Some new version of opencv_performance for opencv_traincascade?

Question

Some new version of opencv_performance for opencv_traincascade?

I noticed that cascades taught with opencv_traincascade do not work with the current version of opencv_performance . I tried converting the old performance cpp file to load new cascade types, but to no avail. The code is here:

 #include "cv.h" #include "highgui.h" #include <cstdio> #include <cmath> #include <ctime> #include <math.h> #include "opencv2/objdetect/objdetect.hpp" #include "opencv2/highgui/highgui.hpp" #include "opencv2/imgproc/imgproc.hpp" #include <iostream> #include <stdio.h> #ifndef PATH_MAX #define PATH_MAX 512 #endif /* PATH_MAX */ /*typedef struct HidCascade { int size; int count; } HidCascade; */ typedef struct ObjectPos { float x; float y; float width; int found; /* for reference */ int neghbors; } ObjectPos; using namespace std; using namespace cv; int main(int argc, char* argv[]) { int i, j; char* classifierdir = NULL; //char* samplesdir = NULL; int saveDetected = 1; double scale_factor = 1.1; float maxSizeDiff = 1.5F; float maxPosDiff = 1.1F; /* number of stages. if <=0 all stages are used */ //int nos = -1, nos0; int width = 25; int height = 15; int rocsize; FILE* info; FILE* resultados; char* infoname; char fullname[PATH_MAX]; //char detfilename[PATH_MAX]; char* filename; //char detname[] = "det-"; CascadeClassifier cascade; double totaltime; if (!(resultados = fopen("resultados.txt", "w"))) { printf("Cannot create results file.\n"); exit(-1); } infoname = (char*) ""; rocsize = 20; if (argc == 1) { printf("Usage: %s\n -data <classifier_directory_name>\n" " -info <collection_file_name>\n" " [-maxSizeDiff <max_size_difference = %f>]\n" " [-maxPosDiff <max_position_difference = %f>]\n" " [-sf <scale_factor = %f>]\n" " [-ni]\n" " [-rs <roc_size = %d>]\n" " [-w <sample_width = %d>]\n" " [-h <sample_height = %d>]\n", argv[0], maxSizeDiff, maxPosDiff, scale_factor, rocsize, width, height); return 0; } for (i = 1; i < argc; i++) { if (!strcmp(argv[i], "-data")) { classifierdir = argv[++i]; } else if (!strcmp(argv[i], "-info")) { infoname = argv[++i]; } else if (!strcmp(argv[i], "-maxSizeDiff")) { maxSizeDiff = (float) atof(argv[++i]); } else if (!strcmp(argv[i], "-maxPosDiff")) { maxPosDiff = (float) atof(argv[++i]); } else if (!strcmp(argv[i], "-sf")) { scale_factor = atof(argv[++i]); } else if (!strcmp(argv[i], "-ni")) { saveDetected = 0; } else if (!strcmp(argv[i], "-rs")) { rocsize = atoi(argv[++i]); } else if (!strcmp(argv[i], "-w")) { width = atoi(argv[++i]); } else if (!strcmp(argv[i], "-h")) { height = atoi(argv[++i]); } } if (!cascade.load(classifierdir)) { printf("Unable to load classifier from %s\n", classifierdir); return 1; } strcpy(fullname, infoname); filename = strrchr(fullname, '\\'); if (filename == NULL) { filename = strrchr(fullname, '/'); } if (filename == NULL) { filename = fullname; } else { filename++; } info = fopen(infoname, "r"); totaltime = 0.0; if (info != NULL) { int x, y, width, height; Mat img; int hits, missed, falseAlarms; int totalHits, totalMissed, totalFalseAlarms; int found; float distance; int refcount; ObjectPos* ref; int detcount; ObjectPos* det; int error = 0; int* pos; int* neg; pos = (int*) cvAlloc(rocsize * sizeof(*pos)); neg = (int*) cvAlloc(rocsize * sizeof(*neg)); for (i = 0; i < rocsize; i++) { pos[i] = neg[i] = 0; } printf("+================================+======+======+======+\n"); printf("| File Name | Hits |Missed| False|\n"); printf("+================================+======+======+======+\n"); fprintf(resultados, "+================================+======+======+======+\n"); fprintf(resultados, "| File Name | Hits |Missed| False|\n"); fprintf(resultados, "+================================+======+======+======+\n"); //fprintf (resultados, "%d\n",framesCnt); totalHits = totalMissed = totalFalseAlarms = 0; while (!feof(info)) { fscanf(info, "%s %d", filename, &refcount); img = imread(fullname); if (!img.data) { cout << "ow" << endl; return -1; } ref = (ObjectPos*) cvAlloc(refcount * sizeof(*ref)); for (i = 0; i < refcount; i++) { error = (fscanf(info, "%d %d %d %d", &x, &y, &width, &height) != 4); if (error) break; ref[i].x = 0.5F * width + x; ref[i].y = 0.5F * height + y; ref[i].width = sqrt(0.5F * (width * width + height * height)); ref[i].found = 0; ref[i].neghbors = 0; //in the new cascade, where to get the neighbors? } vector<Rect> obj_detectados; Rect retang; if (!error) { totaltime -= time(0); cascade.detectMultiScale(img, obj_detectados, scale_factor, 4, 0 //|CV_HAAR_FIND_BIGGEST_OBJECT // |CV_HAAR_DO_ROUGH_SEARCH | CV_HAAR_SCALE_IMAGE, Size(25, 15)); totaltime += time(0); if (obj_detectados.size() == 0) { detcount = 0; } else { detcount = obj_detectados.size(); } det = (detcount > 0) ? ((ObjectPos*) cvAlloc(detcount * sizeof(*det))) : NULL; hits = missed = falseAlarms = 0; for (vector<Rect>::const_iterator r = obj_detectados.begin(); r != obj_detectados.end(); r++, i++) { Point r1, r2; r1.x = (r->x); r1.y = (r->y); r2.x = (r->x + r->width); r2.y = (r->y + r->height); retang.x = r1.x; retang.y = r1.y; retang.width = abs(r2.x - r1.x); retang.height = abs(r2.y - r1.y); if (saveDetected) { rectangle(img, retang, Scalar(0, 0, 255), 3, CV_AA); } det[i].x = 0.5F*r->width + r->x; det[i].y = 0.5F*r->height + r->y; det[i].width = sqrt(0.5F * (r->width * r->width + r->height * r->height)); det[i].neghbors = 1; // i don't know if it will work... // det[i].neghbors = r.neighbors; --- how to do it in the new version?? found = 0; for (j = 0; j < refcount; j++) { distance = sqrtf( (det[i].x - ref[j].x) * (det[i].x - ref[j].x) + (det[i].y - ref[j].y) * (det[i].y - ref[j].y) ); //cout << distance << endl; if( (distance < ref[j].width * maxPosDiff) && (det[i].width > ref[j].width / maxSizeDiff) && (det[i].width < ref[j].width * maxSizeDiff) ) { ref[j].found = 1; ref[j].neghbors = MAX( ref[j].neghbors, det[i].neghbors ); found = 1; } } if (!found) { falseAlarms++; neg[MIN(det[i].neghbors, rocsize - 1)]++; //neg[MIN(0, rocsize - 1)]++; } } //imshow("teste", img); if (saveDetected) { //strcpy(detfilename, detname); //strcat(detfilename, filename); //strcpy(filename, detfilename); imwrite(fullname, img); //cvvSaveImage(fullname, img); } for (j = 0; j < refcount; j++) { if (ref[j].found) { hits++; //pos[MIN(0, rocsize - 1)]++; pos[MIN(ref[j].neghbors, rocsize - 1)]++; } else { missed++; } } totalHits += hits; totalMissed += missed; totalFalseAlarms += falseAlarms; printf("|%32.64s|%6d|%6d|%6d|\n", filename, hits, missed, falseAlarms); //printf("+--------------------------------+------+------+------+\n"); fprintf(resultados, "|%32.64s|%6d|%6d|%6d|\n", filename, hits, missed, falseAlarms); //fprintf(resultados, // "+--------------------------------+------+------+------+\n"); fflush(stdout); if (det) { cvFree( &det); det = NULL; } } /* if( !error ) */ //char c = (char) waitKey(10); // if (c == 27) // exit(0); cvFree( &ref); } fclose(info); printf("|%32.32s|%6d|%6d|%6d|\n", "Total", totalHits, totalMissed, totalFalseAlarms); fprintf(resultados, "|%32.32s|%6d|%6d|%6d|\n", "Total", totalHits, totalMissed, totalFalseAlarms); printf("+================================+======+======+======+\n"); fprintf(resultados, "+================================+======+======+======+\n"); //printf("Number of stages: %d\n", nos); //printf("Number of weak classifiers: %d\n", numclassifiers[nos - 1]); printf("Total time: %f\n", totaltime); fprintf(resultados, "Total time: %f\n", totaltime); /* print ROC to stdout */ for (i = rocsize - 1; i > 0; i--) { pos[i - 1] += pos[i]; neg[i - 1] += neg[i]; } //fprintf(stderr, "%d\n", nos); for (i = 0; i < rocsize; i++) { fprintf(stderr, "\t%d\t%d\t%f\t%f\n", pos[i], neg[i], ((float) pos[i]) / (totalHits + totalMissed), ((float) neg[i]) / (totalHits + totalMissed)); } cvFree( &pos); cvFree( &neg); } return 0; }