Unified handling of InputOutputArrays in Python wrapper generator

This makes arguments of type InputOutputArray required in python unless they
have a default value in C++.

As result following python functions changes signatures in non-trivial way:

* calcOpticalFlowFarneback
* calcOpticalFlowPyrLK
* calibrateCamera
* findContours
* findTransformECC
* floodFill
* kmeans
* PCACompute
* stereoCalibrate

And the following functions become return their modified inputs as a return
value:

* accumulate
* accumulateProduct
* accumulateSquare
* accumulateWeighted
* circle
* completeSymm
* cornerSubPix
* drawChessboardCorners
* drawContours
* drawDataMatrixCodes
* ellipse
* fillConvexPoly
* fillPoly
* filterSpeckles
* grabCut
* insertChannel
* line
* patchNaNs
* polylines
* randn
* randShuffle
* randu
* rectangle
* setIdentity
* updateMotionHistory
* validateDisparity
* watershed

samples/python2/calibrate.py

@@ -27,7 +27,7 @@ if __name__ == '__main__':
         img_mask = img_mask[0]
     except:
         img_mask = '../cpp/left*.jpg'
-    
+
     img_names = glob(img_mask)
     debug_dir = args.get('--debug')
     square_size = float(args.get('--square_size', 1.0))
@@ -46,7 +46,7 @@ if __name__ == '__main__':
         if img is None:
           print "Failed to load", fn
           continue
-        
+
         h, w = img.shape[:2]
         found, corners = cv2.findChessboardCorners(img, pattern_size)
         if found:
@@ -65,7 +65,7 @@ if __name__ == '__main__':
 
         print 'ok'
 
-    rms, camera_matrix, dist_coefs, rvecs, tvecs = cv2.calibrateCamera(obj_points, img_points, (w, h))
+    rms, camera_matrix, dist_coefs, rvecs, tvecs = cv2.calibrateCamera(obj_points, img_points, (w, h), None, None)
     print "RMS:", rms
     print "camera matrix:\n", camera_matrix
     print "distortion coefficients: ", dist_coefs.ravel()

samples/python2/contours.py

@@ -46,7 +46,7 @@ if __name__ == '__main__':
     img = make_image()
     h, w = img.shape[:2]
 
-    contours0, hierarchy = cv2.findContours( img.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+    _, contours0, hierarchy = cv2.findContours( img.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
     contours = [cv2.approxPolyDP(cnt, 3, True) for cnt in contours0]
 
     def update(levels):

samples/python2/digits_video.py

@@ -14,9 +14,9 @@ from common import mosaic
 from digits import *
 
 def main():
-    try: 
+    try:
         src = sys.argv[1]
-    except: 
+    except:
         src = 0
     cap = video.create_capture(src)
 
@@ -35,7 +35,7 @@ def main():
 
         bin = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY_INV, 31, 10)
         bin = cv2.medianBlur(bin, 3)
-        contours, heirs = cv2.findContours( bin.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
+        _, contours, heirs = cv2.findContours( bin.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
         try:
             heirs = heirs[0]
         except:

samples/python2/floodfill.py

@@ -29,7 +29,7 @@ if __name__ == '__main__':
     if img is None:
         print 'Failed to load image file:', fn
         sys.exit(1)
-    
+
     h, w = img.shape[:2]
     mask = np.zeros((h+2, w+2), np.uint8)
     seed_pt = None

samples/python2/kmeans.py

@@ -32,7 +32,7 @@ if __name__ == '__main__':
         points, _ = make_gaussians(cluster_n, img_size)
 
         term_crit = (cv2.TERM_CRITERIA_EPS, 30, 0.1)
-        ret, labels, centers = cv2.kmeans(points, cluster_n, term_crit, 10, 0)
+        ret, labels, centers = cv2.kmeans(points, cluster_n, None, term_crit, 10, 0)
 
         img = np.zeros((img_size, img_size, 3), np.uint8)
         for (x, y), label in zip(np.int32(points), labels.ravel()):

samples/python2/opt_flow.py

@@ -63,7 +63,7 @@ if __name__ == '__main__':
     while True:
         ret, img = cam.read()
         gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-        flow = cv2.calcOpticalFlowFarneback(prevgray, gray, 0.5, 3, 15, 3, 5, 1.2, 0)
+        flow = cv2.calcOpticalFlowFarneback(prevgray, gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
         prevgray = gray
 
         cv2.imshow('flow', draw_flow(gray, flow))

samples/python2/squares.py

@@ -24,7 +24,7 @@ def find_squares(img):
                 bin = cv2.dilate(bin, None)
             else:
                 retval, bin = cv2.threshold(gray, thrs, 255, cv2.THRESH_BINARY)
-            contours, hierarchy = cv2.findContours(bin, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
+            bin, contours, hierarchy = cv2.findContours(bin, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
             for cnt in contours:
                 cnt_len = cv2.arcLength(cnt, True)
                 cnt = cv2.approxPolyDP(cnt, 0.02*cnt_len, True)