I have 200 classes to recognize.
I prepare 600 images for each class and I have 120,000 number of images prepared to train.
I am thinking to use VGGNet-16. Would it be possible to recognize such number of classes using VGGNet-16?
I have 200 classes to recognize.
I prepare 600 images for each class and I have 120,000 number of images prepared to train.
I am thinking to use VGGNet-16. Would it be possible to recognize such number of classes using VGGNet-16?
VGG was mainly developed and benchmarked on the ILSVRC classification task, where the task is to classify images into one of 1000 categories.
So yes, 200 should be perfectly fine.