Problem
The models provided in torchvision.models
were trained on ImageNet so the size of image is (3, 224, 224)
. However, I have a small dataset (a custom dataset with about 20 thousand images) which is of smaller size.
I am wondering if there is anyway I could still use the pre-trained weights with those smaller images. There are two directions in my mind.
- Modify the first layer and retrain that layer from scratch so that the the sizes of later layers are compatible with pre-trained weights.
- Somehow augment the original images (perhaps some strategic padding) so that the size is made
(224, 224)
.
However, both of them seems to be a long shot when moving into action.
Therefore, does anyone have encountered similar circumstances? Thank you in advance!