(image)
return (lMean, lStd, aMean, aStd, bMean, bStd)
Parameters:
	-------
	image: NumPy array
		OpenCV image in L*a*b* color space

	Returns:
	-------
	Tuple of mean and standard deviations for the L*, a*, and b*
	channels, respectively
Parameters:
	-------
	image: NumPy array
		OpenCV image in L*a*b* color space
Parameters : ------- image : NumPy array OpenCV image in L * a * b * color space
def image_stats(image):
	"""
	Parameters:
	-------
	image: NumPy array
		OpenCV image in L*a*b* color space

	Returns:
	-------
	Tuple of mean and standard deviations for the L*, a*, and b*
	channels, respectively
	"""
	# compute the mean and standard deviation of each channel
	(l, a, b) = cv2.split(image)
	(lMean, lStd) = (l.mean(), l.std())
	(aMean, aStd) = (a.mean(), a.std())
	(bMean, bStd) = (b.mean(), b.std())

	# return the color statistics
	return (lMean, lStd, aMean, aStd, bMean, bStd)
def image_stats ( image ) : # compute the mean and standard deviation of each channel ( l , a , b ) = cv2 . split ( image ) ( lMean , lStd ) = ( l . mean ( ) , l . std ( ) ) ( aMean , aStd ) = ( a . mean ( ) , a . std ( ) ) ( bMean , bStd ) = ( b . mean ( ) , b . std ( ) ) # return the color statistics return ( lMean , lStd , aMean , aStd , bMean , bStd )