Merge https://github.com/Itseez/opencv_contrib into optflow

.github/ISSUE_TEMPLATE.md

+<!--
+If you have a question rather than reporting a bug please go to http://answers.opencv.org where you get much faster responses.
+If you need further assistance please read [How To Contribute](https://github.com/opencv/opencv/wiki/How_to_contribute).
+
+This is a template helping you to create an issue which can be processed as quickly as possible. This is the bug reporting section for the OpenCV library.
+-->
+
+##### System information (version)
+<!-- Example
+- OpenCV => 3.1
+- Operating System / Platform => Windows 64 Bit
+- Compiler => Visual Studio 2015
+-->
+
+- OpenCV => :grey_question:
+- Operating System / Platform => :grey_question:
+- Compiler => :grey_question:
+
+##### Detailed description
+
+<!-- your description -->
+
+##### Steps to reproduce
+
+<!-- to add code example fence it with triple backticks and optional file extension
+    ```.cpp
+    // C++ code example
+    ```
+ or attach as .txt or .zip file
+-->
\ No newline at end of file

.github/PULL_REQUEST_TEMPLATE.md

+<!-- Please use this line to close one or multiple issues when this pullrequest gets merged
+You can add another line right under the first one:
+resolves #1234
+resolves #1235
+-->
+
+### This pullrequest changes
+
+<!-- Please describe what your pullrequest is changing -->

.travis.yml

@@ -4,7 +4,7 @@ compiler:
   - clang
 before_script:
   - cd ../
-  - git clone https://github.com/Itseez/opencv.git
+  - git clone https://github.com/opencv/opencv.git
   - mkdir build-opencv
   - cd build-opencv
   - cmake -DOPENCV_EXTRA_MODULES_PATH=../opencv_contrib/modules ../opencv

CONTRIBUTING.md

 ## Contributing guidelines
 
-All guidelines for contributing to the OpenCV repository can be found at [`How to contribute guideline`](https://github.com/Itseez/opencv/wiki/How_to_contribute).
+All guidelines for contributing to the OpenCV repository can be found at [`How to contribute guideline`](https://github.com/opencv/opencv/wiki/How_to_contribute).

modules/dnn/CMakeLists.txt

 cmake_minimum_required(VERSION 2.8)
 
-if(APPLE_FRAMEWORK OR WINRT)
+if(APPLE_FRAMEWORK OR WINRT
+    OR AARCH64 # protobuf doesn't know this platform
+)
   ocv_module_disable(dnn)
 endif()
 

modules/dnn/tutorials/tutorial_dnn_build.markdown

@@ -3,7 +3,7 @@ Build opencv_contrib with dnn module {#tutorial_dnn_build}
 
 Introduction
 ------------
-opencv_dnn module is placed in the secondary [opencv_contrib](https://github.com/Itseez/opencv_contrib) repository,
+opencv_dnn module is placed in the secondary [opencv_contrib](https://github.com/opencv/opencv_contrib) repository,
 which isn't distributed in binary form, therefore you need to build it manually.
 
 To do this you need to have installed: [CMake](http://www.cmake.org/download), git, and build system (*gcc* with *make* for Linux or *MS Visual Studio* for Windows)
@@ -12,12 +12,12 @@ Steps
 -----
 -# Make any directory, for example **opencv_root**
 
--# Clone [opencv](https://github.com/Itseez/opencv) and [opencv_contrib](https://github.com/Itseez/opencv_contrib) repos to the **opencv_root**.
+-# Clone [opencv](https://github.com/opencv/opencv) and [opencv_contrib](https://github.com/opencv/opencv_contrib) repos to the **opencv_root**.
    You can do it in terminal like here:
 @code
 cd opencv_root
-git clone https://github.com/Itseez/opencv
-git clone https://github.com/Itseez/opencv_contrib
+git clone https://github.com/opencv/opencv
+git clone https://github.com/opencv/opencv_contrib
 @endcode
 
 -# Run [CMake-gui] and set source and build directories:

modules/optflow/include/opencv2/optflow.hpp

@@ -305,6 +305,25 @@ public:
     /** @copybrief getGradientDescentIterations @see getGradientDescentIterations */
     CV_WRAP virtual void setVariationalRefinementIterations(int val) = 0;
 
