following code is for Detecting lines with Hough transform.But this code doesn't work properly.It says "cannot open pic1.png".Can you please check this code and tell me what is wrong with this code.Please help me. I am using openCV 2.3 library and visual studio 2010.Thank you.
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include"cv.h"
#include"cxcore.h"
#include"stdafx.h"
#include <iostream>
using namespace cv;
using namespace std;
void help()
{
cout << "\nThis program demonstrates line finding with the Hough transform.\n"
"Usage:\n"
"./houghlines <image_name>, Default is pic1.png\n" << endl;
}
int main(int argc, char** argv)
{
const char* filename = argc >= 2 ? argv[1] : "pic1.png";
Mat src = imread(filename, 0);
if(src.empty())
{
help();
cout << "can not open " << filename << endl;
return -1;
}
Mat dst, cdst;
Canny(src, dst, 50, 200, 3);
cvtColor(dst, cdst, CV_GRAY2BGR);
#if 0
vector<Vec2f> lines;
HoughLines(dst, lines, 1, CV_PI/180, 100, 0, 0 );
for( size_t i = 0; i < lines.size(); i++ )
{
float rho = lines[i][0], theta = lines[i][1];
Point pt1, pt2;
double a = cos(theta), b = sin(theta);
double x0 = a*rho, y0 = b*rho;
pt1.x = cvRound(x0 + 1000*(-b));
pt1.y = cvRound(y0 + 1000*(a));
pt2.x = cvRound(x0 - 1000*(-b));
pt2.y = cvRound(y0 - 1000*(a));
line( cdst, pt1, pt2, Scalar(0,0,255), 3, CV_AA);
}
#else
vector<Vec4i> lines;
HoughLinesP(dst, lines, 1, CV_PI/180, 50, 50, 10 );
for( size_t i = 0; i < lines.size(); i++ )
{
Vec4i l = lines[i];
line( cdst, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(0,0,255), 3, CV_AA);
}
#endif
imshow("source", src);
imshow("detected lines", cdst);
waitKey();
return 0;
}
It's looking for pic1.png in the same directory that the executable is running from.
You either need to copy the image to the same directory or enter the path (either full or relative) to the image file.
Mat src = imread("pic1.png", 0); // put the image pic1.png at the current directory.
Mat src = imread("C://...", 0); // at some other directory like #ChrisF stated.
Related
I am a newbie to c++ and the IDE I am using is Visual Studio '22. I have written a code to detect a face (eyes and mouth too) and save the roi to a folder on the pc. Now what it does can be thought of as an auto-capture of the roi as soon as the face is detected.
I now want to create the function for "force capture", for which I will need to have a button and add pretty much the same code I wrote for auto-capture to give it functionality.
How do I add the button and make it perform its task?
I found related answers but they use Qt not sure how to apply that here.
Thanks a ton! Really need help.
#include <opencv2/opencv.hpp>
#include <opencv2/dnn/dnn.hpp>
//(1) include face header
#include "opencv2/face.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
//(2) include face header
#include "opencv2/objdetect.hpp"
#include <iostream>
#include <opencv2/imgproc/types_c.h>
//file handling
#include <fstream>
#include <sstream>
using namespace cv;
using namespace std;
using namespace ml;
using namespace cv::face;
//(3) Global variables
Ptr<Facemark> facemark; //mark detection
