# Bluring/Smoothing examples Normalized Box Filter, Gaussian Blur, and
# custom Kernel. (also a box filter...)
#
# Jay Summet 2015
#
#Python 2.7, OpenCV 2.4.x
#

import cv2
import numpy as np


#Linux window threading setup code.
cv2.startWindowThread()
cv2.namedWindow("Original")
cv2.namedWindow("Normalized Box 9x9")
cv2.namedWindow("our own 9x9 kernel")
cv2.namedWindow("GaussianBlur")

#Load source / input image as grayscale, also works on color images...
imgIn = cv2.imread("oscar.jpg", cv2.IMREAD_GRAYSCALE)
cv2.imshow("Original", imgIn)


#The blur function does a normalized box filter. 
nBoxFilter = cv2.blur(imgIn, (9,9) )
cv2.imshow("Normalized Box 9x9", nBoxFilter)

#Or, you can create your OWN filter kernel where each value is
# 1.0 / 81 (9x9)

kernel = np.ones( (9,9), np.float32)
kernel = kernel / 81   #try leaving this line out!

custom = cv2.filter2D(imgIn, -1, kernel)
cv2.imshow("our own 9x9 kernel", custom)

#Using the GaussianBlur function...(You could also use getGaussianKernel with the filter2D function...)

#Using sigmal of 1.7, try 2.5 and 0.5 instead...
gBlurImg = cv2.GaussianBlur(imgIn, (9,9), 1.7)
cv2.imshow("GaussianBlur", gBlurImg)

cv2.waitKey(0)