float* hough_circles(void* img, int dp, int min_d, int p1, int p2, int min_r, int max_r){
IplImage* image = (IplImage*)img;
CvMemStorage* storage = cvCreateMemStorage(0);
cvClearMemStorage(storage);
CvSeq* circles =
cvHoughCircles(image, storage, CV_HOUGH_GRADIENT, dp, min_d, p1, p2, min_r, max_r);
if(circles->total == 0)
return NULL;
float* coords = malloc((1 + 3 * circles->total) * sizeof(float));
coords[0] = (float)circles->total;
int i,k;
for(i=0, k=1; i<circles->total; i++, k+=3){
float* p = (float*)cvGetSeqElem(circles, i);
coords[k] = p[0];
coords[k+1] = p[1];
coords[k+2] = p[2];
}
cvReleaseMemStorage(&storage);
return coords;
}
void EyeTracker::doHoughTransform()
{
if(!firstDetect)
{
CvMemStorage* storage = cvCreateMemStorage(0);
while(!firstDetect)
{
float* p;
CvSeq* circles;
circles = cvHoughCircles(grayEyeImagePts, storage, CV_HOUGH_GRADIENT,
3, grayEyeImagePts->width, 50, 100, 30, 60);
int i;
static int count = 0;
for(i = 0; i < circles->total; i++)
{
++count;
p = (float*)cvGetSeqElem(circles, i);
prev_center.x = (int)p[0];
prev_center.y = (int)p[1];
//cout << "merkez bulundu hough " << count << endl;
}
firstDetect = true;
}
cvReleaseMemStorage(&storage);
}
}
IplImage * BouyObject::FindCircles(const IplImage * imgIn) const
{
IplImage * imgOut = cvCloneImage(imgIn);
CvSize imageSize = cvSize(imgIn->width & -2, imgIn->height & -2 );
IplImage* imgSmallCopy = cvCreateImage( cvSize(imageSize.width/2, imageSize.height/2), IPL_DEPTH_8U, 1 );
cvPyrDown( imgOut, imgSmallCopy);
cvPyrUp( imgSmallCopy, imgOut);
cvSmooth(imgOut, imgOut, CV_GAUSSIAN, 5);
cvReleaseImage(&imgSmallCopy);
CvMemStorage* storage = cvCreateMemStorage(0);
CvSeq* results = cvHoughCircles(
imgOut,
storage,
CV_HOUGH_GRADIENT,
2,
imgOut->width/10,
100,
100);
cvZero(imgOut);
for( int i = 0; i < results->total; i++ ) {
float* p = (float*) cvGetSeqElem( results, i );
CvPoint pt = cvPoint( cvRound( p[0] ), cvRound( p[1] ) );
cvCircle( imgOut,
pt,
cvRound( p[2] ),
CV_RGB(0xff,0xff,0xff),CV_FILLED);
}
cvReleaseMemStorage(&storage);
return imgOut;
}
int main(int argc, char** argv) {
IplImage* image = cvLoadImage(
"airplane.jpg",
CV_LOAD_IMAGE_GRAYSCALE
);
CvMemStorage* storage = cvCreateMemStorage(0);
cvSmooth(image, image, CV_GAUSSIAN, 5, 5 );
CvSeq* results = cvHoughCircles(
image,
storage,
CV_HOUGH_GRADIENT,
2,
image->width/10
);
for( int i = 0; i < results->total; i++ ) {
float* p = (float*) cvGetSeqElem( results, i );
CvPoint pt = cvPoint( cvRound( p[0] ), cvRound( p[1] ) );
cvCircle(
image,
pt,
cvRound( p[2] ),
CV_RGB(0xff,0xff,0xff)
);
}
cvNamedWindow( "cvHoughCircles", 1 );
cvShowImage( "cvHoughCircles", image);
cvWaitKey(0);
}
void Process::findHoughCircles()
{
cvClearMemStorage(houghCirclesStorage);
cvCvtColor(image, grayImage, CV_RGB2GRAY);
cvSmooth(grayImage, grayImage, CV_GAUSSIAN, 5, 5 );
CvSeq* seq = cvHoughCircles(
grayImage,
houghCirclesStorage,
CV_HOUGH_GRADIENT,
houghCirclesParam.inverseRatio,
houghCirclesParam.minDistance,
houghCirclesParam.param1,
houghCirclesParam.param2,
houghCirclesParam.minRadius,
houghCirclesParam.maxRadius
);
areas.clear();
for (int i=0; i<seq->total; i++) {
float* p = (float*) cvGetSeqElem( seq, i );
Area area;
area.pt[0] = p[0];
area.pt[1] = p[1];
area.width = p[2];
area.height = p[2];
areas.push_back(area);
}
}
/**
* Accurately applies circle detection and filtering in order to detect the position
* of the dot within an image then, it draws a red rectangle around it in the
* original image.
* @param img: pointer to the input image
* @return PointImage: pointer to a newly created data structure holding the image,
* center position of the dot within the image as well as it's radius.
