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| import gradio as gr | |
| import torch | |
| import torch.nn as nn | |
| import torchvision | |
| import torch.backends.cudnn as cudnn | |
| import torch.optim | |
| import os | |
| import sys | |
| import argparse | |
| import time | |
| import dataloader | |
| import model | |
| import numpy as np | |
| from torchvision import transforms | |
| from PIL import Image | |
| import glob | |
| import time | |
| def lowlight(image_path): | |
| os.environ['CUDA_VISIBLE_DEVICES']='' | |
| data_lowlight = Image.open(image_path) | |
| data_lowlight = (np.asarray(data_lowlight)/255.0) | |
| data_lowlight = torch.from_numpy(data_lowlight).float() | |
| data_lowlight = data_lowlight.permute(2,0,1) | |
| data_lowlight = data_lowlight.cpu().unsqueeze(0) | |
| DCE_net = model.enhance_net_nopool().cpu() | |
| DCE_net.load_state_dict(torch.load('Epoch99.pth')) | |
| start = time.time() | |
| _,enhanced_image,_ = DCE_net(data_lowlight) | |
| end_time = (time.time() - start) | |
| print(end_time) | |
| image_path = image_path.replace('test_data','result') | |
| result_path = image_path | |
| if not os.path.exists(image_path.replace('/'+image_path.split("/")[-1],'')): | |
| os.makedirs(image_path.replace('/'+image_path.split("/")[-1],'')) | |
| torchvision.utils.save_image(enhanced_image, result_path) | |
| if __name__ == '__main__': | |
| # test_images | |
| with torch.no_grad(): | |
| filePath = 'data/test_data/' | |
| file_list = os.listdir(filePath) | |
| for file_name in file_list: | |
| test_list = glob.glob(filePath+file_name+"/*") | |
| for image in test_list: | |
| # image = image | |
| print(image) | |
| lowlight(image) | |
| 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 = [['data/test_data//01.jpg'], ['data/test_data//02.jpg'], ['data/test_data//03.jpg'],] | |
| gr.Interface( | |
| inference, | |
| [gr.inputs.Image(type="pil", label="Input")], | |
| gr.outputs.Image(type="file", label="Output"), | |
| title=title, | |
| description=description, | |
| article=article, | |
| allow_flagging=False, | |
| allow_screenshot=False, | |
| examples=examples | |
| ).launch(debug=True) | |