--- a/python/cvutils.py	Thu Jun 01 17:55:40 2017 -0400
+++ b/python/cvutils.py	Wed Jun 14 01:11:56 2017 -0400
@@ -434,17 +434,18 @@
 
     def cameraIntrinsicCalibration(path, checkerBoardSize=[6,7], secondPassSearch=False, display=False):
         ''' Camera calibration searches through all the images (jpg or png) located
-            in _path_ for matches to a checkerboard pattern of size checkboardSize.
-            These images should all be of the same camera with the same resolution.
+        in _path_ for matches to a checkerboard pattern of size checkboardSize.
+        These images should all be of the same camera with the same resolution.
+        
+        For best results, use an asymetric board and ensure that the image has
+        very high contrast, including the background. 
 
-            For best results, use an asymetric board and ensure that the image has
-            very high contrast, including the background. Suitable checkerboard:
-            http://ftp.isr.ist.utl.pt/pub/roswiki/attachments/camera_calibration(2f)Tutorials(2f)StereoCalibration/check-108.png
-
-            The code below is based off of:
-            https://opencv-python-tutroals.readthedocs.org/en/latest/py_tutorials/py_calib3d/py_calibration/py_calibration.html
-            Modified by Paul St-Aubin
-            '''
+        cherckerBoardSize is the number of internal corners (7x10 squares have 6x9 internal corners) 
+        
+        The code below is based off of:
+        https://opencv-python-tutroals.readthedocs.org/en/latest/py_tutorials/py_calib3d/py_calibration/py_calibration.html
+        Modified by Paul St-Aubin
+        '''
         import glob, os
 
         # termination criteria

--- a/scripts/compute-homography.py	Thu Jun 01 17:55:40 2017 -0400
+++ b/scripts/compute-homography.py	Wed Jun 14 01:11:56 2017 -0400
@@ -92,12 +92,12 @@
     if args.undistort:        
         [map1, map2] = cvutils.computeUndistortMaps(videoImg.shape[1], videoImg.shape[0], args.undistortedImageMultiplication, np.loadtxt(args.intrinsicCameraMatrixFilename), args.distortionCoefficients)
         videoImg = cv2.remap(videoImg, map1, map2, interpolation=cv2.INTER_LINEAR)
-    print('Click on {0} points in the video frame'.format(args.nPoints))
+    print('Click on {} points in the video frame'.format(args.nPoints))
     plt.figure()
     plt.imshow(videoImg)
     plt.tight_layout()
     videoPts = np.array(plt.ginput(args.nPoints, timeout=3000))
-    print('Click on {0} points in the world image'.format(args.nPoints))
+    print('Click on {} points in the world image'.format(args.nPoints))
     plt.figure()
     plt.imshow(worldImg)
     plt.tight_layout()