Image augmentation layer

#importing libraries
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from matplotlib import pyplot
import numpy as np
import tensorflow as tf
 
# downloading and saving the image
import requests
DownURL = "https://images.pexels.com/photos/1056251/pexels-photo-1056251.jpeg?crop=entropy&cs=srgb&dl=pexels-ihsan-aditya-1056251.jpg&fit=crop&fm=jpg&h=426&w=640"
img_data = requests.get(DownURL).content
with open('/tmp/impath/cat/cat-small.jpg', 'wb') as handler:
    handler.write(img_data)
 
# setting up data pipeline to read image from disk
image_augmentor = ImageDataGenerator()
data = image_augmentor.flow_from_directory(
    "/tmp/impath",
    target_size=(213, 320),
    batch_size=1,
)
 
# plotting an original image
pyplot.imshow(data.next()[0][0].astype('int'))
pyplot.title("Without Augmentation")
 
# set up horizontal flip
image_augmentor = ImageDataGenerator(horizontal_flip=True)
data = image_augmentor.flow_from_directory(
    "/tmp/impath",
    target_size=(213, 320),
    batch_size=1,
)
pyplot.imshow(data.next()[0][0].astype('int'))
pyplot.title("Augmentation: Horizontal flip")
 
# set up vertical flip
image_augmentor = ImageDataGenerator(vertical_flip=True)
data = image_augmentor.flow_from_directory(
    "/tmp/impath",
    target_size=(213, 320),
    batch_size=1,
)
pyplot.imshow(data.next()[0][0].astype('int'))
pyplot.title("Augmentation: Vertical flip")
 
# random rotation
image_augmentor = ImageDataGenerator(rotation_range=45)
data = image_augmentor.flow_from_directory(
    "/tmp/impath",
    target_size=(213, 320),
    batch_size=1,
)
pyplot.imshow(data.next()[0][0].astype('int'))
pyplot.title("Augmentation: Random rotation")
 
# random zoom
# zooms an image to between 80% to 125%
image_augmentor = ImageDataGenerator(zoom_range=[0.8, 1.25])
data = image_augmentor.flow_from_directory(
    "/tmp/impath",
    target_size=(213, 320),
    batch_size=1,
)
pyplot.imshow(data.next()[0][0].astype('int'))
pyplot.title("Augmentation: Random zoom")
 
#Random Height Shift
image_augmentor = ImageDataGenerator(height_shift_range=0.30)
data = image_augmentor.flow_from_directory(
    "/tmp/impath",
    target_size=(213, 320),
    batch_size=1,
)
pyplot.imshow(data.next()[0][0].astype('int'))
pyplot.title("Augmentation: Height shift")
 
#Random Width Shift
image_augmentor = ImageDataGenerator(width_shift_range=0.30)
data = image_augmentor.flow_from_directory(
    "/tmp/impath",
    target_size=(213, 320),
    batch_size=1,
)
pyplot.imshow(data.next()[0][0].astype('int'))
pyplot.title("Augmentation: Width shift")
 
#Random Height & Width Shift
image_augmentor = ImageDataGenerator(width_shift_range=0.30, height_shift_range=0.30)
data = image_augmentor.flow_from_directory(
    "/tmp/impath",
    target_size=(213, 320),
    batch_size=1,
)
pyplot.imshow(data.next()[0][0].astype('int'))
pyplot.title("Augmentation: Height & width shift")
 
#Tilt and Perspective (Shear)
image_augmentor = ImageDataGenerator(shear_range=45)
data = image_augmentor.flow_from_directory(
    "/tmp/impath",
    target_size=(213, 320),
    batch_size=1,
)
pyplot.imshow(data.next()[0][0].astype('int'))
pyplot.title("Augmentation: Tilt & perspective")
 
#Lighting Transformations
image_augmentor = ImageDataGenerator(brightness_range=(0.3, 1))
data = image_augmentor.flow_from_directory(
    "/tmp/impath",
    target_size=(213, 320),
    batch_size=1,
)
pyplot.imshow(data.next()[0][0].astype('int'))
pyplot.title("Augmentation: Brightness")