Hi
Is it possible to get a pretrained model that is based on the selective classes of the ImageNet?
I have computed the similarity between each Imagenet class and my dataset using cvpr18-inaturalist-transfer/DomainSimilarityDemo.ipynb at master · richardaecn/cvpr18-inaturalist-transfer · GitHub
and got the subset of Imagenet Classes which are most similar to my dataset. Now I want to use the pretrained features only from these most similar classes.
Earlier, I was using the pretrained model as follows:
def get_resnet34(num_classes=20, **_):
    model_name = 'resnet34'
    model = pretrainedmodels.__dict__[model_name](num_classes=1000, pretrained='imagenet')
    conv1 = model.conv1

May I know how can i get the pretrained features from the selective classes of Imagenet.
I don’t have any clue to pursue this further.
Looking for help.
Thank you