Merge 3b33713a8c into ce3c6681c9
Maicol Gomez
1 month ago
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/*
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* textdetection_2.cpp |
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* |
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* A demo program based on the code of Lluis Gomez i Bigorda provide by opencv_contrib |
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* |
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* Created on: August, 2018 |
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* Author: UNICAMP-Samsung group - Contact: mpereira at ic.unicamp.br |
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*/ |
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#include "opencv2/text.hpp" |
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#include "opencv2/highgui.hpp" |
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#include "opencv2/imgproc.hpp" |
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#include <vector> |
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#include <iostream> |
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#include <omp.h> |
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#include <iomanip> |
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#define MIN_HEIGHT_RATIO 0.5 |
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using namespace std; |
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using namespace cv; |
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using namespace cv::text; |
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bool cmp(ERStat &a,ERStat &b); |
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vector< vector<ERStat> > Sort(Mat &src,vector<vector<ERStat> > ®ions); |
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//Draw ER's in an image via floodFill
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void er_draw(vector<Mat> &channels, vector<vector<ERStat> > ®ions, vector<Vec2i> group, Mat& segmentation); |
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int main(int argc, const char * argv[]){ |
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if(argc != 2){ |
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cout << "Error: argv(1) = ImagePath" << endl; |
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return 0; |
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} |
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Mat src = imread(argv[1]); |
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Mat gray; |
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// Extract channels to be processed individually
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vector<Mat> channels; |
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cvtColor(src,gray,COLOR_BGR2GRAY); |
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// Append gray and negative channel to detect ER- (bright regions over dark background)
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channels.push_back(gray); |
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channels.push_back(255-gray); |
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int cn = (int)channels.size(); |
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//Text Spotting
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// Create ERFilter objects with the 1st and 2nd stage default classifiers for each channel
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Ptr<ERFilter> er_filter1[2]; |
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Ptr<ERFilter> er_filter2[2]; |
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for (int c=0; c < cn ; c++) |
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{ |
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er_filter1[c] = createERFilterNM1(loadClassifierNM1("trained_classifierNM1.xml"),16,0.00015f,0.13f,0.2f,true,0.1f); |
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er_filter2[c] = createERFilterNM2(loadClassifierNM2("trained_classifierNM2.xml"),0.5); |
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} |
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//er_filter1[0] = createERFilterNM1(loadClassifierNM1("trained_classifierNM1.xml"),16,0.00015f,0.13f,0.2f,true,0.1f);
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//Ptr<ERFilter> er_filter2 = createERFilterNM2(loadClassifierNM2("trained_classifierNM2.xml"),0.5);
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//Ptr<M_ERFilter> er_filter2 = M_createERFilterNM2(M_loadClassifierNM2("trained_classifierNM2.xml"),0.5);
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vector<vector<ERStat> > regions(cn); |
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// Apply the default cascade classifier to each independent channel (could be done in parallel)
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//cout << "Extracting Class Specific Extremal Regions from " << (int)channels.size() << " channels ..." << endl;
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//cout << " (...) this may take a while (...)" << endl << endl;
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//Parallelizing the process of region extraction
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#pragma omp parallel for num_threads(2) |
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for (int c=0; c < cn ; c++) |
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{ |
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er_filter1[c]->run(channels[c], regions[c]); |
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er_filter2[c]->run(channels[c], regions[c]); |
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} |
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vector< vector<ERStat> > sort_regions = Sort( src , regions ); |
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// Detect character groups
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//cout << "Grouping extracted ERs ... ";
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vector< vector<Vec2i> > region_groups; |
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vector<Rect> groups_boxes; |
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erGrouping(src, channels, regions, region_groups, groups_boxes, ERGROUPING_ORIENTATION_HORIZ); |
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//erGrouping(src, channels, regions, region_groups, groups_boxes, ERGROUPING_ORIENTATION_ANY, "./trained_classifier_erGrouping.xml", 0.5);
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//End Text Spotting
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Mat out_img; |
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Mat out_img_detection; |
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Mat out_img_segmentation = Mat::zeros(src.rows+2, src.cols+2, CV_8UC1); |
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src.copyTo(out_img); |
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src.copyTo(out_img_detection); |
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string output; |
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//Text Recognition
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Ptr<OCRTesseract> ocr = OCRTesseract::create(); |
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for(int i = 0 ; i < groups_boxes.size(); i++){ |
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rectangle(out_img_detection, groups_boxes[i].tl(), groups_boxes[i].br(), Scalar(0,255,255), 3); |
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Mat group_img = Mat::zeros(src.rows+2, src.cols+2, CV_8UC1); |
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er_draw(channels, regions, region_groups[i], group_img); |
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Mat group_segmentation; |