*/
PointImage* getPoint(IplImage* img) {
IplImage* clone = cvCreateImage(cvSize(img->width, img->height), img->depth, 1);
cvCvtColor(img, clone, CV_RGB2GRAY);
cvThreshold(clone, clone, 127, 255, CV_THRESH_BINARY_INV);
cvSmooth(clone, clone, CV_GAUSSIAN, 31, 31);
cvMorphologyEx(clone, clone, NULL, NULL, CV_MOP_CLOSE, 6);
CvMemStorage* storage = cvCreateMemStorage();
CvSeq* circles = cvHoughCircles(clone, storage, CV_HOUGH_GRADIENT, ((double) (clone->width * clone->height * 5)) / ((double) 964 * 726),
50, 200, 100, 0, 35);
float* p;
PointImage* out;
for (int i = circles->total; i > 0; i--) {
p = (float*) cvGetSeqElem(circles, i);
if (*I(cvRound(p[0]), cvRound(p[1]), clone) > 185)
if (abs(cvRound(p[0]) - (clone->width / 2) * (clone->width / clone->height)) <= 100) {
cvRectangle(img, cvPoint(cvRound(p[0] - p[2]), cvRound(p[1] - p[2])), cvPoint(cvRound(p[0] + p[2]), cvRound(p[1] + p[2])),
CV_RGB(255,0,0), 3);
out = new PointImage(clone, cvPoint(cvRound(p[0]), cvRound(p[1])), cvRound(p[2]));
break;
}
}
cvNamedWindow("Circle Detection", CV_WINDOW_AUTOSIZE);
cvShowImage("Circle Detection", img);
cvReleaseMemStorage(&storage);
return out;
}
IplImage* BouyObject::ShapeMask(const IplImage * imgIn) const
{
IplImage * hsv = cvCloneImage(imgIn);
IplImage * imgOut = cvCreateImage(cvGetSize(imgIn),IPL_DEPTH_8U, 1);
//cvEqualizeHist( imgIn, hsv);
IplImage * chan0 = cvCreateImage(cvGetSize(imgIn),IPL_DEPTH_8U, 1);
IplImage * chan1 = cvCreateImage(cvGetSize(imgIn),IPL_DEPTH_8U, 1);
IplImage * chan2 = cvCreateImage(cvGetSize(imgIn),IPL_DEPTH_8U, 1);
IplImage * chan3 = cvCreateImage(cvGetSize(imgIn),IPL_DEPTH_8U, 1);
cvCvtColor(imgIn, hsv, CV_BGR2YCrCb);
cvSplit(hsv,chan0,chan1,chan2, NULL);
CvScalar white = cvRealScalar(255);
//imgOut = SegmentationMask(imgIn);
imgOut = cvCloneImage(chan2);
//invert black and white
cvAbsDiffS(imgOut, imgOut, white);
// cvShowImage("hue",chan0);
// cvShowImage("sat",chan1);
// cvShowImage("val",chan2);
// cvShowImage("inv",imgOut);
//cvWaitKey(0);
cvReleaseImage(&hsv);
cvReleaseImage(&chan0);
cvReleaseImage(&chan1);
cvReleaseImage(&chan2);
cvReleaseImage(&chan3);
CvSize imageSize = cvSize(imgIn->width & -2, imgIn->height & -2 );
IplImage* imgSmallCopy = cvCreateImage( cvSize(imageSize.width/2, imageSize.height/2), IPL_DEPTH_8U, 1 );
cvPyrDown( imgOut, imgSmallCopy);
cvPyrUp( imgSmallCopy, imgOut);
cvSmooth(imgOut, imgOut, CV_GAUSSIAN, 5);
cvReleaseImage(&imgSmallCopy);
CvMemStorage* storage = cvCreateMemStorage(0);
CvSeq* results = cvHoughCircles(
imgOut,
storage,
CV_HOUGH_GRADIENT,
2,
imgOut->width/10,
100,
100);
cvZero(imgOut);
for( int i = 0; i < results->total; i++ ) {
float* p = (float*) cvGetSeqElem( results, i );
CvPoint pt = cvPoint( cvRound( p[0] ), cvRound( p[1] ) );
cvCircle( imgOut,
pt,
cvRound( p[2] ),
CV_RGB(0xff,0xff,0xff),CV_FILLED);
}
cvReleaseMemStorage(&storage);
return imgOut;
}
void TamatarVision::update() {
vidGrabber.grabFrame();
if (vidGrabber.isFrameNew()) {
// load image from videograbber
colorImg.setFromPixels(vidGrabber.getPixels(), camWidth, camHeight);
// convert to grayscale
cvCvtColor( colorImg.getCvImage(), grayImg.getCvImage(), CV_RGB2GRAY );
grayImg.flagImageChanged();
// equalize histogram
if (doHistEqualize) {
cvEqualizeHist(grayImg.getCvImage(), grayImg.getCvImage() );
}
// `morphological opening`
if (doMorphEx) {
int anchor = morphExRadius / 2;
structure = cvCreateStructuringElementEx(morphExRadius, morphExRadius, anchor, anchor, CV_SHAPE_ELLIPSE);
cvCopy(grayImg.getCvImage(), grayImg2.getCvImage());
cvMorphologyEx(grayImg2.getCvImage(), grayImg.getCvImage(), NULL, structure, CV_MOP_OPEN);
}
if (doSmoothing) {
//grayImg2 = grayImg;
//smoothSigmaColor=20;
//smoothSigmaSpatial=20;
//cvSmooth(grayImg2.getCvImage(), grayImg.getCvImage(), CV_BILATERAL, 9, 9, smoothSigmaColor, smoothSigmaSpatial);
cvSmooth(grayImg.getCvImage(), grayImg.getCvImage(), CV_GAUSSIAN, 3, 3, 2, 2);
}
//grayImg.threshold(120);
// threshold
if (doThreshold) {
// grayImg.threshold(threshold);
grayImg2 = grayImg;
cvThreshold(grayImg2.getCvImage(), grayImg.getCvImage(), threshold, thresholdMax, CV_THRESH_TOZERO);
// cvAdaptiveThreshold(grayImg2.getCvImage(), grayImg.getCvImage(), threshold, CV_ADAPTIVE_THRESH_MEAN_C, CV_THRESH_, 3, 5);
}
if (doCanny) {
cvCanny(grayImg.getCvImage(), grayImg.getCvImage(), cannyThres1, cannyThres2, 3);
}
//cvCanny5grayImg.getCvImage(),grayImg.getCvImage(), 120, 180, 3);
//cvSobel(grayImg.getCvImage(), grayImg.getCvImage(), 1, 1, 3);
if (doCircles) {
CvMemStorage* storage = cvCreateMemStorage(0);
circles = cvHoughCircles(grayImg.getCvImage(), storage, CV_HOUGH_GRADIENT, 2, grayImg.getHeight()/4, circleEdgeThres, circleAccThres, circleMinRadius, circleMaxRadius);
}
if (doContours) {
