pre-merge

modules/xphoto/doc/xphoto.rst

-**********************************
-xphoto. Addon to basic photo modul
-**********************************
+*****************************
+xphoto. Extended photo module
+*****************************
 
 .. toctree::
     :maxdepth: 2

modules/xphoto/src/annf.hpp

@@ -95,11 +95,12 @@ public:
 };
 
 template <typename Tp, int cn> int KDTree <Tp, cn>::
-getMaxSpreadN(const int _left, const int _right) const
+getMaxSpreadN(const int left, const int right) const
 {
-    cv::Vec<Tp, cn> maxValue = data[ idx[_left] ],
-                    minValue = data[ idx[_left] ];
-    for (int i = _left + 1; i < _right; i += cn)
+    cv::Vec<Tp, cn> maxValue = data[ idx[left] ],
+                    minValue = data[ idx[left] ];
+
+    for (int i = left + 1; i < right; ++i)
         for (int j = 0; j < cn; ++j)
         {
             minValue[j] = std::min( minValue[j], data[idx[i]][j] );
@@ -143,6 +144,7 @@ KDTree(const cv::Mat &img, const int _leafNumber, const int _zeroThresh)
         }
 
         int nth = _left + (_right - _left)/2;
+
         int dimIdx = getMaxSpreadN(_left, _right);
         KDTreeComparator comp( this, dimIdx );
 
@@ -169,7 +171,7 @@ updateDist(const int leaf, const int &idx0, int &bestIdx, double &dist)
             abs(nx - x) < zeroThresh)
             continue;
         if (nx > width  - 1 || nx < 1 ||
-            ny > height - 1 || ny > 1 )
+            ny > height - 1 || ny < 1 )
             continue;
 
         double ndist = norm2(data[idx0], data[idx[k]]);
@@ -187,6 +189,9 @@ updateDist(const int leaf, const int &idx0, int &bestIdx, double &dist)
 static void dominantTransforms(const cv::Mat &img, std::vector <cv::Matx33f> &transforms,
                                const int nTransform, const int psize)
 {
+    const int zeroThresh = 2*psize;
+    const int leafNum = 63;
+
     /** Walsh-Hadamard Transformation **/
 
     std::vector <cv::Mat> channels;
@@ -204,7 +209,7 @@ static void dominantTransforms(const cv::Mat &img, std::vector <cv::Matx33f> &tr
     cv::Mat whs; // Walsh-Hadamard series
     cv::merge(channels, whs);
 
-    KDTree <float, 24> kdTree(whs, 16, 32);
+    KDTree <float, 24> kdTree(whs, leafNum, zeroThresh);
     std::vector <int> annf( whs.total(), 0 );
 
     /** Propagation-assisted kd-tree search **/
@@ -220,8 +225,8 @@ static void dominantTransforms(const cv::Mat &img, std::vector <cv::Matx33f> &tr
                 if (i - dy[k] >= 0 && j - dx[k] >= 0)
                 {
                     int neighbor = (i - dy[k])*whs.cols + (j - dx[k]);
-                    int leafIdx = k == 0 ? neighbor :
-                        annf[neighbor] + dy[k]*whs.cols + dx[k];
+                    int leafIdx = (dx[k] == 0 && dy[k] == 0)
+                        ? neighbor : annf[neighbor] + dy[k]*whs.cols + dx[k];
                     kdTree.updateDist(leafIdx, current,
                                annf[i*whs.cols + j], dist);
                 }
@@ -232,8 +237,8 @@ static void dominantTransforms(const cv::Mat &img, std::vector <cv::Matx33f> &tr
     cv::Mat_<double> annfHist(2*whs.rows - 1, 2*whs.cols - 1, 0.0),
                     _annfHist(2*whs.rows - 1, 2*whs.cols - 1, 0.0);
     for (size_t i = 0; i < annf.size(); ++i)
-        ++annfHist( (annf[i] - int(i))/whs.cols + whs.rows - 1,
-                    (annf[i] - int(i))%whs.cols + whs.cols - 1 );
+        ++annfHist( annf[i]/whs.cols - int(i)/whs.cols + whs.rows - 1,
+                    annf[i]%whs.cols - int(i)%whs.cols + whs.cols - 1 );
 
     cv::GaussianBlur( annfHist, annfHist,
         cv::Size(0, 0), std::sqrt(2.0), 0.0, cv::BORDER_CONSTANT);
@@ -260,13 +265,15 @@ static void dominantTransforms(const cv::Mat &img, std::vector <cv::Matx33f> &tr
     std::partial_sort( amount.begin(), amount.begin() + nTransform,
         amount.end(), std::greater< std::pair<double, int> >() );
 
+    std::ofstream out("C:/Users/Yury/Projects/inpaint/output/log.log");
     transforms.resize(nTransform);
     for (int i = 0; i < nTransform; ++i)
     {
         int idx = amount[i].second;
         transforms[i] = cv::Matx33f(1, 0, float(shiftM[idx].x),
                                     0, 1, float(shiftM[idx].y),
-                                    0, 0,          1          );
+                                    0, 0,         1          );
+        out << int(shiftM[idx].x) << "," << int(shiftM[idx].y) << std::endl;
     }
 }
 

modules/xphoto/src/inpainting.cpp

@@ -43,6 +43,7 @@
 #include <algorithm>
 #include <iterator>
 #include <iostream>
+#include <fstream>
 #include <time.h>
 #include <functional>
 
@@ -98,6 +99,7 @@ namespace cv
 
             warpPerspective( masks[0], masks[i + 1], transforms[i],
                              masks[0].size(), INTER_NEAREST);
+            cv::imwrite(cv::format("C:/Users/Yury/Projects/inpaint/output/%d.png", i), images[i]);
             masks[i + 1] &= invMask;
         }
 

modules/xphoto/src/whs.hpp

@@ -137,8 +137,11 @@ static void rgb2whs(const cv::Mat &src, cv::Mat &dst, const int nProjections, co
         nextProjection(projections, snake_idx[i - 1],
             snake_idx[i], npsize);
 
+    int pad = 0;
+
     cv::merge(projections, img);
-    img(cv::Rect(npsize, npsize, src.cols, src.rows)).copyTo(dst);
+    img(cv::Rect(npsize + pad, npsize + pad, src.cols - pad,
+        src.rows - pad)).copyTo(dst);
 }