transforms.Compose（）

transforms.Compose是PyTorch中用于将多个图像预处理操作组合在一起的函数。它接受一个由多个预处理操作构成的列表作为参数，并按照列表中操作的顺序依次应用这些操作。这样可以方便地将多个预处理步骤整合到一起，以便一次性对图像进行多个操作。

例如，transforms.Compose([transforms.CenterCrop(10), transforms.ToTensor()])将创建一个组合操作，该操作首先将图像进行中心裁剪，然后将其转换为张量。

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transforms.Compose

transforms.Compose is a class in PyTorch's torchvision module that allows the user to group multiple image transformations together into a single transformation pipeline. The transformations are applied in the order they are added to the list of transforms. This is useful when working with large datasets where multiple transformations may need to be applied to each image in a consistent and efficient way.

Example usage:

from torchvision import transforms

transform = transforms.Compose([
    transforms.Resize((256, 256)),
    transforms.RandomCrop(224),
    transforms.ToTensor(),
    transforms.Normalize(mean=[0.485, 0.456, 0.406],
                         std=[0.229, 0.224, 0.225])
])

# Apply the transformation pipeline to an image
image = Image.open('example.jpg')
transformed_image = transform(image)

In this example, the `Compose` class is used to group together four different transformations: `Resize`, `RandomCrop`, `ToTensor`, and `Normalize`. These transformations are then applied to an image in a consistent order to produce a transformed version of the original image.

transforms.compose

transforms.compose 是 Python 中用于组合多个变换操作的函数。它可以将多个变换操作按照一定的顺序组合起来，形成一个新的变换操作。例如，可以将平移、旋转和缩放操作组合起来，形成一个新的变换操作。这个新的变换操作可以应用到图像、视频等数据上，实现各种效果。