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| import os | |
| import sys | |
| import gradio as gr | |
| from PIL import Image | |
| ## environment settup | |
| os.system("git clone https://github.com/codeslake/RefVSR.git") | |
| os.chdir("RefVSR") | |
| os.system("./install/install_cudnn113.sh") | |
| os.system("wget https://www.dropbox.com/s/xv6inxwy0so4ni0/LR.png -O LR.png") | |
| os.system("wget https://www.dropbox.com/s/abydd1oczs1163l/Ref.png -O Ref.png") | |
| os.mkdir("ckpt") | |
| os.system("wget -P ckpt https://huggingface.co/codeslake/RefVSR/resolve/main/RefVSR_small_MFID_8K.pytorch") | |
| os.system("wget -P ckpt https://huggingface.co/codeslake/RefVSR/resolve/main/SPyNet.pytorch") | |
| sys.path.append("RefVSR") | |
| ## RefVSR | |
| LR_path = "test/test/HR/UW/0000" | |
| Ref_path = "test/test/HR/W/0000" | |
| Ref_path_T = "test/test/HR/W/0000" | |
| os.makedirs(LR_path) | |
| os.makedirs(Ref_path) | |
| os.makedirs('result') | |
| def resize(width,img): | |
| basewidth = width | |
| wpercent = (basewidth/float(img.size[0])) | |
| hsize = int((float(img.size[1])*float(wpercent))) | |
| img = img.resize((basewidth,hsize), Image.ANTIALIAS) | |
| return img | |
| def inference(LR, Ref): | |
| #LR = resize(256, LR) | |
| #Ref = resize(256, Ref) | |
| LR.save(os.path.join(LR_path, '0000.png')) | |
| Ref.save(os.path.join(Ref_path, '0000.png')) | |
| Ref.save(os.path.join(Ref_path_T, '0000.png')) | |
| # os.system("python inference_realbasicvsr.py configs/realbasicvsr_x4.py RealBasicVSR_x4.pth test/ results/demo_000") | |
| os.system("python -B run.py \ | |
| --mode amp_RefVSR_small_MFID_8K \ | |
| --config config_RefVSR_small_MFID_8K \ | |
| --data RealMCVSR \ | |
| --ckpt_abs_name ckpt/RefVSR_small_MFID_8K.pytorch \ | |
| --data_offset ./test \ | |
| --output_offset ./result \ | |
| --qualitative_only \ | |
| --cpu \ | |
| --is_gradio") | |
| return "result/0000.png" | |
| title="RefVSR" | |
| #description="Demo application for Reference-based Video Super-Resolution (RefVSR).\nInstruction: Upload a low-resolution frame and a reference frame to 'LR' and 'Ref' input windows, respectively.\nNote 1: This demo only supports RefVSR for a single LR and Ref frame due to computational complexity. Hence, the model might not take advantage of temporal frames. \nNote 2: The model is our small 8K model trained with the proposed two-stage training strategy. \nNote 3: The spatial size of input LR and Ref frames is 1920x1080 (HD), in the PNG format." | |
| description="Demo application for Reference-based Video Super-Resolution (RefVSR).Upload a low-resolution frame and a reference frame to 'LR' and 'Ref' input windows, respectively." | |
| article = "<p style='text-align: center'>This demo only supports RefVSR for a single LR and Ref frame due to computational complexity. Hence, the model might not take advantage of temporal frames.</p><p style='text-align: center'>The model is our small 8K model trained with the proposed two-stage training strategy.</p><p style='text-align: center'>The spatial size of input LR and Ref frames is 1920x1080 (HD), in the PNG format.</p><p style='text-align: center'><a href='https://junyonglee.me/projects/RefVSR' target='_blank'>Project</a> | <a href='https://arxiv.org/abs/2203.14537' target='_blank'>arXiv</a> | <a href='https://github.com/codeslake/RefVSR' target='_blank'>Github</a></p>" | |
| examples=[[['LR.png'], ['Ref.png']]] | |
| gr.Interface(inference,[gr.inputs.Image(type="pil"), gr.inputs.Image(type="pil")],gr.outputs.Image(type="file"),title=title,description=description,article=article,theme ="peach",examples=examples).launch(enable_queue=True) | |