Add a category to a pretrained model for classification in object detection

Hi all,

I ran the transfer learning on my datasets, achieved n classes on the top of the network, but my purpose is simply expanding the categories of a pretrained model (such as resnet18 which trained on ImageNet and can predict thousand categories) and add a new category. The advantage of this approach is avoiding a situation in which the input is X1 (categorized by the pretrained categories) and my network mistakenly predict one of my trained classes (of the n classes that I trained).

You just need to simply remove the the fc layer and replace it with a Linear(512,n+1) layer. Then the thing you need to do is to use your own dataset to finetune the new model.

This is exactly what I DON’T want to do because I want to leave the 1000 categories as they are and simply add another category and retrain the whole net. So the number of classes would be 1001 after this process.