+    /** @brief Weight of the smoothness term
+    @see setVariationalRefinementAlpha */
+    CV_WRAP virtual float getVariationalRefinementAlpha() const = 0;
+    /** @copybrief getVariationalRefinementAlpha @see getVariationalRefinementAlpha */
+    CV_WRAP virtual void setVariationalRefinementAlpha(float val) = 0;
+
+    /** @brief Weight of the color constancy term
+    @see setVariationalRefinementDelta */
+    CV_WRAP virtual float getVariationalRefinementDelta() const = 0;
+    /** @copybrief getVariationalRefinementDelta @see getVariationalRefinementDelta */
+    CV_WRAP virtual void setVariationalRefinementDelta(float val) = 0;
+
+    /** @brief Weight of the gradient constancy term
+    @see setVariationalRefinementGamma */
+    CV_WRAP virtual float getVariationalRefinementGamma() const = 0;
+    /** @copybrief getVariationalRefinementGamma @see getVariationalRefinementGamma */
+    CV_WRAP virtual void setVariationalRefinementGamma(float val) = 0;
+
+
     /** @brief Whether to use mean-normalization of patches when computing patch distance. It is turned on
         by default as it typically provides a noticeable quality boost because of increased robustness to
         illumanition variations. Turn it off if you are certain that your sequence does't contain any changes

modules/optflow/src/dis_flow.cpp

@@ -65,6 +65,9 @@ class DISOpticalFlowImpl : public DISOpticalFlow
     int patch_stride;
     int grad_descent_iter;
     int variational_refinement_iter;
+    float variational_refinement_alpha;
+    float variational_refinement_gamma;
+    float variational_refinement_delta;
     bool use_mean_normalization;
     bool use_spatial_propagation;
 
@@ -84,6 +87,13 @@ class DISOpticalFlowImpl : public DISOpticalFlow
     void setGradientDescentIterations(int val) { grad_descent_iter = val; }
     int getVariationalRefinementIterations() const { return variational_refinement_iter; }
     void setVariationalRefinementIterations(int val) { variational_refinement_iter = val; }
+    float getVariationalRefinementAlpha() const { return variational_refinement_alpha; }
+    void setVariationalRefinementAlpha(float val) { variational_refinement_alpha = val; }
+    float getVariationalRefinementDelta() const { return variational_refinement_delta; }
+    void setVariationalRefinementDelta(float val) { variational_refinement_delta = val; }
+    float getVariationalRefinementGamma() const { return variational_refinement_gamma; }
+    void setVariationalRefinementGamma(float val) { variational_refinement_gamma = val; }
+
     bool getUseMeanNormalization() const { return use_mean_normalization; }
     void setUseMeanNormalization(bool val) { use_mean_normalization = val; }
     bool getUseSpatialPropagation() const { return use_spatial_propagation; }
@@ -161,6 +171,10 @@ DISOpticalFlowImpl::DISOpticalFlowImpl()
     patch_stride = 4;
     grad_descent_iter = 16;
     variational_refinement_iter = 5;
+    variational_refinement_alpha = 20.f;
+    variational_refinement_gamma = 10.f;
+    variational_refinement_delta = 5.f;
+
     border_size = 16;
     use_mean_normalization = true;
     use_spatial_propagation = true;
@@ -234,9 +248,9 @@ void DISOpticalFlowImpl::prepareBuffers(Mat &I0, Mat &I1)
             spatialGradient(I0s[i], I0xs[i], I0ys[i]);
             Ux[i].create(cur_rows, cur_cols);
             Uy[i].create(cur_rows, cur_cols);
-            variational_refinement_processors[i]->setAlpha(20.0f);
-            variational_refinement_processors[i]->setDelta(5.0f);
-            variational_refinement_processors[i]->setGamma(10.0f);
+            variational_refinement_processors[i]->setAlpha(variational_refinement_alpha);
+            variational_refinement_processors[i]->setDelta(variational_refinement_delta);
+            variational_refinement_processors[i]->setGamma(variational_refinement_gamma);
             variational_refinement_processors[i]->setSorIterations(5);
             variational_refinement_processors[i]->setFixedPointIterations(variational_refinement_iter);
         }

