Image transformation operations, including the ones provided by ImageDataGenerator class from keras, modify numpy arrays based on the user description. The modification of these arrays may yield unintended results as the data may be modified from interpolation. If the user is not careful in spotting these issues the results may turn out to be meaningless. This is especially true when working with categorical labels where each label value needs to be conserved throughout the training and prediction process.
This video walks you through this issue and also offers suggestions on how to handle data augmentation for categorical labels. Custom code for augmentation can be downloaded here: https://github.com/bnsreenu/python_fo...
Watch video 150 - Warning about keras' data augmentation when working with categorical labels online without registration, duration hours minute second in high quality. This video was added by user DigitalSreeni 18 August 2020, don't forget to share it with your friends and acquaintances, it has been viewed on our site 3,065 once and liked it 89 people.