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opencv_performace for new cascade.xml format in OpenCV2.4
/*
* performance.cpp
* copied from http://pastebin.com/V8RfGuid ( http://comments.gmane.org/gmane.comp.lib.opencv/52984 )
*
* Measure performance of classifier
*
* License:
* * The original source code's license is unknown... But, I guess some OSS License is assumed.
* * So,
* 1. this source code's is applied the original license.
* 2. If nothing, The MIT License: http://mokemokechicken.mit-license.org/ is applied.
*/
#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 minWidth = 25;
int minHeight = 15;
int rocsize;
int nNeighbors = 3;
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"
" [-minWidth <min_width = %d>]\n"
" [-minHeight <min_height = %d>]\n"
" [-neighbors <neighbors = %d>]\n"
, argv[0], maxSizeDiff,
maxPosDiff, scale_factor, rocsize, minWidth, minHeight, nNeighbors);
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], "-minWidth")) {
minWidth = atoi(argv[++i]);
} else if (!strcmp(argv[i], "-minHeight")) {
minHeight = atoi(argv[++i]);
} else if (!strcmp(argv[i], "-neighbors")) {
nNeighbors = 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, nNeighbors, 0
//|CV_HAAR_FIND_BIGGEST_OBJECT
// |CV_HAAR_DO_ROUGH_SEARCH
| CV_HAAR_SCALE_IMAGE, Size(minWidth, minHeight));
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;
i=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);
fprintf(resultados, "|%32.64s|%6d|%6d|%6d|\n", filename, hits,
missed, falseAlarms);
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;
}
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