Hi!
RestNet, DenseNet and other model in torchvison.model are all designed for image of size 224x224?
How can I use it to other image tasks with image size not 224x224?.
These days I’m trying to use torchvison.models for cifar10 classificaion task, and I already try some methods to overcome the image size mismatch problem：

resize the image size to 224x224. but i found that it will cost more times for training than using a image size of 32x32.
In ResNet model, Ichange the avgpool to adaptiveavgpool, like that model.avgpool = t.nn.AdaptiveAvgPool2d(1). But I found that it does’t obtain a good performance, the best validation acc is just 84%. I found somebody can reach 92%. So whats’s the problem with this method?

So, I want to know other better methods to deal with the problem! I’ll be really grateful for any advice or help.