Lucas
100 lines
2.4 KiB
Python
100 lines
2.4 KiB
Python
import os
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from random import random
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from shutil import copyfile, rmtree
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from pathlib import Path
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import multiprocessing
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train_dir = "./data/train/"
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test_dir = "./data/test/"
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val_dir = "./data/val/"
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train = .80
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test = .10
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val = .10
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def add_train_data(file, filename, label):
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dest = train_dir + label + "/" + filename
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if not os.path.exists(os.path.dirname(dest)):
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try:
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os.makedirs(os.path.dirname(dest))
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except Exception as e:
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print(e)
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try:
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Path(dest).absolute().symlink_to(Path(file).absolute())
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except Exception as e:
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print(e)
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print("INVALID FILE")
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os.remove(file)
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def add_val_data(file, filename, label):
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dest = val_dir + label + "/" + filename
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if not os.path.exists(os.path.dirname(dest)):
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try:
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os.makedirs(os.path.dirname(dest))
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except Exception as e:
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print(e)
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Path(dest).absolute().symlink_to(Path(file).absolute())
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def add_test_data(file, filename, label):
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dest = test_dir + label + "/" + filename
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if not os.path.exists(os.path.dirname(dest)):
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try:
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os.makedirs(os.path.dirname(dest))
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except Exception as e:
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print(e)
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Path(dest).absolute().symlink_to(Path(file).absolute())
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def remove_previous():
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if os.path.exists(os.path.dirname(test_dir)):
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rmtree(test_dir)
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if os.path.exists(os.path.dirname(train_dir)):
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rmtree(train_dir)
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if os.path.exists(os.path.dirname(val_dir)):
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rmtree(val_dir)
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files_processed = 0
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def test_split_file(file_root):
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global files_processed
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root = file_root[0]
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file = file_root[1]
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# print(file)
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if file == ".DS_Store":
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return
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c = random()
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if c < train:
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add_train_data(os.path.join(root, file), file, root.split("/")[-1])
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elif c < (train + val):
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add_val_data(os.path.join(root, file), file, root.split("/")[-1])
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else:
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add_test_data(os.path.join(root, file), file, root.split("/")[-1])
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files_processed += 1
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if files_processed % 1000==0:
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print(root.split("/")[-1])
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print(files_processed)
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print(file)
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if __name__ == '__main__':
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remove_previous()
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file_root_list = []
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for root, dirs, files in os.walk("downloads/"):
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for file in files:
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file_root_list.append((root, file))
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pool = multiprocessing.Pool(multiprocessing.cpu_count()*2)
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pool.map(test_split_file, file_root_list)
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