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group_img.copyTo(group_segmentation); |
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//image(nm_boxes[i]).copyTo(group_img);
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group_img(groups_boxes[i]).copyTo(group_img); |
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copyMakeBorder(group_img,group_img,15,15,15,15,BORDER_CONSTANT,Scalar(0)); |
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vector<Rect> boxes; |
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vector<string> words; |
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vector<float> confidences; |
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ocr->run(group_img, output, &boxes, &words, &confidences, OCR_LEVEL_WORD); |
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printf("x: %d - y: %d - width: %d - height: %d ",\
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groups_boxes[i].x, groups_boxes[i].y, groups_boxes[i].width, groups_boxes[i].height); |
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printf("- text: "); |
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for(int j = 0; j < output.size(); j++){ |
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if( output[j] != '\n' ) |
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printf("%c",output[j]); |
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else |
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printf(" "); |
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} |
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printf("\n"); |
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} |
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// memory clean-up
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er_filter1[0].release(); |
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er_filter1[1].release();
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regions.clear(); |
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if (!groups_boxes.empty()) |
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{ |
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groups_boxes.clear(); |
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} |
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return 0; |
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} |
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void er_draw(vector<Mat> &channels, vector<vector<ERStat> > ®ions, vector<Vec2i> group, Mat& segmentation) |
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{ |
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for (int r=0; r<(int)group.size(); r++) |
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{ |
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ERStat er = regions[group[r][0]][group[r][1]]; |
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if (er.parent != NULL) // deprecate the root region
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{ |
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int newMaskVal = 255; |
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int flags = 4 + (newMaskVal << 8) + FLOODFILL_FIXED_RANGE + FLOODFILL_MASK_ONLY; |
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floodFill(channels[group[r][0]],segmentation,Point(er.pixel%channels[group[r][0]].cols,er.pixel/channels[group[r][0]].cols), |
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Scalar(255),0,Scalar(er.level),Scalar(0),flags); |
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} |
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} |
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} |
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vector<vector<ERStat>> Sort(Mat &src,vector<vector<ERStat> > ®ions){ |
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vector< vector<ERStat> > ans; |
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for(int c = 0 ; c < regions.size() ; c++){ |
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vector<ERStat> tmp; |
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for(int i = 1 ; i < regions[c].size() ; i++){ |
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bool inside = 0; |
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for(int j = 0 ; j < tmp.size() ; j++){ |
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Rect area = regions[c][i].rect | tmp[j].rect; |
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if( area == regions[c][i].rect or area == tmp[j].rect ){ |
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inside = 1; |
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break; |
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} |
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} |
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if( inside ) |
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continue; |
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tmp.push_back( regions[c][i] ); |
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for(int j = tmp.size() - 2 ; j >= 0 ; j--){ |
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if( cmp( tmp[j] , tmp[j+1] ) ){ |
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swap( tmp[j] , tmp[j+1] ); |
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} |
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} |
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} |
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ans.push_back( tmp ); |
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} |
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return ans; |
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} |
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bool cmp(ERStat ®ion_1,ERStat ®ion_2){ |
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Point center_i(region_1.rect.x + region_1.rect.width/2, region_1.rect.y + region_1.rect.height/2); |
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Point center_j(region_2.rect.x + region_2.rect.width/2, region_2.rect.y + region_2.rect.height/2); |
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float centroid_angle = (float)atan2((float)(center_j.y - center_i.y), (float)(center_j.x - center_i.x)); |
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float height_ratio = (float)min(region_1.rect.height,region_2.rect.height) \
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/ max(region_1.rect.height,region_2.rect.height); |
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if( height_ratio < MIN_HEIGHT_RATIO ){ |
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return region_2.rect.y < region_1.rect.y; |
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} |
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if( region_2.rect.y + region_2.rect.height * .95 <= region_1.rect.y ) |
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return 1; |
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if( (region_1.rect.y <= region_2.rect.y and region_1.rect.y + region_1.rect.height >= region_2.rect.y \
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+ region_2.rect.height) or (region_1.rect.y - 0.5 * region_1.rect.height <= region_2.rect.y \
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and region_1.rect.y + 0.5 * region_2.rect.height >= region_2.rect.y) )
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return region_2.rect.x < region_1.rect.x; |
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if( region_1.rect.y > region_2.rect.y ) |
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return 1; |
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return 0; |
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} |
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