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Create app.py
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app.py
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import os
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import shutil
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import torch
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from natsort import natsorted
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from glob import glob
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import cv2
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import numpy as np
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import gradio as gr
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from PIL import Image
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os.system("pip install einops")
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os.system("git clone https://github.com/swz30/Restormer.git")
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os.chdir('Restormer')
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# Download pretrained models
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os.system("wget https://github.com/swz30/Restormer/releases/download/v1.0/real_denoising.pth -P Denoising/pretrained_models")
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os.system("wget https://github.com/swz30/Restormer/releases/download/v1.0/single_image_defocus_deblurring.pth -P Defocus_Deblurring/pretrained_models")
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os.system("wget https://github.com/swz30/Restormer/releases/download/v1.0/motion_deblurring.pth -P Motion_Deblurring/pretrained_models")
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os.system("wget https://github.com/swz30/Restormer/releases/download/v1.0/deraining.pth -P Deraining/pretrained_models")
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# Download sample images
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os.system("wget https://github.com/swz30/Restormer/releases/download/v1.0/sample_images.zip -P demo")
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shutil.unpack_archive('demo/sample_images.zip', 'demo/')
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os.remove('demo/sample_images.zip')
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examples = [['demo/sample_images/Real_Denoising/degraded/117355.png', 'Denoising'],
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['demo/sample_images/Single_Image_Defocus_Deblurring/degraded/engagement.jpg', 'Defocus Deblurring'],
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['demo/sample_images/Motion_Deblurring/degraded/GoPro-GOPR0854_11_00-000090-input.jpg','Motion Deblurring'],
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['demo/sample_images/Deraining/degraded/Rain100H-77-input.jpg','Deraining']]
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title = "Restormer"
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description = """
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Gradio demo for Restormer: Efficient Transformer for High-Resolution Image Restoration, CVPR 2022--ORAL. <a href='https://arxiv.org/abs/2111.09881'>[Paper]</a><a href='https://github.com/swz30/Restormer'>[Github Code]</a>\n
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With Restormer, you can perform: (1) Image Denoising, (2) Defocus Deblurring, (3) Motion Deblurring, and (4) Image Deraining.
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To use it, simply upload your own image, or click one of the examples provided below.
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"""
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article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2111.09881'>Restormer: Efficient Transformer for High-Resolution Image Restoration </a> | <a href='https://github.com/swz30/Restormer'>Github Repo</a></p>"
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def inference(img,task):
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os.system('mkdir temp')
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max_res = 904
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width, height = img.size
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if max(width,height) > max_res:
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scale = min(width,height)/max(width,height)
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if width > max_res:
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width = max_res
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height = int(scale*max_res)
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if height > max_res:
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height = max_res
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width = int(scale*max_res)
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img = img.resize((width,height), Image.ANTIALIAS)
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img.save("temp/image.jpg", "JPEG")
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if task == 'Motion Deblurring':
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task = 'Motion_Deblurring'
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os.system("python demo.py --task 'Motion_Deblurring' --input_dir './temp/image.jpg' --result_dir './temp/'")
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if task == 'Defocus Deblurring':
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task = 'Single_Image_Defocus_Deblurring'
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os.system("python demo.py --task 'Single_Image_Defocus_Deblurring' --input_dir './temp/image.jpg' --result_dir './temp/'")
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if task == 'Denoising':
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task = 'Real_Denoising'
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os.system("python demo.py --task 'Real_Denoising' --input_dir './temp/image.jpg' --result_dir './temp/'")
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if task == 'Deraining':
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os.system("python demo.py --task 'Deraining' --input_dir './temp/image.jpg' --result_dir './temp/'")
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restored = f'temp/{task}/image.png'
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return restored
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gr.Interface(
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inference,
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[
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gr.inputs.Image(type="pil", label="Input"),
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gr.inputs.Radio(["Denoising", "Defocus Deblurring", "Motion Deblurring", "Deraining"], default="Denoising", label='task type')
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],
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gr.outputs.Image(type="file", label="Output"),
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title=title,
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description=description,
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article=article,
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examples=examples,
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allow_flagging=False,
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).launch(debug=True,enable_queue=True)
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