CascadeClassifier faceDetector, mouth, eye, eye1; //face detection
string name, filename;
void process(Mat img, Mat imgcol) {
vector<Rect> faces;
faceDetector.detectMultiScale(img, faces);
Mat imFace;
if (faces.size() != 0) {
for (size_t i = 0; i < faces.size(); i++)
{
cv::rectangle(imgcol, faces[i], Scalar(255, 0, 0));
imFace = imgcol(faces[i]);
resize(imFace, imFace, Size(imFace.cols * 5, imFace.rows * 5));
faces[i] = Rect(faces[i].x = 0, faces[i].y = 0, faces[i].width * 5,
(faces[i].height) * 5);
}
vector< vector<Point2f> > shapes;
//vector < Rect > measures;
if (facemark->fit(imFace, faces, shapes)) //fiiting predef shapes in faces// // imface is the size of faces
{
for (unsigned long i = 0; i < faces.size(); i++) {
for (unsigned long k = 0; k < shapes[i].size(); k++) {
cv::circle(imFace, shapes[i][k], 5, cv::Scalar(0, 0, 255), FILLED);
}
}
}
namedWindow("Detected_shape");
imshow("Detected_shape", imFace);
waitKey(5);
}
else {
cout << "Faces not detected." << endl;
}
}
int main()
{
facemark = FacemarkLBF::create();
facemark->loadModel("C:/Dev/HeadPose/HeadPose/lbfmodel.yml");
faceDetector.load("D:/opencv/build/install/etc/haarcascades/haarcascade_frontalface_alt2.xml");
mouth.load("D:/opencv/build/install/etc/haarcascades/haarcascade_smile.xml");
eye.load("D:/opencv/build/install/etc/haarcascades/haarcascade_eye.xml");
cout << "Loaded model" << endl;
Mat frame, grayframe, testframe, faceROI;
int x_axis, y_axis;
namedWindow("Detecting");
VideoCapture cap(0); //1 for diff cam
while (1)
{
cap.read(frame);
if (!cap.read(frame))
{
cout << "an error while taking the frame from cap" << endl;
}
//face
vector<Rect> faces;
Mat frame_gray;
Mat crop;
Mat res;
Mat gray;
string text;
stringstream sstm;
cvtColor(frame, grayframe, CV_BGR2GRAY);
equalizeHist(grayframe, testframe);
faceDetector.detectMultiScale(testframe, faces, 1.1, 3, CASCADE_SCALE_IMAGE, Size(30, 30));
Rect roi_b;
Rect roi_c;
size_t ic = 0;
int ac = 0;
size_t ib = 0;
int ab = 0;
for (int ic = 0; ic < faces.size(); ic++)
{
roi_b.x = faces[ib].x;
roi_b.y = faces[ib].y;
roi_b.width = (faces[ib].width);
roi_b.height = (faces[ib].height);
crop = frame(roi_b);
resize(crop, res, Size(128, 128), 0, 0, INTER_LINEAR);
cvtColor(crop, gray, COLOR_BGR2GRAY);
stringstream ssfn;
filename = "C:\\Users\\Hp\\Desktop\\Faces\\";
ssfn << filename.c_str() << name <<"_"<< roi_b.width<<"_"<< roi_b.height << ".jpg";
filename = ssfn.str();
imwrite(filename, res);
rectangle(frame, faces[ic], Scalar(255, 0, 255), 2, 8, 0);
Mat face = frame(faces[ic]);
cvtColor(face, face, CV_BGR2GRAY);
//mouth
vector <Rect> mouthi;
mouth.detectMultiScale(face, mouthi);
for (int k = 0; k < mouthi.size(); k++)
{
Point pt1(mouthi[0].x + faces[ic].x, mouthi[0].y + faces[ic].y);
Point pt2(pt1.x + mouthi[0].width, pt1.y + mouthi[0].height);
rectangle(frame, pt1, pt2, Scalar(255, 0, 0), 1, 8, 0);
}
//eyes
faceROI = frame(faces[ic]);//Taking area of the face as Region of Interest for eyes//
vector<Rect>eyes;//declaring a vector named eyes//
eye.detectMultiScale(faceROI, eyes, 1.1, 3, 0 | CASCADE_SCALE_IMAGE, Size(5, 5)); //detect eyes in every face//
