Add doCrop into LQGT
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@ -20,10 +20,11 @@ class LQGTDataset(data.Dataset):
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self.paths_LQ, self.paths_GT = None, None
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self.sizes_LQ, self.sizes_GT = None, None
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self.paths_PIX, self.sizes_PIX = None, None
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self.LQ_env, self.GT_env, self.PIX_env = None, None, None # environments for lmdb
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self.LQ_env, self.GT_env, self.PIX_env = None, None, None # environments for lmdbs
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self.paths_GT, self.sizes_GT = util.get_image_paths(self.data_type, opt['dataroot_GT'])
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self.paths_LQ, self.sizes_LQ = util.get_image_paths(self.data_type, opt['dataroot_LQ'])
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self.doCrop = opt['doCrop']
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if 'dataroot_PIX' in opt.keys():
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self.paths_PIX, self.sizes_PIX = util.get_image_paths(self.data_type, opt['dataroot_PIX'])
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@ -107,6 +108,7 @@ class LQGTDataset(data.Dataset):
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H, W, C = img_LQ.shape
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LQ_size = GT_size // scale
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if self.doCrop:
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# randomly crop
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rnd_h = random.randint(0, max(0, H - LQ_size))
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rnd_w = random.randint(0, max(0, W - LQ_size))
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@ -114,6 +116,10 @@ class LQGTDataset(data.Dataset):
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rnd_h_GT, rnd_w_GT = int(rnd_h * scale), int(rnd_w * scale)
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img_GT = img_GT[rnd_h_GT:rnd_h_GT + GT_size, rnd_w_GT:rnd_w_GT + GT_size, :]
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img_PIX = img_PIX[rnd_h_GT:rnd_h_GT + GT_size, rnd_w_GT:rnd_w_GT + GT_size, :]
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else:
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img_LQ = cv2.resize(img_LQ, (LQ_size, LQ_size), interpolation=cv2.INTER_LINEAR)
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img_GT = cv2.resize(img_GT, (GT_size, GT_size), interpolation=cv2.INTER_LINEAR)
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img_PIX = cv2.resize(img_PIX, (GT_size, GT_size), interpolation=cv2.INTER_LINEAR)
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# augmentation - flip, rotate
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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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