https://s00hyun.github.io/ml&dl/keras-confusion-matrix-doesn't-match/
shuffle=False
valid_datagen = ImageDataGenerator(rescale=1.0 / 255)
validation_generator = valid_datagen.flow_from_directory(
validation_dir,
target_size=(height, width),
batch_size=batch_size,
class_mode="categorical",
shuffle=False, # For evaluation
)
call reset() in ImageDataGenerator
validation_generator.reset()
Y_pred = model.predict_generator(validation_generator, STEP_SIZE_VALID+1)#validation_generator.n // validation_generator.batch_size+1)
classes = validation_generator.classes[validation_generator.index_array]
y_pred = np.argmax(Y_pred, axis=-1) # Returns maximum indices in each row