Merge pull request #42 from lluisgomez/master

Adds The exhaustive search algorithm and updates the previous groupining algorithm; Add xml files with default classifier models;

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

@@ -41,8 +41,8 @@
 //
 //M*/
 
-#ifndef __OPENCV_OBJDETECT_ERFILTER_HPP__
-#define __OPENCV_OBJDETECT_ERFILTER_HPP__
+#ifndef __OPENCV_TEXT_ERFILTER_HPP__
+#define __OPENCV_TEXT_ERFILTER_HPP__
 
 #include "opencv2/core.hpp"
 #include <vector>
@@ -52,7 +52,7 @@
 namespace cv
 {
 namespace text
-{    
+{
 
 /*!
     Extremal Region Stat structure
@@ -217,8 +217,8 @@ CV_EXPORTS Ptr<ERFilter::Callback> loadClassifierNM2(const std::string& filename
 
 
 // computeNMChannels operation modes
-enum { ERFILTER_NM_RGBLGrad = 0,
-       ERFILTER_NM_IHSGrad  = 1
+enum { ERFILTER_NM_RGBLGrad,
+       ERFILTER_NM_IHSGrad
      };
 
 /*!
@@ -239,6 +239,12 @@ enum { ERFILTER_NM_RGBLGrad = 0,
 CV_EXPORTS void computeNMChannels(InputArray _src, OutputArrayOfArrays _channels, int _mode = ERFILTER_NM_RGBLGrad);
 
 
+
+// erGrouping operation modes
+enum { ERGROUPING_ORIENTATION_HORIZ,
+       ERGROUPING_ORIENTATION_ANY
+};
+
 /*!
     Find groups of Extremal Regions that are organized as text blocks. This function implements
     the grouping algorithm described in:
@@ -260,10 +266,14 @@ CV_EXPORTS void computeNMChannels(InputArray _src, OutputArrayOfArrays _channels
     \param  minProbability The minimum probability for accepting a group
     \param  groups         The output of the algorithm are stored in this parameter as list of rectangles.
 */
-CV_EXPORTS void erGrouping(InputArrayOfArrays src, std::vector<std::vector<ERStat> > &regions,
-                                                   const std::string& filename, float minProbablity,
-                                                   std::vector<Rect > &groups);
+CV_EXPORTS void erGrouping(InputArray img, InputArrayOfArrays channels,
+                                           std::vector<std::vector<ERStat> > &regions,
+                                           std::vector<std::vector<Vec2i> > &groups,
+                                           std::vector<Rect> &groups_rects,
+                                           int method = ERGROUPING_ORIENTATION_HORIZ,
+                                           const std::string& filename = std::string(),
+                                           float minProbablity = 0.5);
 
 }
 }
-#endif // _OPENCV_ERFILTER_HPP_
+#endif // _OPENCV_TEXT_ERFILTER_HPP_

modules/text/samples/textdetection.cpp

@@ -32,6 +32,7 @@ int main(int argc, const char * argv[])
 
     if (argc < 2) show_help_and_exit(argv[0]);
 
+    namedWindow("grouping",WINDOW_NORMAL);
     Mat src = imread(argv[1]);
 
     // Extract channels to be processed individually
@@ -59,11 +60,13 @@ int main(int argc, const char * argv[])
 
     // Detect character groups
     cout << "Grouping extracted ERs ... ";
-    vector<Rect> groups;
-    erGrouping(channels, regions, "trained_classifier_erGrouping.xml", 0.5, groups);
+    vector< vector<Vec2i> > region_groups;
+    vector<Rect> groups_boxes;
+    erGrouping(src, channels, regions, region_groups, groups_boxes, ERGROUPING_ORIENTATION_HORIZ);
+    //erGrouping(src, channels, regions, region_groups, groups_boxes, ERGROUPING_ORIENTATION_ANY, "./trained_classifier_erGrouping.xml", 0.5);
 
     // draw groups
-    groups_draw(src, groups);
+    groups_draw(src, groups_boxes);
     imshow("grouping",src);
 
     cout << "Done!" << endl << endl;
@@ -75,9 +78,9 @@ int main(int argc, const char * argv[])
     er_filter1.release();
     er_filter2.release();
     regions.clear();
-    if (!groups.empty())
+    if (!groups_boxes.empty())
     {
-        groups.clear();
+        groups_boxes.clear();
     }
 }