modules/optflow/src/variational_refinement.cpp

@@ -1074,9 +1074,10 @@ void VariationalRefinementImpl::RedBlackSOR_ParBody::operator()(const Range &ran
 
 void VariationalRefinementImpl::calc(InputArray I0, InputArray I1, InputOutputArray flow)
 {
-    CV_Assert(!I0.empty() && I0.depth() == CV_8U && I0.channels() == 1);
-    CV_Assert(!I1.empty() && I1.depth() == CV_8U && I1.channels() == 1);
+    CV_Assert(!I0.empty() && I0.channels() == 1);
+    CV_Assert(!I1.empty() && I1.channels() == 1);
     CV_Assert(I0.sameSize(I1));
+    CV_Assert((I0.depth() == CV_8U && I1.depth() == CV_8U) || (I0.depth() == CV_32F && I1.depth() == CV_32F));
     CV_Assert(!flow.empty() && flow.depth() == CV_32F && flow.channels() == 2);
     CV_Assert(I0.sameSize(flow));
 
@@ -1089,9 +1090,10 @@ void VariationalRefinementImpl::calc(InputArray I0, InputArray I1, InputOutputAr
 
 void VariationalRefinementImpl::calcUV(InputArray I0, InputArray I1, InputOutputArray flow_u, InputOutputArray flow_v)
 {
-    CV_Assert(!I0.empty() && I0.depth() == CV_8U && I0.channels() == 1);
-    CV_Assert(!I1.empty() && I1.depth() == CV_8U && I1.channels() == 1);
+    CV_Assert(!I0.empty() && I0.channels() == 1);
+    CV_Assert(!I1.empty() && I1.channels() == 1);
     CV_Assert(I0.sameSize(I1));
+    CV_Assert((I0.depth() == CV_8U && I1.depth() == CV_8U) || (I0.depth() == CV_32F && I1.depth() == CV_32F));
     CV_Assert(!flow_u.empty() && flow_u.depth() == CV_32F && flow_u.channels() == 1);
     CV_Assert(!flow_v.empty() && flow_v.depth() == CV_32F && flow_v.channels() == 1);
     CV_Assert(I0.sameSize(flow_u));

modules/text/include/opencv2/text.hpp

@@ -92,7 +92,7 @@ grouping horizontally aligned text, and the method proposed by Lluis Gomez and D
 in [Gomez13][Gomez14] for grouping arbitrary oriented text (see erGrouping).
 
 To see the text detector at work, have a look at the textdetection demo:
-<https://github.com/Itseez/opencv_contrib/blob/master/modules/text/samples/textdetection.cpp>
+<https://github.com/opencv/opencv_contrib/blob/master/modules/text/samples/textdetection.cpp>
 
     @defgroup text_recognize Scene Text Recognition
   @}

modules/text/include/opencv2/text/erfilter.hpp

@@ -345,7 +345,7 @@ single vector\<Point\>, the function separates them in two different vectors (th
 ERStats where extracted from two different channels).
 
 An example of MSERsToERStats in use can be found in the text detection webcam_demo:
-<https://github.com/Itseez/opencv_contrib/blob/master/modules/text/samples/webcam_demo.cpp>
+<https://github.com/opencv/opencv_contrib/blob/master/modules/text/samples/webcam_demo.cpp>
  */
 CV_EXPORTS void MSERsToERStats(InputArray image, std::vector<std::vector<Point> > &contours,
                                std::vector<std::vector<ERStat> > &regions);