/*eye1.detectMultiScale(faceROI, eyes, 1.1, 3, 0 | CASCADE_SCALE_IMAGE, Size(5, 5));*/
for (size_t j = 0; j < eyes.size(); j++)
{ //for locating eyes//
Point center(faces[ic].x + eyes[j].x + eyes[j].width * 0.5, faces[ic].y + eyes[j].y + eyes[j].height * 0.5);//getting the centers of both eyes//
int radius = cvRound((eyes[j].width + eyes[j].height) * 0.25); //declaring radius of the eye enclosing circles//
// cout << "radius" << radius << endl;
circle(frame, center, radius, Scalar(255, 0, 0), 1, 8, 0);//drawing circle around both eyes//
x_axis = eyes[j].x;//storing x axis location of eyes in x_axis//
y_axis = eyes[j].y;//storing y axis location of eyes in y_axis//
cout << "Position of the eyes is:" << "(" << x_axis << "," << y_axis << ")" << endl;//showing co-ordinate values//
}
}
sstm << "Crop area size: " << roi_b.width << "x" << roi_b.height << " Filename: " << filename;
text = sstm.str();
if (!crop.empty()) {
imshow("detected", crop);
}
else destroyWindow("detected");
cout << "Name\n";
cin >> name;
Mat img; //image containers
Mat imgbw;
cap >> img; //image from webcam
resize(img, img, Size(460, 460), 0, 0, INTER_LINEAR_EXACT);
cvtColor(img, imgbw, COLOR_BGR2GRAY);
process(imgbw, img);
imshow("Detecting", frame);
if (waitKey(30) == 27) {
break;
}
}
return 0;
}
I have written a simple code to perform Hough transform and display the lines. The code is as follows,
#include <opencv2/imgcodecs.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <iostream>
using namespace cv;
using namespace std;
int lowThreshold=0;
int const max_lowThreshold = 100;
int kernel_size = 3;
int ratio = 3;
Mat img;
Mat display;
Mat temp;
void CannyThreshold()
{
cvtColor(img, display, COLOR_RGB2GRAY);
// GaussianBlur(display,display,Size(7,7),3,3);
GaussianBlur(display, display, Size(1, 1), 1,1);
// printf("%d\n",lowThreshold);
Canny(display,display,lowThreshold,3);
imshow("Canny",display);
}
void Hough()
{
Canny(temp,display,50,3);
vector<Vec2f> lines; // will hold the results of the detection
HoughLines(display, lines, 1, CV_PI/180, 150, 0, 0 ); // runs the actual detection
for( size_t i = 0; i < lines.size(); i++ )
{
float rho = lines[i][0], theta = lines[i][1];
Point pt1, pt2;
double a = cos(theta), b = sin(theta);
double x0 = a*rho, y0 = b*rho;
pt1.x = cvRound(x0 + 1000*(-b));
pt1.y = cvRound(y0 + 1000*(a));
pt2.x = cvRound(x0 - 1000*(-b));
pt2.y = cvRound(y0 - 1000*(a));
line(display, pt1, pt2, Scalar(0,0,255), 3, LINE_AA);
}
printf("Lines = %ld\n",lines.size());
imshow("Hough",display);
}
int main()
{
VideoCapture cap(0);
namedWindow("Canny");
createTrackbar("Min Threshold: ","Canny",&lowThreshold,max_lowThreshold);
while(1)
{
cap.read(img);
temp = img;
CannyThreshold();
Hough();
waitKey(1);
}
cap.release();
return 0;
}
I am unable to get a red line (or any color) in the output Image in the window "Hough". I just get a black and white image. I'm also running a simple Canny edge detection before the Hough transform. Could that be causing an issue?
Any suggestions on how I could get a color line on to be displayed?
You are drawing Hough lines on the gray image of canny.
