updating python tutorials + providing necessary data

doc/py_tutorials/py_core/py_basic_ops/py_basic_ops.markdown

@@ -173,7 +173,7 @@ from matplotlib import pyplot as plt
 
 BLUE = [255,0,0]
 
-img1 = cv2.imread('opencv_logo.png')
+img1 = cv2.imread('opencv-logo.png')
 
 replicate = cv2.copyMakeBorder(img1,10,10,10,10,cv2.BORDER_REPLICATE)
 reflect = cv2.copyMakeBorder(img1,10,10,10,10,cv2.BORDER_REFLECT)

doc/py_tutorials/py_core/py_image_arithmetics/py_image_arithmetics.markdown

@@ -51,7 +51,7 @@ is given 0.3. cv2.addWeighted() applies following equation on the image.
 Here \f$\gamma\f$ is taken as zero.
 @code{.py}
 img1 = cv2.imread('ml.png')
-img2 = cv2.imread('opencv_logo.jpg')
+img2 = cv2.imread('opencv-logo.png')
 
 dst = cv2.addWeighted(img1,0.7,img2,0.3,0)
 
@@ -77,7 +77,7 @@ bitwise operations as below:
 @code{.py}
 # Load two images
 img1 = cv2.imread('messi5.jpg')
-img2 = cv2.imread('opencv_logo.png')
+img2 = cv2.imread('opencv-logo.png')
 
 # I want to put logo on top-left corner, So I create a ROI
 rows,cols,channels = img2.shape

doc/py_tutorials/py_imgproc/py_filtering/py_filtering.markdown

@@ -69,7 +69,7 @@ import cv2
 import numpy as np
 from matplotlib import pyplot as plt
 
-img = cv2.imread('opencv_logo.png')
+img = cv2.imread('opencv-logo-white.png')
 
 blur = cv2.blur(img,(5,5))
 

doc/py_tutorials/py_imgproc/py_geometric_transformations/py_geometric_transformations.markdown

@@ -135,7 +135,7 @@ matrix.
 
 See the code below:
 @code{.py}
-img = cv2.imread('sudokusmall.png')
+img = cv2.imread('sudoku.png')
 rows,cols,ch = img.shape
 
 pts1 = np.float32([[56,65],[368,52],[28,387],[389,390]])

doc/py_tutorials/py_imgproc/py_houghcircles/py_houghcircles.markdown

@@ -23,7 +23,7 @@ explained in the documentation. So we directly go to the code.
 import cv2
 import numpy as np
 
-img = cv2.imread('opencv_logo.png',0)
+img = cv2.imread('opencv-logo-white.png',0)
 img = cv2.medianBlur(img,5)
 cimg = cv2.cvtColor(img,cv2.COLOR_GRAY2BGR)
 

doc/py_tutorials/py_imgproc/py_houghlines/py_houghlines.markdown

@@ -73,7 +73,7 @@ represents the minimum length of line that should be detected.
 import cv2
 import numpy as np
 
-img = cv2.imread('dave.jpg')
+img = cv2.imread('sudoku.png')
 gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
 edges = cv2.Canny(gray,50,150,apertureSize = 3)
 
@@ -121,7 +121,7 @@ the parameters of lines, and you had to find all the points. Here, everything is
 import cv2
 import numpy as np
 
-img = cv2.imread('dave.jpg')
+img = cv2.imread('sudoku.png')
 gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
 edges = cv2.Canny(gray,50,150,apertureSize = 3)
 lines = cv2.HoughLinesP(edges,1,np.pi/180,100,minLineLength=100,maxLineGap=10)

doc/py_tutorials/py_imgproc/py_thresholding/py_thresholding.markdown

@@ -87,7 +87,7 @@ import cv2
 import numpy as np
 from matplotlib import pyplot as plt
 
-img = cv2.imread('dave.jpg',0)
+img = cv2.imread('sudoku.png',0)
 img = cv2.medianBlur(img,5)
 
 ret,th1 = cv2.threshold(img,127,255,cv2.THRESH_BINARY)

samples/cpp/peopledetect.cpp

@@ -16,7 +16,7 @@ const char* keys =
     "{ help h      |                     | print help message }"
     "{ image i     |                     | specify input image}"
     "{ camera c    |                     | enable camera capturing }"
-    "{ video v     | ../data/768x576.avi | use video as input }"
+    "{ video v     | ../data/vtest.avi   | use video as input }"
     "{ directory d |                     | images directory}"
 };
 
@@ -79,7 +79,7 @@ int main(int argc, char** argv)
     namedWindow("people detector", 1);
 
     string pattern_glob = "";
-    string video_filename = "../data/768x576.avi";
+    string video_filename = "../data/vtest.avi";
     int camera_id = -1;
     if (parser.has("directory"))
     {

samples/gpu/bgfg_segm.cpp

@@ -23,10 +23,10 @@ enum Method
 int main(int argc, const char** argv)
 {
     cv::CommandLineParser cmd(argc, argv,
-        "{ c camera |             | use camera }"
-        "{ f file   | ../data/768x576.avi | input video file }"
-        "{ m method | mog         | method (mog, mog2, gmg, fgd) }"
-        "{ h help   |             | print help message }");
+        "{ c camera |                    | use camera }"
+        "{ f file   | ../data/vtest.avi  | input video file }"
+        "{ m method | mog                | method (mog, mog2, gmg, fgd) }"
+        "{ h help   |                    | print help message }");
 
     if (cmd.has("help") || !cmd.check())
     {

samples/gpu/performance/tests.cpp

@@ -1191,10 +1191,10 @@ TEST(GoodFeaturesToTrack)
 
 TEST(MOG)
 {
-    const std::string inputFile = abspath("../data/768x576.avi");
+    const std::string inputFile = abspath("../data/vtest.avi");
 
     cv::VideoCapture cap(inputFile);
-    if (!cap.isOpened()) throw runtime_error("can't open ../data/768x576.avi");
+    if (!cap.isOpened()) throw runtime_error("can't open ../data/vtest.avi");
 
     cv::Mat frame;
     cap >> frame;

samples/tapi/bgfg_segm.cpp

@@ -17,11 +17,11 @@ using namespace cv;
 int main(int argc, const char** argv)
 {
     CommandLineParser cmd(argc, argv,
-        "{ c camera   |             | use camera }"
-        "{ f file     | ../data/768x576.avi | input video file }"
-        "{ t type     | mog2        | method's type (knn, mog2) }"
-        "{ h help     |             | print help message }"
-        "{ m cpu_mode | false       | press 'm' to switch OpenCL<->CPU}");
+        "{ c camera   |                    | use camera }"
+        "{ f file     | ../data/vtest.avi  | input video file }"
+        "{ t type     | mog2               | method's type (knn, mog2) }"
+        "{ h help     |                    | print help message }"
+        "{ m cpu_mode | false              | press 'm' to switch OpenCL<->CPU}");
 
     if (cmd.has("help"))
     {

samples/tapi/hog.cpp

@@ -71,7 +71,7 @@ int main(int argc, char** argv)
         "{ h help      |                | print help message }"
         "{ i input     |                | specify input image}"
         "{ c camera    | -1             | enable camera capturing }"
-        "{ v video     | ../data/768x576.avi | use video as input }"
+        "{ v video     | ../data/vtest.avi | use video as input }"
         "{ g gray      |                | convert image to gray one or not}"
         "{ s scale     | 1.0            | resize the image before detect}"
         "{ o output    |                | specify output path when input is images}";