modules/text/include/opencv2/text/ocr.hpp

@@ -81,10 +81,10 @@ Notice that it is compiled only when tesseract-ocr is correctly installed.
 @note
    -   (C++) An example of OCRTesseract recognition combined with scene text detection can be found
         at the end_to_end_recognition demo:
-        <https://github.com/Itseez/opencv_contrib/blob/master/modules/text/samples/end_to_end_recognition.cpp>
+        <https://github.com/opencv/opencv_contrib/blob/master/modules/text/samples/end_to_end_recognition.cpp>
     -   (C++) Another example of OCRTesseract recognition combined with scene text detection can be
         found at the webcam_demo:
-        <https://github.com/Itseez/opencv_contrib/blob/master/modules/text/samples/webcam_demo.cpp>
+        <https://github.com/opencv/opencv_contrib/blob/master/modules/text/samples/webcam_demo.cpp>
  */
 class CV_EXPORTS_W OCRTesseract : public BaseOCR
 {
@@ -152,7 +152,7 @@ enum decoder_mode
 @note
    -   (C++) An example on using OCRHMMDecoder recognition combined with scene text detection can
         be found at the webcam_demo sample:
-        <https://github.com/Itseez/opencv_contrib/blob/master/modules/text/samples/webcam_demo.cpp>
+        <https://github.com/opencv/opencv_contrib/blob/master/modules/text/samples/webcam_demo.cpp>
  */
 class CV_EXPORTS_W OCRHMMDecoder : public BaseOCR
 {
@@ -165,7 +165,7 @@ public:
 
     The default character classifier and feature extractor can be loaded using the utility funtion
     loadOCRHMMClassifierNM and KNN model provided in
-    <https://github.com/Itseez/opencv_contrib/blob/master/modules/text/samples/OCRHMM_knn_model_data.xml.gz>.
+    <https://github.com/opencv/opencv_contrib/blob/master/modules/text/samples/OCRHMM_knn_model_data.xml.gz>.
      */
     class CV_EXPORTS_W ClassifierCallback
     {
@@ -321,7 +321,7 @@ CV_EXPORTS_W Ptr<OCRHMMDecoder::ClassifierCallback> loadOCRHMMClassifierCNN(cons
  * The function calculate frequency statistics of character pairs from the given lexicon and fills the output transition_probabilities_table with them. The transition_probabilities_table can be used as input in the OCRHMMDecoder::create() and OCRBeamSearchDecoder::create() methods.
  * @note
  *    -   (C++) An alternative would be to load the default generic language transition table provided in the text module samples folder (created from ispell 42869 english words list) :
- *            <https://github.com/Itseez/opencv_contrib/blob/master/modules/text/samples/OCRHMM_transitions_table.xml>
+ *            <https://github.com/opencv/opencv_contrib/blob/master/modules/text/samples/OCRHMM_transitions_table.xml>
  **/
 CV_EXPORTS void createOCRHMMTransitionsTable(std::string& vocabulary, std::vector<std::string>& lexicon, OutputArray transition_probabilities_table);
 
@@ -335,7 +335,7 @@ CV_EXPORTS_W Mat createOCRHMMTransitionsTable(const String& vocabulary, std::vec
 @note
    -   (C++) An example on using OCRBeamSearchDecoder recognition combined with scene text detection can
         be found at the demo sample:
-        <https://github.com/Itseez/opencv_contrib/blob/master/modules/text/samples/word_recognition.cpp>
+        <https://github.com/opencv/opencv_contrib/blob/master/modules/text/samples/word_recognition.cpp>
  */
 class CV_EXPORTS_W OCRBeamSearchDecoder : public BaseOCR
 {
@@ -348,7 +348,7 @@ public:
 
     The default character classifier and feature extractor can be loaded using the utility funtion
     loadOCRBeamSearchClassifierCNN with all its parameters provided in
-    <https://github.com/Itseez/opencv_contrib/blob/master/modules/text/samples/OCRBeamSearch_CNN_model_data.xml.gz>.
+    <https://github.com/opencv/opencv_contrib/blob/master/modules/text/samples/OCRBeamSearch_CNN_model_data.xml.gz>.
      */
     class CV_EXPORTS_W ClassifierCallback
     {

modules/text/src/erfilter.cpp

@@ -2820,12 +2820,12 @@ bool guo_hall_thinning(const Mat1b & img, Mat& skeleton)
             p8 = (skeleton.data[row     * skeleton.cols + col-1]) > 0;
             p9 = (skeleton.data[(row-1) * skeleton.cols + col-1]) > 0;
 