contourFinder.findContours(grayImg, 10, (camWidth*camHeight)/2, 20, false, true);
}
}
}
void detectPupils(IplImage *img)
{
//cvShowImage("Eyes before", img);
//setting up the grayscale image
IplImage* gray = cvCreateImage( cvGetSize(img), 8, 1 );
IplImage* copy = cvCreateImage( cvGetSize(img), 8, 3 );
//IplImage* src = cvCreateImage(cvGetSize(img), 8, 1);
//set up circle storage
CvMemStorage* storage = cvCreateMemStorage(0);
//prepair the grayscale image
cvCvtColor( img, gray, CV_RGB2GRAY );
//cvCopy(img, copy);
/*try close elipse start*/
///cvThreshold(gray, gray, 30, 255, CV_THRESH_BINARY_INV);
cvShowImage("Eyes before", gray);
//IplConvKernel elipse = *cvCreateStructuringElementEx(3, 3, 0, 0, CV_SHAPE_ELLIPSE, 0);
//cvMorphologyEx(gray, gray, copy, &elipse, CV_MOP_CLOSE, 2);
/*try close elipse end */
//cvThreshold(gray, gray, 42, 255, CV_THRESH_BINARY_INV);
//cvAdaptiveThreshold(gray, gray, 255);
cvConvertScaleAbs(gray, gray, 4, -3);
cvSmooth( gray, gray, CV_GAUSSIAN, 9, 9); // smooth it, otherwise a lot of false circles may be detected
//cvCanny(gray, gray, 0, canny2, canny3);
//cvThreshold(gray, gray, 200, 255, CV_THRESH_BINARY);
//apply Hough
CvSeq* circles = cvHoughCircles( gray, storage, CV_HOUGH_GRADIENT, dp, 10, param1, param2, 0, gray->height/3);
//loop through circles
for(int i = 0; i < circles->total; i++)
{
float* circle = (float*)cvGetSeqElem( circles, i );
cvCircle( img, cvPoint(cvRound(circle[0]),cvRound(circle[1])), cvRound(circle[2]), CV_RGB(0,255,0), 1, 8, 0 );
}
cvShowImage("Eyes", gray);
//std::cerr << "Circles: " << circles->total << std::endl;
}
void houghCallBack(int pos){
if ( pos ){
IplImage *hsv = convertRGB2HSV(src);
if ( hsv ){
IplImage *thresholded = cvCreateImage(cvGetSize(src),src->depth,1);
CvScalar hsv_min = cvScalar(hue_min_value, sat_min_value, val_min_value);
CvScalar hsv_max = cvScalar(hue_max_value, sat_max_value, val_max_value);
cvInRangeS(hsv,hsv_min,hsv_max,thresholded);
//cvSaveImage("thresholded.jpg",thresholded);
CvMemStorage *storage = cvCreateMemStorage(0);
CvSeq* circles = cvHoughCircles(thresholded,storage,CV_HOUGH_GRADIENT,2,hough_minDist_value,hough_param1_value,hough_param2_value,hough_minRadius_value,hough_maxRadius_value);
printf("found %d circles\n",circles->total);
int i;
for ( i=0; i<circles->total; i++ ){
float *p = (float*)cvGetSeqElem(circles,i);
printf("\tcircle%d x:%f y:%f r:%f\n",i,p[0],p[1],p[2]);
cvCircle(hsv,cvPoint(cvRound(p[0]),cvRound(p[1])),cvRound(p[2]),CV_RGB(255,0,0),3,8,0);
}
cvNamedWindow("Hough");
cvShowImage("Hough",hsv);
cvNamedWindow("thresholdedByHSV");
cvShowImage("thresholdedByHSV",thresholded);
//cvSaveImage("result.jpg",src_backup);
printf("enter some key to kill Hough result...\n");
cvWaitKey();
cvDestroyWindow("thresholdedByHSV");
cvDestroyWindow("Hough");
cvReleaseImage(&hsv);
cvReleaseImage(&thresholded);
}
}
}
int main(int argc, char** argv) {
IplImage* image = cvLoadImage(
"4.jpg"
);
//IplImage* src = cvLoadImage("index.jpg");
IplImage* croped=cvCreateImage( cvGetSize(image), IPL_DEPTH_8U, 1 );
IplImage* src = cvCreateImage( cvGetSize(image), IPL_DEPTH_8U, 1 );
IplImage* canny=cvCreateImage(cvGetSize(image),IPL_DEPTH_8U,1);
IplImage* rgbcanny=cvCreateImage(cvGetSize(image),IPL_DEPTH_8U,3);
CvMemStorage* storage = cvCreateMemStorage(0);
cvCvtColor( image, src, CV_BGR2GRAY );
cvSmooth(src, src, CV_GAUSSIAN, 5, 5 );
//cvCanny(src,canny,50,200,3);
CvSeq* results = cvHoughCircles(
src,
storage,
CV_HOUGH_GRADIENT,
2,
src->height/4,
200,
100
//src->height/20,
//src->height/2
);
cvCvtColor(canny,rgbcanny,CV_GRAY2BGR);
printf("%d",results->total);
for( int i = 0; i < results->total; i++ )
{
float* p = (float*) cvGetSeqElem( results, i );
CvPoint pt = cvPoint( cvRound( p[0] ), cvRound( p[1] ) );
croped=crop(image,pt,cvRound(p[2]));
cvCircle(
image,
pt,
cvRound( p[2] ),
CV_RGB(255,0,0)
);
}
cvNamedWindow( "HoughCircles", 1 );
cvShowImage( "HoughCircles", image);
if(croped){
cvNamedWindow("crop",1);
cvShowImage("crop",croped);}
cvWaitKey(0);
}
int main(int argc, char** argv) {
cvNamedWindow("image");
IplImage * src = cvLoadImage("../cvtest/7newsample.jpg", 0);
IplImage * temp = cvCreateImage(cvGetSize(src), 8,1);
IplImage * img=cvCreateImage(cvGetSize(src), 8, 1);
cvCopyImage(src,temp);
cvCopyImage(src, img);
cvSmooth(img,img);
IplConvKernel *element = 0; //定义形态学结构指针
element = cvCreateStructuringElementEx(3,3, 1, 1, CV_SHAPE_ELLIPSE, 0);//3,5,7
cvErode( src, src, element);
//形态梯度
cvMorphologyEx(
src,
img,
img,
element,//NULL, //default 3*3
CV_MOP_GRADIENT,
1);
cvShowImage("image", img);
cvWaitKey(0);
IplImage* image=img; //= cvLoadImage( "../cvtest/7newsample.jpg", CV_LOAD_IMAGE_GRAYSCALE );
IplImage* src2 =img;//= cvLoadImage( "../cvtest/7newsample.jpg"); //Changed for prettier show in color
