56 lines
1.2 KiB
Python
56 lines
1.2 KiB
Python
import numpy as np
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import os
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import cv2
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PATH = './datasets/SR/NTIRE22-StereoSR/Train'
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LR_FOLDER = 'LR_x4'
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HR_FOLDER = 'HR'
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lr_lists = []
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hr_lists = []
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cnt = 0
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for idx in range(1, 801):
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L_name = f'{idx:04}_L.png'
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R_name = f'{idx:04}_R.png'
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LR_L = cv2.imread(os.path.join(PATH, LR_FOLDER, L_name))
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LR_R = cv2.imread(os.path.join(PATH, LR_FOLDER, R_name))
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HR_L = cv2.imread(os.path.join(PATH, HR_FOLDER, L_name))
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HR_R = cv2.imread(os.path.join(PATH, HR_FOLDER, R_name))
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LR = np.concatenate([LR_L, LR_R], axis=-1)
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HR = np.concatenate([HR_L, HR_R], axis=-1)
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lr_lists.append(LR)
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hr_lists.append(HR)
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cnt = cnt + 1
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if cnt % 50 == 0:
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print(f'cnt .. {cnt}, idx: {idx}')
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import pickle
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with open('./datasets/ntire-stereo-sr.train.lr.pickle', 'wb') as f:
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pickle.dump(lr_lists, f)
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with open('./datasets/ntire-stereo-sr.train.hr.pickle', 'wb') as f:
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pickle.dump(hr_lists, f)
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# print(f'... {lr_all_np.shape}, {lr_all_np.dtype}')
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# print(f'... {hr_all_np.shape}, {hr_all_np.dtype}')
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# np.save('./datasets/ntire-stereo-sr.train.lr.npy', lr_all_np)
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# np.save('./datasets/ntire-stereo-sr.train.hr.npy', hr_all_np)
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