erGrouping now uses a classifier for group validation instead of a set of heuristical ifos.

Updated documentation and sample to use the new function API
2013-09-27 16:28:47 +02:00
parent 4b203f7b1a
commit 047b568f6d
13 changed files with 20277 additions and 212 deletions
--- a/samples/cpp/textdetection.cpp
+++ b/samples/cpp/textdetection.cpp
@@ -0,0 +1,127 @@
+/*
+ * textdetection.cpp
+ *
+ * A demo program of the Extremal Region Filter algorithm described in
+ * Neumann L., Matas J.: Real-Time Scene Text Localization and Recognition, CVPR 2012
+ *
+ * Created on: Sep 23, 2013
+ *     Author: Lluis Gomez i Bigorda <lgomez AT cvc.uab.es>
+ */
+
+#include  "opencv2/opencv.hpp"
+#include  "opencv2/objdetect.hpp"
+#include  "opencv2/highgui.hpp"
+#include  "opencv2/imgproc.hpp"
+
+#include  <vector>
+#include  <iostream>
+#include  <iomanip>
+
+using  namespace std;
+using  namespace cv;
+
+void show_help_and_exit(const char *cmd);
+void groups_draw(Mat &src, vector<Rect> &groups);
+void er_show(vector<Mat> &channels, vector<vector<ERStat> > &regions);
+
+int  main(int argc, const char * argv[])
+{
+    cout << endl << argv[0] << endl << endl;
+    cout << "Demo program of the Extremal Region Filter algorithm described in " << endl;
+    cout << "Neumann L., Matas J.: Real-Time Scene Text Localization and Recognition, CVPR 2012" << endl << endl;
+
+    if (argc < 2) show_help_and_exit(argv[0]);
+
+    Mat src = imread(argv[1]);
+
+    // Extract channels to be processed individually
+    vector<Mat> channels;
+    computeNMChannels(src, channels);
+
+    int cn = (int)channels.size();
+    // Append negative channels to detect ER- (bright regions over dark background)
+    for (int c = 0; c < cn-1; c++)
+        channels.push_back(255-channels[c]);
+
+    // Create ERFilter objects with the 1st and 2nd stage default classifiers
+    Ptr<ERFilter> er_filter1 = createERFilterNM1(loadClassifierNM1("trained_classifierNM1.xml"),16,0.00015,0.13,0.2,true,0.1);
+    Ptr<ERFilter> er_filter2 = createERFilterNM2(loadClassifierNM2("trained_classifierNM2.xml"),0.5);
+
+    vector<vector<ERStat> > regions(channels.size());
+    // Apply the default cascade classifier to each independent channel (could be done in parallel)
+    cout << "Extracting Class Specific Extremal Regions from " << (int)channels.size() << " channels ..." << endl;
+    cout << "    (...) this may take a while (...)" << endl << endl;
+    for (int c=0; c<(int)channels.size(); c++)
+    {
+        er_filter1->run(channels[c], regions[c]);
+        er_filter2->run(channels[c], regions[c]);
+    }
+
+    // Detect character groups
+    cout << "Grouping extracted ERs ... ";
+    vector<Rect> groups;
+    erGrouping(channels, regions, "trained_classifier_erGrouping.xml", 0.5, groups);
+
+    // draw groups
+    groups_draw(src, groups);
+    imshow("grouping",src);
+
+    cout << "Done!" << endl << endl;
+    cout << "Press 'e' to show the extracted Extremal Regions, any other key to exit." << endl << endl;
+    if( waitKey (-1) == 101)
+        er_show(channels,regions);
+
+    // memory clean-up
+    er_filter1.release();
+    er_filter2.release();
+    regions.clear();
+    if (!groups.empty())
+    {
+        groups.clear();
+    }
+}
+
+
+
+// helper functions
+
+void show_help_and_exit(const char *cmd)
+{
+    cout << "    Usage: " << cmd << " <input_image> " << endl;
+    cout << "    Default classifier files (trained_classifierNM*.xml) must be in current directory" << endl << endl;
+    exit(-1);
+}
+
+void groups_draw(Mat &src, vector<Rect> &groups)
+{
+    for (int i=groups.size()-1; i>=0; i--)
+    {
+        if (src.type() == CV_8UC3)
+            rectangle(src,groups.at(i).tl(),groups.at(i).br(),Scalar( 0, 255, 255 ), 3, 8 );
+        else
+            rectangle(src,groups.at(i).tl(),groups.at(i).br(),Scalar( 255 ), 3, 8 );
+    }
+}
+
+void er_show(vector<Mat> &channels, vector<vector<ERStat> > &regions)
+{
+    for (int c=0; c<(int)channels.size(); c++)
+    {
+        Mat dst = Mat::zeros(channels[0].rows+2,channels[0].cols+2,CV_8UC1);
+        for (int r=0; r<(int)regions[c].size(); r++)
+        {
+            ERStat er = regions[c][r];
+            if (er.parent != NULL) // deprecate the root region
+            {
+                int newMaskVal = 255;
+                int flags = 4 + (newMaskVal << 8) + FLOODFILL_FIXED_RANGE + FLOODFILL_MASK_ONLY;
+                floodFill(channels[c],dst,Point(er.pixel%channels[c].cols,er.pixel/channels[c].cols),
+                          Scalar(255),0,Scalar(er.level),Scalar(0),flags);
+            }
+        }
+        char buff[10]; char *buff_ptr = buff;
+        sprintf(buff, "channel %d", c);
+        imshow(buff_ptr, dst);
+    }
+    waitKey(-1);
+}