Question

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')

No correct solution

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