I am trying to start training Imagenet classification training using Tensorflow's inception model. I am a bit confused as I am not sure how to fully train the model.
Wherever I go everyone seems to be using the 1000 classes training list. However, while digging in tensorflows inception model files I found a list of labels containing 21000+ classes.
So I am a bit confused as to whether I should train using the 1000 classes that everyone seems to be using or should I train on the 21000 classes. I have the full imagenet data and I checked the images I downloaded and almost all 21000 classes are there (missing only 200 classes).
I really want to train against the full imagenet dataset as this should give more accuracy but I am not sure what the downfalls will be or how to properly prepare the data and how many steps are appropriate for that.