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split_data.py
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split_data.py
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import os
from shutil import copy, rmtree
import random
def make_dir(file_path):
if os.path.exists(file_path):
# 如果文件夹存在,则先删除原文件夹再创建
rmtree(file_path)
os.makedirs(file_path)
def split_data(input_file_path, output_file_path, split_rate, seed='random'):
if seed == 'fixed':
random.seed(0)
else:
random.seed()
# 获取当前文件路径
cwd = os.getcwd()
input_dataset_path = os.path.join(cwd, input_file_path)
output_dataset_path = os.path.join(cwd, output_file_path)
assert os.path.exists(input_dataset_path), f"path '{input_dataset_path}' does not exist."
# ===================#######################################
# os.listdir() 方法用于返回指定的文件夹包含的文件或文件夹的名字的列表
# os.path.isdir() 方法用于判断某一路径是否为目录
# 先遍历dataset_path获得文件\文件夹名称列表,再判断名称是否为目录
############################################################
dataset_classes = [dataset_class for dataset_class in os.listdir(input_dataset_path) if
os.path.isdir(os.path.join(input_dataset_path, dataset_class))]
# 训练集
train_path = os.path.join(output_dataset_path, 'train')
make_dir(train_path)
for dataset_class in dataset_classes:
make_dir(os.path.join(train_path, dataset_class))
# 验证集
val_path = os.path.join(output_dataset_path, 'val')
make_dir(val_path)
for dataset_class in dataset_classes:
make_dir(os.path.join(val_path, dataset_class))
for dataset_class in dataset_classes:
input_dataset_class_path = os.path.join(input_dataset_path, dataset_class)
images = os.listdir(input_dataset_class_path)
images_num = len(images)
# 随机选取验证集
val_images = random.sample(images, k=int(images_num * split_rate))
for index, image in enumerate(images):
# 获取图像路径
image_path = os.path.join(input_dataset_class_path, image)
if image in val_images:
# 将图像文件copy到验证集对应路径
copy(image_path, os.path.join(val_path, dataset_class))
else:
copy(image_path, os.path.join(train_path, dataset_class))
print(f'[{dataset_class}] is processing: {index + 1}/{images_num}')
print('process finished.')
'''
文件结构示例:
|-- split_data.py
|-- flower_photos
|-- daisy
|-- dandelion
|-- roses
|-- sunflowers
|-- tulips
|-- LICENSE.txt
|-- data
|-- train
|-- daisy
|-- dandelion
|-- roses
|-- sunflowers
|-- tulips
|-- val
|-- daisy
|-- dandelion
|-- roses
|-- sunflowers
|-- tulips
'''
if __name__ == '__main__':
original_data_file_path = 'flower_photos'
spilit_data_file_path = 'data'
split_rate = 0.1
split_data(original_data_file_path, spilit_data_file_path, split_rate)