I'm new to CNNs, starting off with keras. I'm currently using ImageDataGenerator to import my train/validation folders (which each have 2 class subfolders for my binary classification task). Was wondering how can I import my train/validation files without using ImageDataGenerator? I'm aware that ImageDataGenerator is good for accuracy as it does some augmentation, but I want to compare the accuracy to a training set without any augmentations. Essentially I think I need to put all the images into an array, but not sure how to.
Basically I want to know what is the normal way to import training/validation data for images, so I can compare what is the accuracy difference with/without imagedatagen. I know with normal NN tasks it's easy as you can just do pd.read_csv().
I'm currently importing like so:
train_datagen = ImageDataGenerator( rescale=1./255, shear_range=0.2, zoom_range=0.2, horizontal_flip=True) test_datagen = ImageDataGenerator(rescale=1./255) train_generator = train_datagen.flow_from_directory( 'data/train', target_size=(150, 150), batch_size=32, class_mode='binary') validation_generator = test_datagen.flow_from_directory( 'data/validation', target_size=(150, 150), batch_size=32, class_mode='binary')