CvMemStorage* storage = cvCreateMemStorage(0);
cvSmooth(image, image, CV_GAUSSIAN, 5, 5 );
CvSeq* results = cvHoughCircles(
image,
storage,
CV_HOUGH_GRADIENT,
4,
image->width/10
);
for( int i = 0; i < results->total; i++ ) {
float* p = (float*) cvGetSeqElem( results, i );
CvPoint pt = cvPoint( cvRound( p[0] ), cvRound( p[1] ) );
cvCircle(
src2,
pt,
cvRound( p[2] ),
CV_RGB(0xff,0,0)
);
}
cvNamedWindow( "cvHoughCircles", 1 );
cvShowImage( "cvHoughCircles", src2);
cvWaitKey(0);
}
int main(int argc, char** argv) {
IplImage* image = cvLoadImage(argv[1], CV_LOAD_IMAGE_GRAYSCALE);
IplImage* src = cvLoadImage(argv[1]); //Changed for prettier show in color
CvMemStorage* storage = cvCreateMemStorage(0);
cvSmooth(image, image, CV_GAUSSIAN, 5, 5);
CvSeq* results = cvHoughCircles(image, storage, CV_HOUGH_GRADIENT, 4,
image->width / 10);
for (int i = 0; i < results->total; i++) {
float* p = (float*) cvGetSeqElem(results, i);
CvPoint pt = cvPoint(cvRound(p[0]), cvRound(p[1]));
cvCircle(src, pt, cvRound(p[2]), CV_RGB(0xff,0,0));
}
cvNamedWindow("cvHoughCircles", 1);
cvShowImage("cvHoughCircles", src);
cvWaitKey(0);
}
vector <Ball> getBalls(Mat img_in){
vector<Ball> balls;
IplImage* img_in1 = new IplImage(img_in);
CvMemStorage* storage = cvCreateMemStorage(0);
// hough detector works better with some smoothing of the image
cvSmooth( img_in1,img_in1, CV_GAUSSIAN, 9, 9 );
// Element to define dilation shape (basically a matrix)
IplConvKernel* element = cvCreateStructuringElementEx(9,9, 4, 4, CV_SHAPE_ELLIPSE);
// Suurenda veits palli (valgeid alasid)
cvDilate(img_in1, img_in1 ,element , 4);
CvSeq* circles = cvHoughCircles(img_in1, storage, CV_HOUGH_GRADIENT, 2,
img_in1->height/4, 100, 50, 10, 400);
for (int i = 0; i < circles-> total; i++)
{
float* p = (float*)cvGetSeqElem( circles, i );
printf("Ball! x=%f y=%f r=%f\n\r" ,p[0],p[1],p[2] );
Ball current_ball = Ball(p[0],p[1],p[2]);
cout << " X, Y radiaanides " << current_ball.getX_degR() <<" "<< current_ball.getY_degR() << endl;
balls.push_back(current_ball);
circle( img_in, cvPoint(cvRound(p[0]),cvRound(p[1])),
3, CV_RGB(255,255,0), -1, 8, 0 );
circle( img_in, cvPoint(cvRound(p[0]),cvRound(p[1])),
cvRound(p[2]), CV_RGB(255,0,0), 3, 8, 0 );
}
sort(balls.begin(),balls.end());
return balls;
}
CvSeq* HoughCircle::locateHoughCircles(IplImage* img,double min_distance, double upperThreshold, double accumulatorThreshold, double min_radius, double max_radius ){
//IplImage* gray = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 1);
//storage = cvCreateMemStorage(0);
IplImage* gray=cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 1);
CvMemStorage* storage = cvCreateMemStorage(0);
cvCvtColor( img, gray, CV_BGR2GRAY );
// cvShowImage("Gray",gray);
// cvEqualizeHist(gray,gray);
// cvShowImage("Hist Eq Gray",gray);
CvSeq* circle = cvHoughCircles( gray, storage, CV_HOUGH_GRADIENT, 2, min_distance, upperThreshold, accumulatorThreshold, min_radius, max_radius);
cvReleaseImage(&gray);
cvReleaseMemStorage(&storage);
return circle;
}
void drawCircleAndCrop(char *pFileName, IplImage* img)
{
IplImage* cpy = cvCloneImage( img );
IplImage* gray = cvCreateImage( cvGetSize(img), 8, 1 );
cvCvtColor( img, gray, CV_BGR2GRAY );
cvSmooth( gray, gray, CV_GAUSSIAN, 9, 9 );
CvMemStorage* storage = cvCreateMemStorage(0);
CvSeq* circles = cvHoughCircles(gray, storage, CV_HOUGH_GRADIENT, 2, gray->height/4, 200, 200);
int i;
for( i = 0; i < circles->total; i++ )
{
float* p = (float*)cvGetSeqElem( circles, i );
cvCircle( gray, cvPoint(cvRound(p[0]),cvRound(p[1])), 3, CV_RGB(0,255,0), -1, 8, 0 );
cvCircle( gray, cvPoint(cvRound(p[0]),cvRound(p[1])), cvRound(p[2]), CV_RGB(255,0,0), 3, 8, 0 );
}
// show the resultant image
cvShowImage( wndname, gray );
cvReleaseImage(&cpy);
cvReleaseImage(&gray);
}
int mapFunction::circleDetect(Mat image1){
IplImage* img = new IplImage(image1);
IplImage* gray = cvCreateImage( cvGetSize(img), img->depth, 1);
CvMemStorage* storage = cvCreateMemStorage(0);
cvCvtColor( img, gray, CV_RGB2GRAY );
//cvSmooth( gray, gray, CV_GAUSSIAN, 9, 9 );
CvSeq* circles = cvHoughCircles( gray, storage, CV_HOUGH_GRADIENT, 2, gray->height/4, 200, 100);
/*for (int i = 0; i < circles->total; i++)
{
float* p = (float*)cvGetSeqElem( circles, i );
cvCircle( img, cvPoint(cvRound(p[0]),cvRound(p[1])),
3, CV_RGB(0,255,0), -1, 8, 0 );
cvCircle( img, cvPoint(cvRound(p[0]),cvRound(p[1])),
cvRound(p[2]), CV_RGB(255,0,0), 3, 8, 0 );
}
cvNamedWindow( "circles", 1 );
cvShowImage( "circles", img );
waitKey(0);*/
if(circles->total==0) return 0;
else return 1;
}
int main(int argc, char* argv[])
{
// Default capture size - 640x480
CvSize size = cvSize(640,480);
// Open capture device. 0 is /dev/video0, 1 is /dev/video1, etc.
