedirs("./test", exist_ok=True)13    basewidth = 51214    wpercent = (basewidth / float(img.size[0]))15    hsize = int((float(img.size[1]) * float(wpercent)))16    img = img.resize((basewidth, hsize), Image.BILINEAR)17    img.save("test/1.png", "PNG")18    os.system(19        'python main_test_CMFNet.py --input_dir test --weights experiments/pretrained_models/deraindrop_DeRainDrop_CMFNet.pth')20    return 'results/1.png'21 22 23title = "Compound Multi-branch Feature Fusion for Image Restoration (Deraindrop)"24description = "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 deraindrop. To use it, simply upload your image, or click one of the examples to load them. Reference from: https://huggingface.co/akhaliq"25article = "<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_deraindrop' alt='visitor badge'></center>"26 27examples = [['Rain4.png']]28gr.Interface(29    inference,30    [gr.components.Image(type="pil", label="Input")],31    gr.components.Image(type="filepath", label="Output"),32    title=title,33    description=description,34    article=article,35    examples=examples36).launch(debug=True)