keras_data_augmentation

keras_data_augmentation.py

# Importing necessary functions
from keras.preprocessing.image import ImageDataGenerator, 
array_to_img, img_to_array, load_img
   
# Initialising the ImageDataGenerator class.
# We will pass in the augmentation parameters in the constructor.
datagen = ImageDataGenerator(
        rotation_range = 40,
        shear_range = 0.2,
        zoom_range = 0.2,
        horizontal_flip = True,
        brightness_range = (0.5, 1.5))
    
# Loading a sample image 
img = load_img('image.jpg') 
# Converting the input sample image to an array
x = img_to_array(img)
# Reshaping the input image
x = x.reshape((1, ) + x.shape) 
   
# Generating and saving 5 augmented samples 
# using the above defined parameters. 
i = 0
for batch in datagen.flow(x, batch_size = 1,
                          save_to_dir ='preview', 
                          save_prefix ='image', save_format ='jpeg'):
    i += 1
    if i > 5:
        break