Image_Aug.py

### Image Augmentation by Affine Transformation

from keras.preprocessing.image import ImageDataGenerator
import time, json, os


# dimensions of our images.
img_width, img_height = 320, 320
batch_size = 26

AbsLoc = 'D:\dataset_root_directory'
data_dir = os.path.join(AbsLoc, 'data_inpit_folder')  # input data

# To apply Affine Transformation
datagen = ImageDataGenerator(rotation_range=30,
                             width_shift_range=0.2,
                             height_shift_range=0.2,
                             shear_range=0.2,
                             zoom_range=0.2,
                             fill_mode='reflect',
                             horizontal_flip=True,
                             vertical_flip=True)

generator = datagen.flow_from_directory(
    data_dir,
    target_size=(img_width, img_height),
    batch_size=batch_size,
    class_mode=None,
    shuffle=True,
    save_to_dir=os.path.join(AbsLoc, 'data_output_folder'), save_prefix='data_name', save_format='png')


i = 1
for batch in generator:
    i += 1
    if i > 45:
        break