-            int C  = (!p2 & (p3 | p4)) + (!p4 & (p5 | p6)) +
-                    (!p6 & (p7 | p8)) + (!p8 & (p9 | p2));
-            int N1 = (p9 | p2) + (p3 | p4) + (p5 | p6) + (p7 | p8);
-            int N2 = (p2 | p3) + (p4 | p5) + (p6 | p7) + (p8 | p9);
+            int C  = (!p2 && (p3 || p4)) + (!p4 && (p5 || p6)) +
+                    (!p6 && (p7 || p8)) + (!p8 && (p9 || p2));
+            int N1 = (p9 || p2) + (p3 || p4) + (p5 || p6) + (p7 || p8);
+            int N2 = (p2 || p3) + (p4 || p5) + (p6 || p7) + (p8 || p9);
             int N  = N1 < N2 ? N1 : N2;
-            int m  = iter == 0 ? ((p6 | p7 | !p9) & p8) : ((p2 | p3 | !p5) & p4);
+            int m  = iter == 0 ? ((p6 || p7 || !p9) && p8) : ((p2 || p3 || !p5) && p4);
 
             if ((C == 1) && (N >= 2) && (N <= 3) && (m == 0))
             {

modules/text/src/ocr_hmm_decoder.cpp

@@ -1206,7 +1206,7 @@ the output transition_probabilities_table with them.
 The transition_probabilities_table can be used as input in the OCRHMMDecoder::create() and OCRBeamSearchDecoder::create() methods.
 @note
    -   (C++) An alternative would be to load the default generic language transition table provided in the text module samples folder (created from ispell 42869 english words list) :
-        <https://github.com/Itseez/opencv_contrib/blob/master/modules/text/samples/OCRHMM_transitions_table.xml>
+        <https://github.com/opencv/opencv_contrib/blob/master/modules/text/samples/OCRHMM_transitions_table.xml>
  */
 void createOCRHMMTransitionsTable(string& vocabulary, vector<string>& lexicon, OutputArray _transitions)
 {

modules/tracking/tutorials/tutorial_introduction_to_tracker.markdown

@@ -28,8 +28,8 @@ Explanation
     as shown in help. In the help, it means that the image files are numbered with 4 digits
     (e.g. the file naming will be 0001.jpg, 0002.jpg, and so on).
 
-    You can find video samples in Itseez/opencv_extra/testdata/cv/tracking
-    <https://github.com/Itseez/opencv_extra/tree/master/testdata/cv/tracking>
+    You can find video samples in opencv_extra/testdata/cv/tracking
+    <https://github.com/opencv/opencv_extra/tree/master/testdata/cv/tracking>
 
 -#  **Declares the required variables**
 

modules/ximgproc/README.md

@@ -9,3 +9,4 @@ Extended Image Processing
 6. Superpixels
 7. Graph segmentation
 8. Selective search from segmentation
+10. Paillou Filter

modules/ximgproc/doc/ximgproc.bib

@@ -166,3 +166,13 @@
   year={2014},
   organization={IEEE}
 }
+
+@article{paillou1997detecting,
+  title={Detecting step edges in noisy SAR images: a new linear operator},
+  author={Paillou, Philippe},
+  journal={IEEE transactions on geoscience and remote sensing},
+  volume={35},
+  number={1},
+  pages={191--196},
+  year={1997}
+}

modules/ximgproc/include/opencv2/ximgproc.hpp

@@ -48,6 +48,8 @@
 #include "ximgproc/weighted_median_filter.hpp"
 #include "ximgproc/slic.hpp"
 #include "ximgproc/lsc.hpp"
+#include "ximgproc/paillou_filter.hpp"
+
 
