#importing some useful packages
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
import cv2
from scipy import ndimage, misc
%matplotlib inline
import math
from skimage import img_as_ubyte

def grayscale(img):
    img=cv2.imread('test_images/solidWhiteRight.jpg')
    img=img_as_ubyte(img)
    """Applies the Grayscale transform
    This will return an image with only one color channel
    but NOTE: to see the returned image as grayscale
    (assuming your grayscaled image is called 'gray')
    you should call plt.imshow(gray, cmap='gray')"""
    #return np.dot(img[...,:3], [0.299, 0.587, 0.114])
    #return cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
    # Or use BGR2GRAY if you read an image with cv2.imread()
    return cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

gr=grayscale(img)

print (gr.dtype)
gr=np.zeros ((...,...,3))
#plt.imshow(gr,cmap = plt.get_cmap('gray'))
plt.imshow(gr)
plt.show()