# Did I do the right thing in my CNN Keras (class imbalance - augmentation)

To implement my Binary CNN in keras, I had a dataset of ~~35000 images but only 700 is from one class and all the others are from the other class, so what I did: I get the 700 unique images from class 1 and get 700 images randomly from class 0 totalizing 1400 samples (700 each class). After I perform this augmentation in my set:

datagen = ImageDataGenerator(
rotation_range=30,
zoom_range=0.15,
featurewise_std_normalization=True,
width_shift_range=0.2,
height_shift_range=0.2,
shear_range=0.15,
horizontal_flip=True,
fill_mode="nearest")


I did it right? or there's a better way to do?