如何在 PyTorch 中使用 2 张图像作为训练样本？

I just begin learning deep learning and my first homework is to finish an leaves-classification system based on convolutional neural networks.I built a resnet-34 model with the code on github to do it.However,my teacher told me that the basic training unit in his dataset is an image pair.I should use 2 images(photos of the same leaf under different light conditions) as the input,combining two 3-channel images into one 6-channel image,but I don't know how to input 2 images and combine them into 6 channels.How can I do that?Are there any functions?Should I modify the structure of the resnet network?
this is my dataset,you can see every two images are about the same leaf.

您有几个问题需要解决：

1. 你需要一个Dataset with a __getitem__返回 2 个图像（和一个标签）的方法，而不是返回单个图像和一个标签的基本方法。你可能需要定制您自己的数据集.
2. 确保应用于图像的增强以相同的方式应用于每对图像。
3. 您需要修改 ResNet-34 网络以获取 2 张图像（而不是一张）作为输入。参见，例如，这个答案如何做到这一点。
4. 您需要将第一个卷积层更改为具有 6 个输入通道，而不是 3 个。
5. 如果您想使用预先训练的权重，您将无法加载现有的权重state_dictResNet34 因为更改 #3 和 #4 - 您必须第一次手动执行此操作。