I would like to detect not regular rectangular objects using OpenCV and approxPolyDP function. In the image I have 4 windows that can be approximate as rectangular contour using the approxPolyDP. But Im not able to detect all of them when set up certain threshold. I filter the windows using the wodth and the height and the angel between the vertices. I would like to have more robust code that can detect all 4 windows. Any help?Here my code
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
#include <stdlib.h>
using namespace cv;
using namespace std;
Mat src; Mat src_gray;
int thresh = 5;
int max_thresh = 60000;
RNG rng(12345);
void thresh_callback(int, void* );
static double angle(Point pt1, Point pt2, Point pt0)
{
double dx1 = pt1.x - pt0.x;
double dy1 = pt1.y - pt0.y;
double dx2 = pt2.x - pt0.x;
double dy2 = pt2.y - pt0.y;
return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10);
}
void setLabel(cv::Mat& im, const std::string label, std::vector<cv::Point>& contour)
{
int fontface = cv::FONT_HERSHEY_SIMPLEX;
double scale = 0.4;
int thickness = 1;
int baseline = 0;
cv::Size text = cv::getTextSize(label, fontface, scale, thickness, &baseline);
cv::Rect r = cv::boundingRect(contour);
cv::Point pt(r.x + ((r.width - text.width) / 2), r.y + ((r.height + text.height) / 2));
cv::rectangle(im, pt + cv::Point(0, baseline), pt + cv::Point(text.width, -text.height), CV_RGB(255,255,255), CV_FILLED);
cv::putText(im, label, pt, fontface, scale, CV_RGB(0,0,0), thickness, 8);
}
int main()
{
cv::Mat src = cv::imread("p3.png");
resize(src, src, Size(640,480), 0, 0, INTER_CUBIC);
char* source_window = "Source";
namedWindow( source_window, CV_WINDOW_AUTOSIZE );
imshow( source_window, src );
createTrackbar( " Canny thresh:", "Source", &thresh, max_thresh, thresh_callback );
thresh_callback( 0, 0 );
waitKey(0);
return(0);
}
void thresh_callback(int, void* ) {
src = imread("p3.png");
resize(src, src, Size(640,480), 0, 0, INTER_CUBIC);
//================================
Mat gray,bw,dil,erd;
Canny(gray,bw,thresh, thresh*1, 5);
//Canny( src_gray, canny_output, thresh, thresh*1, 3 );
dilate(bw,dil,Mat());
erode(dil,erd,Mat());
Mat tmp=bw.clone();
Size kernalSize (15,20);
Mat element = getStructuringElement (MORPH_RECT, kernalSize, Point(4,4) );
morphologyEx( bw, bw, MORPH_CLOSE, element );
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;//novo
findContours(bw.clone(), contours, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE);
vector<Point> approx;
Mat dst = src.clone();
for( int i = 0; i< contours.size(); i++ )
{
approxPolyDP(Mat(contours[i]), approx, arcLength(Mat(contours[i]), true) * 0.09, true);
if (approx.size() >= 4.0 && (approx.size() <= 4.1))
{
int vtc = approx.size();
vector<double> cos;
for(int j = 2; j < vtc + 1; j++)
cos.push_back(angle(approx[j%vtc], approx[j-2], approx[j-1]));
sort(cos.begin(), cos.end());
double mincos = cos.front();
double maxcos = cos.back();
if (vtc == 4 && mincos >= -0.6 && maxcos <= 0.6)
{
Rect r = boundingRect(contours[i]);
double ratio = abs(1 - (double)r.width / r.height);
if (r.height >50 && r.width >20 && r.height < 640 && r.width < 640 && r.height>r.width ) /* constraints on region size */
{
//Rect r = boundingRect(contours[i]);
//double ratio = abs(1 - (double)r.width / r.height);
line(dst, approx.at(0), approx.at(1), cvScalar(0,0,255),4);
line(dst, approx.at(1), approx.at(2), cvScalar(0,0,255),4);
line(dst, approx.at(2), approx.at(3), cvScalar(0,0,255),4);
line(dst, approx.at(3), approx.at(0), cvScalar(0,0,255),4);
}
}
}
}
}
Here the source image
And here detected windows
Here the drawing/visual contours
I am trying to make a hand recognition system but when i used grayscale for cvtColor, i get debug assertion fail but when i use HSV the code works fine. Can you resolve this ? I am a newbie in opencv.
