mask.py

# import the necessary packages
import argparse
import cv2
# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", type=str, required=True,
	help="path to input image")
args = vars(ap.parse_args())

image = cv2.imread(args["image"])
cv2.imshow("Image", image)
# convert the image to grayscale and blur it slightly
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (7, 7), 0)

(T, threshInv) = cv2.threshold(blurred, 200, 255,
	cv2.THRESH_BINARY_INV)
cv2.imshow("Threshold Binary Inverse", threshInv)

(T, thresh) = cv2.threshold(blurred, 200, 255, cv2.THRESH_BINARY)
cv2.imshow("Threshold Binary", thresh)
cv2.imwrite("tk5.pbm", thresh)

# visualize only the masked regions in the image
masked = cv2.bitwise_and(image, image, mask=threshInv)
cv2.imshow("Output", masked)
cv2.waitKey(0)