如何使用torchvision.datasets.Imagefolder将数据分为训练集和测试集? [英] How to split data into train and test sets using torchvision.datasets.Imagefolder?

问题描述

在我的自定义数据集中，一种图像位于torchvision.datasets.Imagefolder可以处理的一个文件夹中，但是如何将数据集拆分为训练和测试?

In my custom dataset, one kind of image is in one folder which torchvision.datasets.Imagefolder can handle, but how to split the dataset into train and test?

推荐答案

您可以使用 torch.utils.data.Subset ，以根据示例索引将您的ImageFolder数据集分为训练和测试.
例如:

You can use torch.utils.data.Subset to split your ImageFolder dataset into train and test based on indices of the examples.
For example:

orig_set = torchvision.datasets.Imagefolder(...)  # your dataset
n = len(orig_set)  # total number of examples
n_test = int(0.1 * n)  # take ~10% for test
test_set = torch.utils.data.Subset(orig_set, range(n_test))  # take first 10%
train_set = torch.utils.data.Subset(orig_set, range(n_test, n))  # take the rest   

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