CvCapture* capture = cvCaptureFromCAM( 0 );
if( !capture )
{
fprintf( stderr, "ERROR: capture is NULL \n" );
getchar();
return -1;
}
// Create a window in which the captured images will be presented
cvNamedWindow( "Camera", CV_WINDOW_AUTOSIZE );
cvNamedWindow( "HSV", CV_WINDOW_AUTOSIZE );
cvNamedWindow( "EdgeDetection", CV_WINDOW_AUTOSIZE );
// Detect a red ball
int hl = 60, hu = 75, sl = 255, su = 256, vl = 170, vu = 256;
IplImage * hsv_frame = cvCreateImage(size, IPL_DEPTH_8U, 3);
IplImage* thresholded = cvCreateImage(size, IPL_DEPTH_8U, 1);
while( 1 )
{
// Get one frame
IplImage* frame = cvQueryFrame( capture );
if( !frame )
{
fprintf( stderr, "ERROR: frame is null...\n" );
getchar();
break;
}
CvScalar hsv_min = cvScalar(hl, sl, vl, 0);
CvScalar hsv_max = cvScalar(hu, su, vu, 0);
// Covert color space to HSV as it is much easier to filter colors in the HSV color-space.
cvCvtColor(frame, hsv_frame, CV_RGB2HSV);
// Filter out colors which are out of range.
cvInRangeS(hsv_frame, hsv_min, hsv_max, thresholded);
// Memory for hough circles
CvMemStorage* storage = cvCreateMemStorage(0);
// hough detector works better with some smoothing of the image
cvDilate(thresholded, thresholded, NULL, 3);
cvSmooth( thresholded, thresholded, CV_GAUSSIAN, 9, 9 );
cvErode(thresholded, thresholded, NULL, 3);
CvSeq* circles = cvHoughCircles(thresholded, storage, CV_HOUGH_GRADIENT, 1,
thresholded->height/4, 400, 10, 20, 400);
int maxRadius = 0;
int x = 0, y = 0;
bool found = false;
for (int i = 0; i < circles->total; i++)
{
float* p = (float*)cvGetSeqElem( circles, i );
if (p[2] > maxRadius){
maxRadius = p[2];
x = p[0];
y = p[1];
found = true;
}
}
if (found){
//printf("Ball! x=%f y=%f r=%f\n\r",p[0],p[1],p[2] );
cvCircle( frame, cvPoint(cvRound(x),cvRound(y)),
3, CV_RGB(0,255,0), -1, 8, 0 );
cvCircle( frame, cvPoint(cvRound(x),cvRound(y)),
cvRound(maxRadius), CV_RGB(255,0,0), 3, 8, 0 );
}
cvShowImage( "Camera", frame ); // Original stream with detected ball overlay
cvShowImage( "HSV", hsv_frame); // Original stream in the HSV color space
cvShowImage( "After Color Filtering", thresholded ); // The stream after color filtering
cvReleaseMemStorage(&storage);
// Do not release the frame!
//If ESC key pressed, Key=0x10001B under OpenCV 0.9.7(linux version),
//remove higher bits using AND operator
int key = cvWaitKey(10);
switch(key){
case 'q' : hu += 5; break;
case 'Q' : hu -= 5; break;
case 'a' : hl -= 5; break;
case 'A' : hl += 5; break;
case 'w' : su += 5; break;
case 'W' : su -= 5; break;
case 's' : sl -= 5; break;
case 'S' : sl += 5; break;
case 'e' : vu += 5; break;
case 'E' : vu -= 5; break;
case 'd' : vl -= 5; break;
case 'D' : vl += 5; break;
}
if (key != -1){
printf("H: %i, S: %i, V: %i\nH: %i, S: %i, V: %i\n\n", hu, su, vu, hl, sl, vl);
}
}
// Release the capture device housekeeping
cvReleaseCapture( &capture );
cvDestroyWindow( "mywindow" );
return 0;
}
void process_image(){
///////////////////////////////////////////////////////
//////////////////// PUPIL/////////////////////////////
///////////////////////////////////////////////////////
int numBins = 256;
float range[] = {0, 255};
float *ranges[] = { range };
CvHistogram *hist = cvCreateHist(1, &numBins, CV_HIST_ARRAY, ranges, 1);
cvClearHist(hist);
cvCalcHist(&smooth, hist, 0, 0);
IplImage* imgHist = DrawHistogram(hist,1,1);
cvClearHist(hist);
//cvShowImage("hist", imgHist);
cvThreshold(smooth,pupil,50,255,CV_THRESH_BINARY);
//cvShowImage( "pupi_binary",pupil);
cvCanny(pupil,pedge,40,50);
//cvShowImage( "pupil_edge",pedge);
//////////////////////////////////////////////////////////
//////////////////////IRIS////////////////////////////////
//////////////////////////////////////////////////////////
//cvEqualizeHist(smooth,smooth);
//cvShowImage("Equalized",smooth);
cvThreshold(smooth,iris,100,255,CV_THRESH_BINARY); //115
//cvShowImage( "iris_binary",iris);
//cvSobel(iris,iedge,1,0,3);
cvCanny(iris,iedge,1,255);
//cvShowImage( "iris_edge",iedge);
/////////////////////////////////////////////////////////
///////////////////////Eyelids///////////////////////////
/////////////////////////////////////////////////////////
cvThreshold(smooth,eyelid_mask,150,255,CV_THRESH_OTSU);
cvNot(eyelid_mask,eyelid_mask);
//cvShowImage("eyelid",eyelid_mask);
//cvAdaptiveThreshold(smooth,contour,255,CV_ADAPTIVE_THRESH_MEAN_C,CV_THRESH_BINARY,9,1);
//cvThreshold(smooth,contour,130,255,CV_THRESH_BINARY);
//cvShowImage( "contour",contour);
//CvSeq* firstContour = NULL;
//CvMemStorage* cstorage = cvCreateMemStorage(0);
//cvFindContours(con, cstorage, &firstContour,sizeof(CvContour), CV_RETR_LIST,CV_CHAIN_APPROX_SIMPLE);
//cvDrawContours(dst,firstContour,CV_RGB(0,255,0),CV_RGB(0,0,255),10,2,8);
CvMemStorage* storage_pupil = cvCreateMemStorage(0);
CvSeq* presults = cvHoughCircles(pedge,storage_pupil,CV_HOUGH_GRADIENT,2,src->width,255,1);
for( int i = 0; i < presults->total; i++ )
{
float* p = (float*) cvGetSeqElem( presults, i );
CvPoint pt = cvPoint( cvRound( p[0] ),cvRound( p[1] ) );
xp=cvRound( p[0] );
yp=cvRound( p[1] );
rp=p[2];
cvCircle(dst,pt,cvRound( p[2] ),CV_RGB(0,255,255),1,400);
xroi= xp-shift;
yroi= yp-shift;
cvRectangle(dst,cvPoint(( p[0] )-shift,p[1]-shift),cvPoint(( p[0] )+shift,p[1]+shift),CV_RGB(255,0,255), 1);
CvRect roi= cvRect(xroi ,yroi,shift*2,shift*2);
cvSetImageROI( iedge, roi );
//cvShowImage("ROI",iedge);
}
////////////////////////////////////////////////////////////
///////////////////////////////////////////////////////////
///////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////
CvMemStorage* storage_iris = cvCreateMemStorage(0);
