augmentation_tools.py
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	import os
	#import tensorflow
	import numpy as np
	import scipy
	#import cv2

	from scipy import ndimage
	#from matplotlib import pyplot as plt

	from PIL import Image


	def change_contrast(img, level):
	factor = (259 * (level + 255)) / (255 * (259 - level))
	def contrast(c):
	return 128 + factor * (c - 128)
	return img.point(contrast)


	def change_contrast_multi(img, steps):
	result = []
	for n, level in enumerate(steps):
	img_filtered = change_contrast(img, level)
	result.append(img_filtered)
	return result


	def rotatedImages(image_array):
	return [ndimage.rotate(image_array, degree) for degree in range(0,360,90)] ## rotated image, 4 times 90 degree


	def rgb2gray(rgb):
	return np.dot(rgb[...,:3], [0.299, 0.587, 0.114])


	def sobel(image_array):
	image_gray = rgb2gray(image_array).astype('int')
	dx = ndimage.sobel(image_gray, axis=0, mode='constant') # horizontal derivative
	dy = ndimage.sobel(image_gray, axis=1, mode='constant') # vertical derivative
	mag = np.hypot(dx, dy) # magnitude
	return mag