 /** @defgroup ximgproc Extended Image Processing
   @{

modules/ximgproc/include/opencv2/ximgproc/paillou_filter.hpp

+/*
+ *  By downloading, copying, installing or using the software you agree to this license.
+ *  If you do not agree to this license, do not download, install,
+ *  copy or use the software.
+ *
+ *
+ *  License Agreement
+ *  For Open Source Computer Vision Library
+ *  (3 - clause BSD License)
+ *
+ *  Redistribution and use in source and binary forms, with or without modification,
+ *  are permitted provided that the following conditions are met :
+ *
+ *  *Redistributions of source code must retain the above copyright notice,
+ *  this list of conditions and the following disclaimer.
+ *
+ *  * Redistributions in binary form must reproduce the above copyright notice,
+ *  this list of conditions and the following disclaimer in the documentation
+ *  and / or other materials provided with the distribution.
+ *
+ *  * Neither the names of the copyright holders nor the names of the contributors
+ *  may be used to endorse or promote products derived from this software
+ *  without specific prior written permission.
+ *
+ *  This software is provided by the copyright holders and contributors "as is" and
+ *  any express or implied warranties, including, but not limited to, the implied
+ *  warranties of merchantability and fitness for a particular purpose are disclaimed.
+ *  In no event shall copyright holders or contributors be liable for any direct,
+ *  indirect, incidental, special, exemplary, or consequential damages
+ *  (including, but not limited to, procurement of substitute goods or services;
+ *  loss of use, data, or profits; or business interruption) however caused
+ *  and on any theory of liability, whether in contract, strict liability,
+ *  or tort(including negligence or otherwise) arising in any way out of
+ *  the use of this software, even if advised of the possibility of such damage.
+ */
+
+#ifndef __OPENCV_PAILLOUFILTER_HPP__
+#define __OPENCV_PAILLOUFILTER_HPP__
+#ifdef __cplusplus
+
+#include <opencv2/core.hpp>
+
+namespace cv {
+namespace ximgproc {
+
+//! @addtogroup ximgproc_filters
+//! @{
+
+/**
+* @brief   Applies Paillou filter to an image.
+*
+* For more details about this implementation, please see @cite paillou1997detecting
+*
+* @param   op          Source 8-bit or 16bit image, 1-channel or 3-channel image.
+* @param   _dst        result CV_32F image with same numeber of channel than op.
+* @param   omega double see paper
+* @param   alpha double see paper
+*
+* @sa GradientPaillouX, GradientPaillouY
+*/
+CV_EXPORTS void GradientPaillouY(InputArray op, OutputArray _dst, double alpha, double omega);
+CV_EXPORTS void GradientPaillouX(InputArray op, OutputArray _dst, double alpha, double omega);
+
+}
+}
+#endif
+#endif

