void sceneTextDetector::set_Filter()
{
for (int i = 0; i<2; i++)
{
Ptr<ERFilter> er_filter1 = createERFilterNM1(loadClassifierNM1("trained_classifierNM1.xml"), 7, 0.00015f, 0.13f, 0.2f, true, 0.02f);
Ptr<ERFilter> er_filter2 = createERFilterNM2(loadClassifierNM2("trained_classifierNM2.xml"), 0.2);
er_filters1.push_back(er_filter1);
er_filters2.push_back(er_filter2);
}
}
OCRTess::OCRTess(bool downsize, int region, int group) {
this->downsize = downsize;
this->REGION = region;
this->GROUP = group;
for (int i = 0; i < 2; i++) {
Ptr<ERFilter> er_filter1 = createERFilterNM1(loadClassifierNM1(DIR + TR_NM1), 8, 0.00015f, 0.13f, 0.2f, true, 0.1f);
Ptr<ERFilter> er_filter2 = createERFilterNM2(loadClassifierNM2(DIR + TR_NM2), 0.5);
this->erf1.push_back(er_filter1);
this->erf2.push_back(er_filter2);
}
}
void ExtractTexto::Segmentar( cv::Mat const & source, std::vector<cv::Rect> &groups_boxes ){
std::vector<cv::Mat> channels;
cv::text::computeNMChannels(source, channels);
groups_boxes.clear();
int cn = (int)channels.size();
for (int c = 0; c < cn-1; c++)
channels.push_back(channels[c]);
//Ptr<cv::text::ERFilter> er_filter1 = createERFilterNM1(loadClassifierNM1("trained_classifierNM1.xml"), 11, 0.00005, 0.2, 0.8, true, 0.5);
Ptr<cv::text::ERFilter> er_filter1 = createERFilterNM1(loadClassifierNM1("trained_classifierNM1.xml"), 13, 0.0005, 0.2, 0.5, true, 0.5);
Ptr<cv::text::ERFilter> er_filter2 = createERFilterNM2(loadClassifierNM2("trained_classifierNM2.xml"), 0.5);
std::vector< std::vector<cv::text::ERStat> > regions(channels.size());
for (int c=0; c<(int)channels.size(); c++){
er_filter1->run(channels[c], regions[c]);
er_filter2->run(channels[c], regions[c]);
}
std::vector< std::vector<Vec2i>> region_groups;
cv::text::erGrouping(source, channels, regions, region_groups, groups_boxes, ERGROUPING_ORIENTATION_HORIZ);
cv::Mat imagClone = source.clone();
findSuperRect(groups_boxes, groups_boxes);
groups_draw(imagClone, groups_boxes);
er_filter1.release();
er_filter2.release();
regions.clear();
}
