Merge branch 4.x

doc/py_tutorials/py_feature2d/py_brief/py_brief.markdown

@@ -63,7 +63,7 @@ import numpy as np
 import cv2 as cv
 from matplotlib import pyplot as plt
 
-img = cv.imread('simple.jpg',0)
+img = cv.imread('simple.jpg', cv.IMREAD_GRAYSCALE)
 
 # Initiate FAST detector
 star = cv.xfeatures2d.StarDetector_create()

doc/py_tutorials/py_feature2d/py_fast/py_fast.markdown

@@ -98,7 +98,7 @@ import numpy as np
 import cv2 as cv
 from matplotlib import pyplot as plt
 
-img = cv.imread('blox.jpg',0) # `<opencv_root>/samples/data/blox.jpg`
+img = cv.imread('blox.jpg', cv.IMREAD_GRAYSCALE) # `<opencv_root>/samples/data/blox.jpg`
 
 # Initiate FAST object with default values
 fast = cv.FastFeatureDetector_create()

doc/py_tutorials/py_feature2d/py_feature_homography/py_feature_homography.markdown

@@ -40,8 +40,8 @@ from matplotlib import pyplot as plt
 
 MIN_MATCH_COUNT = 10
 
-img1 = cv.imread('box.png',0)          # queryImage
-img2 = cv.imread('box_in_scene.png',0) # trainImage
+img1 = cv.imread('box.png', cv.IMREAD_GRAYSCALE)          # queryImage
+img2 = cv.imread('box_in_scene.png', cv.IMREAD_GRAYSCALE) # trainImage
 
 # Initiate SIFT detector
 sift = cv.SIFT_create()

doc/py_tutorials/py_feature2d/py_orb/py_orb.markdown

@@ -67,7 +67,7 @@ import numpy as np
 import cv2 as cv
 from matplotlib import pyplot as plt
 
-img = cv.imread('simple.jpg',0)
+img = cv.imread('simple.jpg', cv.IMREAD_GRAYSCALE)
 
 # Initiate ORB detector
 orb = cv.ORB_create()

doc/py_tutorials/py_feature2d/py_surf_intro/py_surf_intro.markdown

@@ -76,7 +76,7 @@ and descriptors.
 First we will see a simple demo on how to find SURF keypoints and descriptors and draw it. All
 examples are shown in Python terminal since it is just same as SIFT only.
 @code{.py}
->>> img = cv.imread('fly.png',0)
+>>> img = cv.imread('fly.png', cv.IMREAD_GRAYSCALE)
 
 # Create SURF object. You can specify params here or later.
 # Here I set Hessian Threshold to 400