CvSeq* iresults = cvHoughCircles(iedge,storage_iris,CV_HOUGH_GRADIENT,2,src->width,1,50,50);
for( int i = 0; i < iresults->total; i++ )
{
float* p = (float*) cvGetSeqElem( iresults, i );
CvPoint pt = cvPoint( cvRound( p[0] )+xroi,cvRound( p[1] )+yroi );
cvCircle(dst,pt,cvRound( p[2] ),CV_RGB(255,0,0),1,400);
xi=cvRound( p[0] )+xroi;
yi=cvRound( p[1] )+yroi;
ri=(p[2]);
cvCircle(iris_mask,pt,cvRound( p[2] ),CV_RGB(255, 255, 255),-1, 8, 0);
//cvShowImage("iris_mask",iris_mask);
}
///////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////
///////////////////////////////////////////
cvResetImageROI(iedge);
cvAnd(dst,dst,res,iris_mask);
//cvShowImage("iris_mask",res);
cvAnd(res,res, mask, eyelid_mask);
//cvShowImage("Mask",mask);
//cvLogPolar(mask,finalres,cvPoint2D32f (xp,yp),100, CV_INTER_LINEAR );
//cvShowImage("Final Result",finalres);
/////////////////////////////////////////////////////////
/////////////////////////////////////////////////////////
/////////////////////////////////////////////////////////
/*
*/
}
void testApp::houghCircles( ofxCvGrayscaleImage sourceImg) {
IplImage* gray = sourceImg.getCvImage();
cvSmooth( gray, gray, CV_GAUSSIAN, 5, 5 ); // smooth it, otherwise a lot of false circles may be detected
CvMemStorage* storage = cvCreateMemStorage(0);
circles = cvHoughCircles(gray, storage, CV_HOUGH_GRADIENT, 2, gray->width/8, 300, 200 );
circCount = circles->total;
// find positions of CV circles
for (int i = 0; i < circles->total; i++)
{
float* p = (float*)cvGetSeqElem( circles, i );
ofPoint pos;
pos.x = cvPoint( cvRound(p[0]),cvRound(p[1]) ).x;
pos.y = cvPoint( cvRound(p[0]),cvRound(p[1]) ).y;
pos.x = (int)pos.x;
pos.y = (int)pos.y;
int radius = cvRound( p[2] );
bool cFound = false;
for (int circs = 0; circs < myCircles.size(); circs++)
{
ofPoint& posCirc = myCircles[circs].pos;
float dist = ofDistSquared(pos.x, pos.y, posCirc.x, posCirc.y);
//cout << "distance is: " << dist << endl;
// check to see if there is a circle near an existing tracked circle
if ( dist < 1000 )
{
myCircles[circs].lastSeen = ofGetFrameNum();
myCircles[circs].radius = radius;
myCircles[circs].pos = pos;
myCircles[circs].isAlive += 1;
cFound = true;
}
}
if (!cFound)
{
radius *=1.05;
CircleTrack c = CircleTrack( pos );
c.pos = pos;
c.radius = radius;
c.lastSeen = ofGetFrameNum();
c.isAlive = 0;
c.drawMe = false;
c.isSetUp = false;
c.iD = circID;
if (c.radius) {
myCircles.push_back(c);
circID++;
ofPixels pixCopy = pix;
pixCopy.crop( pos.x-radius, (pos.y-radius), radius*2 , radius*2 );
tex.loadData( pixCopy );
ofTexture T;
T.allocate(radius*2,radius*2, GL_RGB);
T.loadData(pixCopy);
particle P = particle( pos,circID,radius,T );
punched.push_back( P );
printf("punched %f,%f\n", pos.x,pos.y);
}
}
}
cvReleaseMemStorage(&storage);
for ( int x = 0; x<myCircles.size(); x++ )
{
bool isSetupNow = myCircles[x].isSetUp;
if ( !isSetupNow ) {
myCircles[x].setup();
}
}
vector<CircleTrack>::iterator iter = myCircles.begin();
while (iter != myCircles.end()) {
double life = iter->lastSeen;
int isAlive = iter->isAlive;
// kill old particles;
if ( (ofGetFrameNum()-life) > 50 )
{
ofPoint tracePos = iter->pos;
iter = myCircles.erase(iter);
cout << "shape deleted at: "<< tracePos.x << ", " << tracePos.y << endl;
} else {
if (iter->isAlive > 0) // used to be 3?
{
iter->drawMe = true;
} else
{
iter->drawMe = false;
}
iter++;
}
}
}
void Run()
{
int w, h;
IplImage *pCapImage;
PBYTE pCapBuffer = NULL;
// Create camera instance
_cam = CLEyeCreateCamera(_cameraGUID, _mode, _resolution, _fps);
if(_cam == NULL) return;
// Get camera frame dimensions
CLEyeCameraGetFrameDimensions(_cam, w, h);
// Depending on color mode chosen, create the appropriate OpenCV image
if(_mode == CLEYE_COLOR_PROCESSED || _mode == CLEYE_COLOR_RAW)
pCapImage = cvCreateImage(cvSize(w, h), IPL_DEPTH_8U, 4);
else
pCapImage = cvCreateImage(cvSize(w, h), IPL_DEPTH_8U, 1);
// Set some camera parameters
//CLEyeSetCameraParameter(_cam, CLEYE_GAIN, 30);
//CLEyeSetCameraParameter(_cam, CLEYE_EXPOSURE, 500);
//CLEyeSetCameraParameter(_cam, CLEYE_AUTO_EXPOSURE, false);
//CLEyeSetCameraParameter(_cam, CLEYE_AUTO_GAIN, false);
//CLEyeSetCameraParameter(_cam, CLEYE_AUTO_WHITEBALANCE, false);
//CLEyeSetCameraParameter(_cam, CLEYE_WHITEBALANCE_RED, 100);
//CLEyeSetCameraParameter(_cam, CLEYE_WHITEBALANCE_BLUE, 200);
//CLEyeSetCameraParameter(_cam, CLEYE_WHITEBALANCE_GREEN, 200);
// Start capturing
CLEyeCameraStart(_cam);
CvMemStorage* storage = cvCreateMemStorage(0);
IplImage* hsv_frame = cvCreateImage(cvSize(pCapImage->width, pCapImage->height), IPL_DEPTH_8U, 3);
IplImage* thresholded = cvCreateImage(cvSize(pCapImage->width, pCapImage->height), IPL_DEPTH_8U, 1);
IplImage* temp = cvCreateImage(cvSize(pCapImage->width >> 1, pCapImage->height >> 1), IPL_DEPTH_8U, 3);
// Create a window in which the captured images will be presented
cvNamedWindow( "Camera" , CV_WINDOW_AUTOSIZE );
cvNamedWindow( "HSV", CV_WINDOW_AUTOSIZE );
cvNamedWindow( "EdgeDetection", CV_WINDOW_AUTOSIZE );
//int hl = 100, hu = 115, sl = 95, su = 135, vl = 115, vu = 200;
int hl = 5, hu = 75, sl = 40, su = 245, vl = 105, vu = 175;
// image capturing loop
while(_running)
{
// Detect a red ball
CvScalar hsv_min = cvScalar(hl, sl, vl, 0);
CvScalar hsv_max = cvScalar(hu, su, vu, 0);
cvGetImageRawData(pCapImage, &pCapBuffer);
CLEyeCameraGetFrame(_cam, pCapBuffer);
cvConvertImage(pCapImage, hsv_frame);
// Get one frame
if( !pCapImage )
{
fprintf( stderr, "ERROR: frame is null...\n" );
getchar();
break;
}
// Covert color space to HSV as it is much easier to filter colors in the HSV color-space.
