来自文件路径和标签的csv的Pytorch数据加载器

import torch
from torch.utils.data import Dataset, DataLoader
import pandas as pd

class CustomDataset(Dataset):
    def __init__(self, csv_file, transform=None):
        self.data = pd.read_csv(csv_file)
        self.transform = transform

    def __len__(self):
        return len(self.data)

    def __getitem__(self, idx):
        image_path = self.data.iloc[idx, 0]  # 文件路径所在列的索引为0
        label = self.data.iloc[idx, 1]  # 标签所在列的索引为1

        # 加载图像数据
        image = self.load_image(image_path)

        if self.transform:
            image = self.transform(image)

        return image, label

    def load_image(self, image_path):
        # 根据文件路径加载图像数据的具体实现
        # 可以使用PIL库或OpenCV库等进行图像加载
        # 示例代码：
        # image = Image.open(image_path)
        # image = np.array(image)

        return image

dataset = CustomDataset(csv_file='path/to/your/csv/file.csv', transform=your_transform)
dataloader = DataLoader(dataset, batch_size=batch_size, shuffle=True)