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					@ -57,8 +57,9 @@ image_gt = cv2.imread(str(config.hr_image_path))[:,:,::-1].copy()
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					input_image = torch.tensor(lr_image).type(torch.float32).permute(2,0,1)[None,...].cuda()
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					input_image = torch.tensor(lr_image).type(torch.float32).permute(2,0,1)[None,...].cuda()
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					net_prediction = net_model(input_image).cpu().type(torch.uint8).squeeze().permute(1,2,0).numpy().copy()
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					with torch.inference_mode():
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					lut_prediction = lut_model(input_image).cpu().type(torch.uint8).squeeze().permute(1,2,0).numpy().copy()
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					    net_prediction = net_model(input_image).cpu().type(torch.uint8).squeeze().permute(1,2,0).numpy().copy()
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					    lut_prediction = lut_model(input_image).cpu().type(torch.uint8).squeeze().permute(1,2,0).numpy().copy()
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					image_gt = cv2.putText(image_gt, 'GT', org=(20, 50) , fontFace=cv2.FONT_HERSHEY_SIMPLEX, fontScale=1, color=(255,255,255), thickness=2, lineType= cv2.LINE_AA) 
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					image_gt = cv2.putText(image_gt, 'GT', org=(20, 50) , fontFace=cv2.FONT_HERSHEY_SIMPLEX, fontScale=1, color=(255,255,255), thickness=2, lineType= cv2.LINE_AA) 
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