#include "stdafx.h"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/objdetect.hpp"
#include < opencv2\opencv.hpp>
#include < stdio.h>
#include <iostream>
using namespace std;
using namespace cv;
int thresh = 100;
int findBiggestContour(vector<vector<Point> > contours){
int indexOfBiggestContour = -1;
int sizeOfBiggestContour = 0;
for (int i = 0; i < contours.size(); i++){
if (contours[i].size() > sizeOfBiggestContour){
sizeOfBiggestContour = contours[i].size();
indexOfBiggestContour = i;
}
}
return indexOfBiggestContour;
}
void shifcontour(vector<Point>& contour, int x, int y)
{
for (size_t i = 0; i<contour.size(); i++)
{
contour[i].x += x;
contour[i].y += y;
}
}
int main()
{
cout << "beginning";
VideoCapture cap("pathaka.MP4");
if (!cap.isOpened()) // check if we succeeded
return -1;
Ptr<BackgroundSubtractor> pMOG2 = createBackgroundSubtractorMOG2();
for (;;)
{
Mat original, img;
cap >> img;
imshow("Source", img);
Mat hsv;
cvtColor(img, hsv, CV_BGR2GRAY);
Mat bw;
inRange(hsv, Scalar(0, 30, 80), Scalar(20, 150, 255), bw);
GaussianBlur(bw, bw, Size(7, 7), 1.5, 1.5);
Canny(bw, bw, 0, 30, 3);
vector<vector<Point> > contours;
vector<vector<Point> > convex_hull;
vector<Vec4i> hierarchy;
int erosion_type = MORPH_ELLIPSE;
int erosion_size = 0;
Mat element = getStructuringElement(erosion_type,
Size(2 * erosion_size + 1, 2 * erosion_size + 1),
Point(erosion_size, erosion_size));
dilate(bw, bw, element);
findContours(bw, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0));
int s = findBiggestContour(contours);
Mat drawing = Mat::zeros(img.size(), CV_8UC1);
dilate(drawing, drawing, getStructuringElement(MORPH_ELLIPSE, Size(5, 5)));
dilate(drawing, drawing, getStructuringElement(MORPH_ELLIPSE, Size(5, 5)));
std::vector<cv::Point> cnt;
cnt = contours[s];
Moments M;
M = cv::moments(cnt);
cv::Point result;
result = cv::Point(M.m10 / M.m00, M.m01 / M.m00);
Point center(drawing.cols / 2, drawing.rows / 2);
cv::circle(drawing, center, 3, Scalar(255, 255, 255), -1, 8, 0);
int x;
if (result.x > center.x)
{
x = result.x - center.x;
x = -x;
}
else
{
x = result.x - center.x;
}
int y;
if (result.y < center.y)
{
y = center.y - result.y;
}
else
{
y = center.y - result.y;
}
cout << "x:" << x << endl;
cout << "y: " << y << endl;
shifcontour(contours[s], x, y);
drawContours(drawing, contours, s, Scalar(255), -1, 8, hierarchy, 0, Point());
imshow("Hsv", drawing);
if (waitKey(30) >= 0) break;
}
return 0;
}
I think the problem is:
findContours(bw, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0));
contours now may have something inside, but it could be empty, right? Then, you do this:
int s = findBiggestContour(contours);
If contours.size() == 0, then s == -1, correct?
But after that, you do this:
std::vector<cv::Point> cnt;
cnt = contours[s];
If contours is empty, contours[-1] throws vector subscript out of range.
You should check if (s != -1) before using contours[s], ok?
Perhaps you should process the contours only if there is any, like this:
findContours(bw, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0));
if (contours.size() > 0) {
int s = findBiggestContour(contours);
Mat drawing = Mat::zeros(img.size(), CV_8UC1);
// these dilates are useless, because drawing is an empty image!
dilate(drawing, drawing, getStructuringElement(MORPH_ELLIPSE, Size(5, 5)));
dilate(drawing, drawing, getStructuringElement(MORPH_ELLIPSE, Size(5, 5)));
std::vector<cv::Point> cnt = contours[s];
Moments M = cv::moments(cnt);
Point result = cv::Point(M.m10 / M.m00, M.m01 / M.m00);
Point center(drawing.cols / 2, drawing.rows / 2);
circle(drawing, center, 3, Scalar(255, 255, 255), -1, 8, 0);
int x;
if (result.x > center.x) {
x = result.x - center.x;
x = -x;
} else {
x = result.x - center.x;
}
// is this correct? y has the same value in both cases...
int y;
if (result.y < center.y) y = center.y - result.y;
else y = center.y - result.y;
cout << "x:" << x << endl;
cout << "y: " << y << endl;
shifcontour(contours[s], x, y);
drawContours(drawing, contours, s, Scalar(255), -1, 8, hierarchy, 0, Point());
imshow("Hsv", drawing);
}
I'm using Opencv2.4.6 and Netbeans IDE for C++.
