如何理解和使用torchvision.datasets.ImageFolder

torchvision.datasets.ImageFolder 是一个用于加载图像数据集的 PyTorch 数据集类。它会根据文件夹名称来自动为每个图像分配标签，并按照其类别存放在某个预定义目录中。使用 ImageFolder，我们可以方便地对一个图像数据集进行预处理、数据增强和批次化等操作。使用 ImageFolder，我们只需要将数据存储在按其类别分好的文件夹中，然后创建 ImageFolder 对象并传递数据目录的路径即可加载数据集。

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torchvision.datasets.ImageFolder

torchvision.datasets.ImageFolder is a PyTorch dataset class that represents a generic image folder dataset. It assumes that the images are organized in subfolders under a root folder, where each subfolder represents a label/class. For example, the root folder may contain subfolders "cat", "dog", "bird", etc., where each subfolder contains images of the corresponding label/class.

The ImageFolder class takes two arguments: the path to the root folder and an optional transform function. The transform function is applied to each image before it is returned. The class also provides a default transformation that resizes the image to 256x256 and applies a center crop to obtain a 224x224 image.

The ImageFolder dataset can be used as input to a DataLoader to create a batched data loader for training or testing a neural network.

torchvision.datasets.imagefolder

torchvision.datasets.imagefolder 是 PyTorch 中 torchvision 库中的一个数据集类，它可以读取本地图像文件夹中的图像并将其转换为 PyTorch 数据集。这个数据集类期望图像文件夹中的每个子文件夹都对应一个类别，并且每个子文件夹中都只包含属于该类别的图像。