cvCvtColor(pCapImage, hsv_frame, CV_RGB2HSV);
// Filter out colors which are out of range.
cvInRangeS(hsv_frame, hsv_min, hsv_max, thresholded);
// Memory for hough circles
CvMemStorage* storage = cvCreateMemStorage(0);
// hough detector works better with some smoothing of the image
cvSmooth( thresholded, thresholded, CV_GAUSSIAN, 9, 9 );
CvSeq* circles = cvHoughCircles(thresholded, storage, CV_HOUGH_GRADIENT, 2,
thresholded->height/4, 100, 50, 10, 400);
for (int i = 0; i < circles->total; i++)
{
float* p = (float*)cvGetSeqElem( circles, i );
//printf("Ball! x=%f y=%f r=%f\n\r",p[0],p[1],p[2] );
cvCircle( pCapImage, cvPoint(cvRound(p[0]),cvRound(p[1])),
3, CV_RGB(0,255,0), -1, 8, 0 );
cvCircle( pCapImage, cvPoint(cvRound(p[0]),cvRound(p[1])),
cvRound(p[2]), CV_RGB(255,0,0), 3, 8, 0 );
}
cvShowImage( "Camera", pCapImage ); // Original stream with detected ball overlay
cvShowImage( "HSV", hsv_frame); // Original stream in the HSV color space
cvShowImage( "EdgeDetection", thresholded ); // The stream after color filtering
cvReleaseMemStorage(&storage);
// Do not release the frame!
//If ESC key pressed, Key=0x10001B under OpenCV 0.9.7(linux version),
//remove higher bits using AND operator
int key = cvWaitKey(10);
switch(key){
case 'q' : hu += 5; break;
case 'Q' : hu -= 5; break;
case 'a' : hl -= 5; break;
case 'A' : hl += 5; break;
case 'w' : su += 5; break;
case 'W' : su -= 5; break;
case 's' : sl -= 5; break;
case 'S' : sl += 5; break;
case 'e' : vu += 5; break;
case 'E' : vu -= 5; break;
case 'd' : vl -= 5; break;
case 'D' : vl += 5; break;
}
if (key != -1){
printf("H: %i, S: %i, V: %i\nH: %i, S: %i, V: %i\n\n", hu, su, vu, hl, sl, vl);
}
}
cvReleaseImage(&temp);
cvReleaseImage(&pCapImage);
// Stop camera capture
CLEyeCameraStop(_cam);
// Destroy camera object
CLEyeDestroyCamera(_cam);
// Destroy the allocated OpenCV image
cvReleaseImage(&pCapImage);
_cam = NULL;
}
int main(int argc, char* argv[])
{
int i;
CvSize size = cvSize(640,480);
CvCapture* capture = cvCaptureFromCAM(0);
if(!capture)
{
fprintf(stderr, "Error in opening the Camera.\n");
exit(1);
}
cvSetCaptureProperty(capture, CV_CAP_PROP_FRAME_WIDTH, 640);
cvSetCaptureProperty(capture, CV_CAP_PROP_FRAME_HEIGHT, 480);
cvNamedWindow("Camera", CV_WINDOW_AUTOSIZE);
cvNamedWindow("HSV", CV_WINDOW_AUTOSIZE);
cvNamedWindow("Thresholded", CV_WINDOW_AUTOSIZE);
IplImage* frame = cvQueryFrame(capture);
if(!frame)
exit(1);
IplImage* hsv = cvCreateImage(size, IPL_DEPTH_8U, 3);
IplImage* thresholded = cvCreateImage(size, IPL_DEPTH_8U, 1);
CvScalar hsv_min = cvScalar(170, 120, 100, 0);
CvScalar hsv_max = cvScalar(358, 256, 256, 0);
int xpre = 0, ypre = 0;
while(1)
{
frame = cvQueryFrame(capture);
if(!frame)
{
fprintf(stderr, "Failed to capture an Image.\n");
break;
}
cvCvtColor(frame, hsv, CV_BGR2HSV);
cvInRangeS(hsv, hsv_min, hsv_max, thresholded);
cvSmooth(thresholded, thresholded, CV_GAUSSIAN, 9,9,0,0);
CvMemStorage* storage = cvCreateMemStorage(0);
CvSeq* circles = cvHoughCircles(thresholded, storage, CV_HOUGH_GRADIENT, 2,thresholded->height/4, 100, 50, 40, 400);
/*The entire code lies in this line, This function detects the actual circles in the image. The parameters are as follows:
thresholded - input image
storage - memory storage that stores location of circles
CV_HOUGH_GRADIENT - method used to detect circles(only one present)
2(dp) - Resolution for the detection, more the better
(thresholded->height)/4(minDist) - Minimum Distance between the circles
100(param1) - For the Canny Edge Detection
50(param2) - For the Canny Edge Detection
10(minRadius) - Minimum radius of Circle
400(maxRadius) - Maximum radius of Circle
Link Followed for above information - http://www.emgu.com/wiki/files/1.3.0.0/html/0ac8f298-48bc-3eee-88b7-d2deed2a285d.htm
*/
for(i = 0;i<circles->total;i++)
{
float* p = (float*)cvGetSeqElem( circles, i );
printf("Ball! x=%f y=%f r=%f\n\r",p[0],p[1],p[2] );
if(xpre == 0 && ypre == 0)
{
xpre = p[0];
ypre = p[1];
cvCircle( frame, cvPoint(cvRound(p[0]),cvRound(p[1])), 3, CV_RGB(0,255,0), -1, 8, 0 );
cvCircle( frame, cvPoint(cvRound(p[0]),cvRound(p[1])), cvRound(p[2]), CV_RGB(255,0,0), 3, 8, 0 );
}
else
{
if((abs(p[0] - xpre) < 100) && (abs(p[1] - ypre) < 100))
{
cvCircle( frame, cvPoint(cvRound(p[0]),cvRound(p[1])), 3, CV_RGB(0,255,0), -1, 8, 0 );
cvCircle( frame, cvPoint(cvRound(p[0]),cvRound(p[1])), cvRound(p[2]), CV_RGB(255,0,0), 3, 8, 0 );