I'm trying to do a program to detect a face with the CascadeClassifier, and then pass the Rect of the face to the Camshift function to track this face.
To do that, I took the sample code "Camshiftdemo.cpp" that comes in the samples folder of opencv and I've modified. In my code instead of use the mouse to select the region over which you want to do tracking, is the cascade classifier which passes that information.
#include "opencv2/video/tracking.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include <iostream>
#include <ctype.h>
using namespace cv;
using namespace std;
Mat image;
int trackObject = 0;
Rect selection;
int main()
{
VideoCapture cap;
Rect trackWindow;
int hsize = 16;
float hranges[] = {0,180};
const float* phranges = hranges;
int matchesNum = 0;
CascadeClassifier cascade;
if (!cascade.load("C:/opencv/data/haarcascades/haarcascade_frontalface_default.xml")) {
cout << "Cannot load face xml!" << endl;
return -1;
}
cap.open("D:/Videos_Proy/ProgramacionII/CAMERA3_clase1.MP4");
if (!cap.isOpened()) {
cout << "***Could not initialize capturing...***\n";
return -1;
}
namedWindow( "Result", 1 );
Mat frame, hsv, hue, hist, mask, backproj;
for(;;)
{
cap >> frame;
if( frame.empty() )
break;
frame.copyTo(image);
if ( !trackObject )
{
Mat grayframe;
vector <Rect> facesBuf;
int detectionsNum = 0;
cvtColor(image, grayframe, CV_BGR2GRAY);
cascade.detectMultiScale(grayframe, facesBuf, 1.2, 4, CV_HAAR_FIND_BIGGEST_OBJECT |
CV_HAAR_SCALE_IMAGE, cvSize(0, 0));
detectionsNum = (int) facesBuf.size();
Rect *faceRects = &facesBuf[0];
//It must found faces in three consecutives frames to start the tracking to discard false positives
if (detectionsNum > 0)
matchesNum += 1;
else matchesNum = 0;
if ( matchesNum == 3 )
{
trackObject = -1;
selection = faceRects[0];
}
for (int i = 0; i < detectionsNum; i++)
{
Rect r = faceRects[i];
rectangle(image, Point(r.x, r.y), Point(r.x + r.width, r.y + r.height), CV_RGB(0, 255, 0));
}
}
if( trackObject )
{
cvtColor(image, hsv, CV_BGR2HSV);
inRange(hsv, Scalar(0, 69, 53),
Scalar(180, 256, 256), mask);
int ch[] = {0, 0};
hue.create(hsv.size(), hsv.depth());
mixChannels(&hsv, 1, &hue, 1, ch, 1);
if( trackObject < 0 )
{
Mat roi(hue, selection), maskroi(mask, selection);
calcHist(&roi, 1, 0, maskroi, hist, 1, &hsize, &phranges);
normalize(hist, hist, 0, 255, CV_MINMAX);
trackWindow = selection;
trackObject = 1;
}
calcBackProject(&hue, 1, 0, hist, backproj, &phranges);
backproj &= mask;
RotatedRect trackBox = CamShift(backproj, trackWindow,
TermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ));
if( trackWindow.area() <= 1 )
{
int cols = backproj.cols, rows = backproj.rows, r = (MIN(cols, rows) + 5)/6;
trackWindow = Rect(trackWindow.x - r, trackWindow.y - r,
trackWindow.x + r, trackWindow.y + r) &
Rect(0, 0, cols, rows);
}
ellipse( image, trackBox, Scalar(0,0,255), 3, CV_AA );
}
imshow( "Result", image );
if(waitKey(30) >= 0) break;
}
return 0;
}
This code makes sense to me, and when I Build it in Netbeans do not get any error, the problem is that don't run and Netbeans don't give any clue, only says: RUN FAILED (exit value -1.073.741.819, total time: 5s)
Anyone could help me and give any idea about what is happening. Thanks!!