# CLICK ON OUTPUT and THEN ctrl C to close
from __future__ import print_function
import sys
import time
import numpy as np
import cv2 as cv
def is_grayscale(my_image):
return len(my_image.shape) < 3
def saturated(sum_value):
# STARTING POINT:
# if sum_value > 255:
if sum_value > 100:
sum_value = 255
# STARTING POINT:
# if sum_value < 0:
if sum_value < 50:
sum_value = 0
return sum_value
def make_mask(my_image):
if is_grayscale(my_image):
height, width = my_image.shape
else:
my_image = cv.cvtColor(my_image, cv.CV_8U)
height, width, n_channels = my_image.shape
result = np.zeros(my_image.shape, my_image.dtype)
for j in range(1, height - 1):
for i in range(1, width - 1):
if is_grayscale(my_image):
sum_value = 5 * my_image[j, i] - my_image[j + 1, i] - my_image[j - 1, i] \
- my_image[j, i + 1] - my_image[j, i - 1]
result[j, i] = saturated(sum_value)
else:
for k in range(0, n_channels):
sum_value = 5 * my_image[j, i, k] - my_image[j + 1, i, k] \
- my_image[j - 1, i, k] - my_image[j, i + 1, k]\
- my_image[j, i - 1, k]
result[j, i, k] = saturated(sum_value)
return result
def main(argv):
filename = 'lena.jpg'
img_codec = cv.IMREAD_COLOR
if argv:
filename = sys.argv[1]
if len(argv) >= 2 and sys.argv[2] == "G":
img_codec = cv.IMREAD_GRAYSCALE
src = cv.imread(cv.samples.findFile(filename), img_codec)
cv.namedWindow("Input", cv.WINDOW_AUTOSIZE)
cv.namedWindow("Output", cv.WINDOW_AUTOSIZE)
cv.imshow("Input", src)
t = round(time.time())
dst0 = make_mask(src)
t = (time.time() - t)
print("Time passed in seconds: %s" % t)
cv.imshow("Output", dst0)
cv.waitKey()
cv.destroyAllWindows()
return 0
if __name__ == "__main__":
main(sys.argv[1:])
