import sys

  import cv2
  import numpy as np
  from matplotlib import pyplot as plt
  
  def ThresholdEverything(img):
  	ret,th1 = cv2.threshold(img,127,255,cv2.THRESH_BINARY)
  	th2 = cv2.adaptiveThreshold(img,255,cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY,11,2)
  	th3 = cv2.adaptiveThreshold(img,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,11,2)
  	titles = ['Original Image', 'Global Thresholding (v = 127)',
  	'Adaptive Mean Thresholding', 'Adaptive Gaussian Thresholding']
  	images = [img, th1, th2, th3]
  	for i in xrange(4):
  		plt.subplot(2,2,i+1),plt.imshow(images[i],'gray')
  		plt.title(titles[i])
  		plt.xticks([]),plt.yticks([])
  	plt.show()

  	cv2.imwrite('Threshold.png', th1)

  	return images
  
  def GlobalThresholding(img):
  	ret,th1 = cv2.threshold(img,127,255,cv2.THRESH_BINARY)
  	plt.plot(), plt.imshow(th1, 'gray')
  	plt.title('Global Thresholding (v = 127)')
  	plt.show()
  	return th1
  
  def AdaptiveMeanThresholding(img):
  	th2 = cv2.adaptiveThreshold(img,255,cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY,11,2)
  	plt.plot(), plt.imshow(th2, 'gray')
  	plt.title('Adaptive Mean Thresholding')
  	plt.show()
  	return th2
  
  def AdaptiveGaussianThresholding(img):
  	th3 = cv2.adaptiveThreshold(img,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,11,2)
  	plt.plot(), plt.imshow(th3, 'gray')
  	plt.title('Adaptive Gaussian Thresholding')
  	plt.show()
  	return th3
  
  def ThresholdChoiceProcessing(img, choice):
  	if choice == '1':
  		img = GlobalThresholding(img)
  		return img
  	elif choice == '2':
  		img = AdaptiveMeanThresholding(img)
  		return img
  	elif choice == '3':
  		img = AdaptiveGaussianThresholding(img)
  		return img
  	elif choice == '4':
  		img = ThresholdEverything(img)
  		return img
  	else:
  		return
  
  
  def ThresholdChoice() :
  	image = None
  	print('\t\tThreshold Menu\n')
  	while (image is None):

  		if sys.version_info >= (3, 0):
  			image = str(input('\tImage to use ? By default couleur.png \n'))
  		else:
  			image = str(raw_input('\tImage to use ? By default couleur.png \n'))

  		if not image:
  			image = 'couleur.png'
  		image = cv2.imread(str(image), 0)
  	img = cv2.medianBlur(image,5)
  	print ('\t1. Global Thresholding\n\t2. Adaptive Mean Thresholding\n\t3. Adaptive Gaussian Thresholding\n\t4. Everything\n')

  	if sys.version_info >= (3, 0):
  		choice = input('\n\tMultiple choices possible\n')
  	else:
  		choice = raw_input('\n\tMultiple choices possible\n')

  	for i in range (0, len(choice)):
  		img = image.copy()
  		img = ThresholdChoiceProcessing(img, choice[i])
  	return