note5计算机视觉 卷积模型训练 （四种天气数据集）_气象图片数据集

import torchvision
torchvision.datasets.ImageFolder  # 从分类文件夹中创建dataset数据

os库详解_蕾峰的博客-CSDN博客_os库

分目录的方法

torchvision.datasets.ImageFolder  # 从分类文件夹中创建dataset数据
base_dir = r'./dataa/4weather'
if not os.path.isdir(base_dir):
    os.mkdir(base_dir)
    train_dir = os.path.join(base_dir, 'train')
    test_dir = os.path.join(base_dir, 'test')
    os.mkdir(train_dir)
    os.mkdir(test_dir)
specises = ['cloudy', 'rain', 'shine', 'sunrise']
for train_or_test in ['train', 'test']:
    for spec in specises:
        os.mkdir(os.path.join(base_dir, train_or_test, spec))

创建的结果

 Python的enumerate函数_Python 学习者的博客-CSDN博客_enumerate python

# 把图片分别放入文件夹
image_dir = r'./dataa/dataset2'
for i, img in enumerate(os.listdir(image_dir)):    # enumerate() 遍历列表输出对应的内容和索引
    for spec in specises:
        if spec in img:
            s = os.path.join(image_dir, img)
            if i % 5 == 0:
                d = os.path.join(base_dir, 'train', spec, img)
            else:
                d = os.path.join(base_dir, 'test', spec, img)
            shutil.copy(s, d)
# 查看各文件夹数量
for train_or_test in ['train', 'test']:
    for spec in specises:
        print(train_or_test, spec, len(os.listdir(os.path.join(base_dir, train_or_test, spec))))

torchvision.datasets.ImageFolder使用详解_马鹏森的博客-CSDN博客_datasets.imagefolder