deep-learninginpaintingcomputer-visionimage-inpaintingcolab-notebookhigh-resolutioncolabgenerative-adversarial-networkscnngenerative-adversarial-networkganfourier-transformfourier-convolutionspytorchfourierinpainting-methodsdeep-neural-networksinpainting-algorithm
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20 lines
782 B
20 lines
782 B
import os |
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import random |
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val_files_path = os.path.abspath('.') + '/places_standard_dataset/original/val/' |
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list_of_random_val_files = os.path.abspath('.') + '/places_standard_dataset/original/eval_random_files.txt' |
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val_files = [val_files_path + image for image in os.listdir(val_files_path)] |
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print(f'Sampling 30000 images out of {len(val_files)} images in {val_files_path}' + \ |
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f'and put their paths to {list_of_random_val_files}') |
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print('In our paper we evaluate trained models on these 30k sampled (mask,image) pairs in our paper (check Sup. mat.)') |
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random.shuffle(val_files) |
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val_files_random = val_files[0:30000] |
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with open(list_of_random_val_files, 'w') as fw: |
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for filename in val_files_random: |
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fw.write(filename+'\n') |
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print('...done') |
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