image_output_1.png
from keras.preprocessing.image import ImageDataGenerator

train_gen = ImageDataGenerator(rotation_range=10, rescale=1.0 / 255, width_shift_range=0.1, height_shift_range=0.1, horizontal_flip=True, vertical_flip=False, zoom_range=0.1, shear_range=0.1, brightness_range=[0.8, 1.2], fill_mode='nearest', validation_split=0.2)
train_data = train_gen.flow_from_directory('/kaggle/input/5-flower-types-classification-dataset/flower_images', target_size=(224, 224), batch_size=32, class_mode='categorical', shuffle=True, subset='training')
test_data = train_gen.flow_from_directory('/kaggle/input/5-flower-types-classification-dataset/flower_images', target_size=(224, 224), batch_size=1, shuffle=False, subset='validation')