Blur HR image before downsizing, when available
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@ -90,6 +90,7 @@ class LQGTDataset(data.Dataset):
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img_PIX = img_GT
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# get LQ image
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already_blurred = False
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if self.paths_LQ:
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LQ_path = self.get_lq_path(index)
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resolution = [int(s) for s in self.sizes_LQ[index].split('_')
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@ -113,8 +114,16 @@ class LQGTDataset(data.Dataset):
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img_GT = cv2.cvtColor(img_GT, cv2.COLOR_GRAY2BGR)
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H, W, _ = img_GT.shape
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if self.opt['use_blurring']:
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blur_sig = int(random.randrange(0, 4))
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hqxform = cv2.GaussianBlur(img_GT, (3, 3), blur_sig)
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already_blurred = True
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else:
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hqxform = img_GT
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# using matlab imresize
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img_LQ = util.imresize_np(img_GT, 1 / scale, True)
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img_LQ = util.imresize_np(hqxform, 1 / scale, True)
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if img_LQ.ndim == 2:
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img_LQ = np.expand_dims(img_LQ, axis=2)
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@ -142,8 +151,8 @@ class LQGTDataset(data.Dataset):
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img_LQ, img_GT, img_PIX = util.augment([img_LQ, img_GT, img_PIX], self.opt['use_flip'],
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self.opt['use_rot'])
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if self.opt['use_blurring']:
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blur_sig = int(random.randrange(0, 10))
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if self.opt['use_blurring'] and not already_blurred:
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blur_sig = int(random.randrange(0, 4))
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img_LQ = cv2.GaussianBlur(img_LQ, (3, 3), blur_sig)
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if self.opt['color']: # change color space if necessary
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