modules/ximgproc/samples/paillou_demo.cpp

+/*
+ *  By downloading, copying, installing or using the software you agree to this license.
+ *  If you do not agree to this license, do not download, install,
+ *  copy or use the software.
+ *
+ *
+ *  License Agreement
+ *  For Open Source Computer Vision Library
+ *  (3 - clause BSD License)
+ *
+ *  Redistribution and use in source and binary forms, with or without modification,
+ *  are permitted provided that the following conditions are met :
+ *
+ *  *Redistributions of source code must retain the above copyright notice,
+ *  this list of conditions and the following disclaimer.
+ *
+ *  * Redistributions in binary form must reproduce the above copyright notice,
+ *  this list of conditions and the following disclaimer in the documentation
+ *  and / or other materials provided with the distribution.
+ *
+ *  * Neither the names of the copyright holders nor the names of the contributors
+ *  may be used to endorse or promote products derived from this software
+ *  without specific prior written permission.
+ *
+ *  This software is provided by the copyright holders and contributors "as is" and
+ *  any express or implied warranties, including, but not limited to, the implied
+ *  warranties of merchantability and fitness for a particular purpose are disclaimed.
+ *  In no event shall copyright holders or contributors be liable for any direct,
+ *  indirect, incidental, special, exemplary, or consequential damages
+ *  (including, but not limited to, procurement of substitute goods or services;
+ *  loss of use, data, or profits; or business interruption) however caused
+ *  and on any theory of liability, whether in contract, strict liability,
+ *  or tort(including negligence or otherwise) arising in any way out of
+ *  the use of this software, even if advised of the possibility of such damage.
+ */
+
+#include <opencv2/core.hpp>
+#include <opencv2/core/utility.hpp>
+#include <opencv2/highgui.hpp>
+#include <opencv2/ximgproc.hpp>
+#include "opencv2/ximgproc/paillou_filter.hpp"
+
+using namespace cv;
+using namespace cv::ximgproc;
+
+#include <iostream>
+using namespace std;
+
+int aa = 100, ww = 10;
+Mat dx, dy;
+UMat img;
+const char* window_name = "Gradient Modulus";
+
+static void DisplayImage(Mat x,string s)
+{
+	vector<Mat> sx;
+	split(x, sx);
+	vector<double> minVal(3), maxVal(3);
+	for (int i = 0; i < static_cast<int>(sx.size()); i++)
+	{
+		minMaxLoc(sx[i], &minVal[i], &maxVal[i]);
+	}
+	maxVal[0] = *max_element(maxVal.begin(), maxVal.end());
+	minVal[0] = *min_element(minVal.begin(), minVal.end());
+	Mat uc;
+	x.convertTo(uc, CV_8U,255/(maxVal[0]-minVal[0]),-255*minVal[0]/(maxVal[0]-minVal[0]));
+	imshow(s, uc);
+}
+
+
+/**
+ * @function paillouFilter
+ * @brief Trackbar callback
+ */
+static void PaillouFilter(int, void*)
+{
+    Mat dst;
+    double a=aa/100.0,w=ww/100.0;
+    Mat rx,ry;
+    GradientPaillouX(img,rx,a,w);
+    GradientPaillouY(img,ry,a,w);
+    DisplayImage(rx, "Gx");
+    DisplayImage(ry, "Gy");
+    add(rx.mul(rx),ry.mul(ry),dst);
+    sqrt(dst,dst);
+    DisplayImage(dst, window_name );
+}
+
+
+int main(int argc, char* argv[])
+{
+    if (argc==2)
+        imread(argv[1]).copyTo(img);
+    if (img.empty())
+    {
+        cout << "File not found or empty image\n";
+    }
+    imshow("Original",img);
+    namedWindow( window_name, WINDOW_AUTOSIZE );
+
+    /// Create a Trackbar for user to enter threshold
+    createTrackbar( "a:",window_name, &aa, 400, PaillouFilter );
+    createTrackbar( "w:", window_name, &ww, 400, PaillouFilter );
+    PaillouFilter(0,NULL);
+    waitKey();
+    return 0;
+}
\ No newline at end of file

modules/ximgproc/samples/structured_edge_detection.cpp

 /**************************************************************************************
 The structered edge demo requires you to provide a model.
 This model can be found at the opencv_extra repository on Github on the following link:
-https://github.com/Itseez/opencv_extra/blob/master/testdata/cv/ximgproc/model.yml.gz
+https://github.com/opencv/opencv_extra/blob/master/testdata/cv/ximgproc/model.yml.gz
 ***************************************************************************************/
 
 #include <opencv2/ximgproc.hpp>

modules/ximgproc/tutorials/disparity_filtering.markdown

@@ -27,7 +27,7 @@ Source Stereoscopic Image
 Source Code
 -----------
 
-We will be using snippets from the example application, that can be downloaded [here ](https://github.com/Itseez/opencv_contrib/blob/master/modules/ximgproc/samples/disparity_filtering.cpp).
+We will be using snippets from the example application, that can be downloaded [here ](https://github.com/opencv/opencv_contrib/blob/master/modules/ximgproc/samples/disparity_filtering.cpp).
 
 Explanation
 -----------

modules/xobjdetect/tools/waldboost_detector/CMakeLists.txt

@@ -19,7 +19,7 @@ file(GLOB ${the_target}_SOURCES ${CMAKE_CURRENT_SOURCE_DIR}/*.cpp)
 
 add_executable(${the_target} ${${the_target}_SOURCES})
 
-target_link_libraries(${the_target} ${OPENCV_${the_target}_DEPS})
+ocv_target_link_libraries(${the_target} ${OPENCV_${the_target}_DEPS})
 
 set_target_properties(${the_target} PROPERTIES
                       DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"