Prevent grabcut, houghcircles and houghlines python2 demos from running…

Prevent grabcut, houghcircles and houghlines python2 demos from running automatically while browsing demos in the demo list viewer

samples/python2/grabcut.py

@@ -95,32 +95,34 @@ def onmouse(event,x,y,flags,param):
             cv2.circle(img,(x,y),thickness,value['color'],-1)
             cv2.circle(mask,(x,y),thickness,value['val'],-1)
 
-# print documentation
-print __doc__
+if __name__ == '__main__':
 
-# Loading images
-if len(sys.argv) == 2:
+    # print documentation
+    print __doc__
+
+    # Loading images
+    if len(sys.argv) == 2:
         filename = sys.argv[1] # for drawing purposes
-else:
+    else:
         print "No input image given, so loading default image, ../data/lena.jpg \n"
         print "Correct Usage: python grabcut.py <filename> \n"
         filename = '../data/lena.jpg'
 
-img = cv2.imread(filename)
-img2 = img.copy()                               # a copy of original image
-mask = np.zeros(img.shape[:2],dtype = np.uint8) # mask initialized to PR_BG
-output = np.zeros(img.shape,np.uint8)           # output image to be shown
+    img = cv2.imread(filename)
+    img2 = img.copy()                               # a copy of original image
+    mask = np.zeros(img.shape[:2],dtype = np.uint8) # mask initialized to PR_BG
+    output = np.zeros(img.shape,np.uint8)           # output image to be shown
 
-# input and output windows
-cv2.namedWindow('output')
-cv2.namedWindow('input')
-cv2.setMouseCallback('input',onmouse)
-cv2.moveWindow('input',img.shape[1]+10,90)
+    # input and output windows
+    cv2.namedWindow('output')
+    cv2.namedWindow('input')
+    cv2.setMouseCallback('input',onmouse)
+    cv2.moveWindow('input',img.shape[1]+10,90)
 
-print " Instructions: \n"
-print " Draw a rectangle around the object using right mouse button \n"
+    print " Instructions: \n"
+    print " Draw a rectangle around the object using right mouse button \n"
 
-while(1):
+    while(1):
 
         cv2.imshow('output',output)
         cv2.imshow('input',img)
@@ -171,4 +173,4 @@ while(1):
         mask2 = np.where((mask==1) + (mask==3),255,0).astype('uint8')
         output = cv2.bitwise_and(img2,img2,mask=mask2)
 
-cv2.destroyAllWindows()
+    cv2.destroyAllWindows()

samples/python2/houghcircles.py

@@ -10,24 +10,25 @@ import cv2
 import numpy as np
 import sys
 
+if __name__ == '__main__':
 
-print __doc__
-try:
+    print __doc__
+    try:
         fn = sys.argv[1]
-except:
+    except:
         fn = "../data/board.jpg"
 
-src = cv2.imread(fn, 1)
-img = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
-img = cv2.medianBlur(img, 5)
-cimg = src.copy() # numpy function
+    src = cv2.imread(fn, 1)
+    img = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
+    img = cv2.medianBlur(img, 5)
+    cimg = src.copy() # numpy function
 
-circles = cv2.HoughCircles(img, cv2.HOUGH_GRADIENT, 1, 10, np.array([]), 100, 30, 1, 30)
-a, b, c = circles.shape
-for i in range(b):
+    circles = cv2.HoughCircles(img, cv2.HOUGH_GRADIENT, 1, 10, np.array([]), 100, 30, 1, 30)
+    a, b, c = circles.shape
+    for i in range(b):
         cv2.circle(cimg, (circles[0][i][0], circles[0][i][1]), circles[0][i][2], (0, 0, 255), 3, cv2.LINE_AA)
         cv2.circle(cimg, (circles[0][i][0], circles[0][i][1]), 2, (0, 255, 0), 3, cv2.LINE_AA) # draw center of circle
 
-cv2.imshow("source", src)
-cv2.imshow("detected circles", cimg)
-cv2.waitKey(0)
+    cv2.imshow("source", src)
+    cv2.imshow("detected circles", cimg)
+    cv2.waitKey(0)

samples/python2/houghlines.py

@@ -9,22 +9,24 @@ import numpy as np
 import sys
 import math
 
-try:
+if __name__ == '__main__':
+
+    try:
         fn = sys.argv[1]
-except:
+    except:
         fn = "../data/pic1.png"
-print __doc__
-src = cv2.imread(fn)
-dst = cv2.Canny(src, 50, 200)
-cdst = cv2.cvtColor(dst, cv2.COLOR_GRAY2BGR)
+    print __doc__
+    src = cv2.imread(fn)
+    dst = cv2.Canny(src, 50, 200)
+    cdst = cv2.cvtColor(dst, cv2.COLOR_GRAY2BGR)
 
-if True: # HoughLinesP
+    if True: # HoughLinesP
         lines = cv2.HoughLinesP(dst, 1, math.pi/180.0, 40, np.array([]), 50, 10)
         a,b,c = lines.shape
         for i in range(a):
             cv2.line(cdst, (lines[i][0][0], lines[i][0][1]), (lines[i][0][2], lines[i][0][3]), (0, 0, 255), 3, cv2.LINE_AA)
 
-else:    # HoughLines
+    else:    # HoughLines
         lines = cv2.HoughLines(dst, 1, math.pi/180.0, 50, np.array([]), 0, 0)
         a,b,c = lines.shape
         for i in range(a):
@@ -38,6 +40,6 @@ else:    # HoughLines
             cv2.line(cdst, pt1, pt2, (0, 0, 255), 3, cv2.LINE_AA)
 
 
-cv2.imshow("source", src)
-cv2.imshow("detected lines", cdst)
-cv2.waitKey(0)
+    cv2.imshow("source", src)
+    cv2.imshow("detected lines", cdst)
+    cv2.waitKey(0)