def __apply_transformation(image, generator: ImageDataGenerator):
# Turn the read image into colour so that the ImageDataGenerator can apply its transformation. Then return the
# image gray-scaled
coloured_image = cv.cvtColor(
image,
cv.COLOR_GRAY2RGB) # Transform the gray-scaled image into colour
transformed_image = generator.random_transform(
coloured_image) # Transform the image with the ImageDataGenerator
gray_scaled_image = cv.cvtColor(
transformed_image,
cv.COLOR_RGB2GRAY) # Revert the coloured image back to grey
return gray_scaled_image
def imageAugmentation(image):
seed = int(random() * 100000000)
wShift = 5
hShift = 5
# rotation is changing values of image
imgen = ImageDataGenerator(rotation_range=365,
width_shift_range=wShift,
height_shift_range=hShift,
horizontal_flip=True,
vertical_flip=True,
fill_mode='constant',
cval=0)
image = imgen.random_transform(image, seed)
return image
