title: Class imbalance for image recognition
body: <p>I’ve used InceptionV3 network as base for my model to classify car side(back, front, side, interior, other). 
  Now, one of the classes(interior) has only 350 images and largest(other) has more than 4000. Other three are about the same, with appx 1000 images per class.
  Issue is that, while training, accuracy on training and test data reaches ~75% but when I run the model on all images on the same data it gets classified as ‘other’.</p>
  
  <hr>
  
  <p>I’ve thought that the weighting the classes woth class_weights would help, but same issue happens.</p>
  
  <p>Can someone suggest what might be the reason for this behaviour?</p>