}
else;
}
xpre = p[0];
ypre = p[1];
}
/*cvGetSeqElem(circles,i) - This gets each sequence element form the memory storage and puts in the pointer p. Now p has three variables
(p[0],p[1]) - (x,y) coordinates of circle
p[2] - radius of the circle
Link Followed - http://opencv.willowgarage.com/documentation/dynamic_structures.html
*/
cvShowImage("Camera", frame);
cvShowImage("HSV", hsv);
cvShowImage("Thresholded", thresholded);
char c=cvWaitKey(33);
if(c == 27)
break;
}
cvDestroyAllWindows();
cvReleaseCapture(&capture);
cvReleaseImage(&frame);
cvReleaseImage(&hsv);
}
int run(const char *serverAddress, const int serverPort, char headless)
{
int i, sockfd, show = ~0;
int frames = 0;
int returnValue = EXIT_SUCCESS;
CvCapture *capture;
CvMemStorage *storage;
IplImage *grabbedImage;
IplImage *imgThreshold;
CvSeq *seq;
CvFont font;
SendQueue *queue;
char strbuf[255];
struct timeval oldTime, time, diff;
float lastKnownFPS = 0;
sockfd = initNetwork(serverAddress, serverPort);
if (sockfd == -1) {
fprintf(stderr, "ERROR: initNetwork returned -1\n");
return EXIT_FAILURE;
}
queue = initSendQueue();
capture = cvCaptureFromCAM(CV_CAP_ANY);
if (capture == NULL) {
fprintf( stderr, "ERROR: capture is NULL \n" );
getchar();
return EXIT_FAILURE;
}
// Create a window in which the captured images will be presented
cvNamedWindow("mywindow", CV_WINDOW_AUTOSIZE);
storage = cvCreateMemStorage(0);
// void cvInitFont(font, font_face, hscale, vscale, shear=0, thickness=1, line_type=8 )
cvInitFont(&font, CV_FONT_HERSHEY_PLAIN, 1, 1, 0, 1, 8);
gettimeofday(&oldTime, NULL);
// Show the image captured from the camera in the window and repeat
while (1) {
cvClearMemStorage(storage);
grabbedImage = cvQueryFrame(capture);
if (grabbedImage == NULL) {
fprintf( stderr, "ERROR: frame is null...\n" );
getchar();
returnValue = EXIT_FAILURE;
break;
}
//Create detection image
imgThreshold = cvCreateImage(cvGetSize(grabbedImage), 8, 1);
cvInRangeS(grabbedImage, min, max, imgThreshold);
//Flip images to act as a mirror.
//TODO remove when camera faces screen
if (show) {
cvFlip(grabbedImage, grabbedImage, 1);
cvFlip(imgThreshold, imgThreshold, 1);
}
//Find all dots in the image. This is where any calibration of dot detection is done, if needed, though it
//should be fine as it is right now.
/*
* image, circleStorage, method, double dp, double minDist, double param1, double param2, int minRadius, int maxRadius
*/
seq = cvHoughCircles(imgThreshold, storage, CV_HOUGH_GRADIENT, 2, 20, 20, 2, 0, 10);
for (i = 0; i < seq->total; i++){
// Get point
float *p = (float*)cvGetSeqElem(seq, i);
//Draw current circle to the original image
if (show) paintCircle(p, grabbedImage);
//Buffer current circle to be sent to the server
addPointToSendQueue(p, queue);
}
//Print some statistics to the image
if (show) {
snprintf(strbuf, sizeof(strbuf), "Dots: %i", seq->total);
cvPutText(grabbedImage, strbuf, cvPoint(10, 20), &font, cvScalar(WHITE));
snprintf(strbuf, sizeof(strbuf), "FPS: %.1f", lastKnownFPS);
cvPutText(grabbedImage, strbuf, cvPoint(10, 200), &font, cvScalar(WHITE));
}
//Show images
//TODO Comment these out will probably improve performance quite a bit
if (show) {
cvShowImage("mywindow", imgThreshold);
cvShowImage("mywindow", grabbedImage);
}
gettimeofday(&time, NULL);
timeval_subtract(&diff, &time, &oldTime);
// printf("Frames = %i\n", diff.tv_sec);
if (diff.tv_sec >= 2) {
lastKnownFPS = (float)frames / diff.tv_sec;
oldTime = time;
frames = 0;
}
//Add one to the frame rate counter
frames++;
//Send to dots detected this frame to the server
sendQueue(sockfd, queue);
clearSendQueue(queue);
//
//If ESC key pressed, Key=0x10001B under OpenCV 0.9.7(linux version),
//remove higher bits using AND operator
i = (cvWaitKey(10) & 0xff);
if (i == 'v') show = ~show;
if (i == 27) break;
}
// Release the capture device housekeeping
cvReleaseCapture( &capture );
cvDestroyWindow( "mywindow" );
destroySendQueue(queue);
close(sockfd);
return returnValue;
}
// --------------------------------------------------------------------------
// main(Number of arguments, Argument values)
// Description : This is the entry point of the program.
// Return value : SUCCESS:0 ERROR:-1
// --------------------------------------------------------------------------
int main(int argc, char **argv)
{
// AR.Drone class
ARDrone ardrone;
// Initialize
if (!ardrone.open()) {
printf("Failed to initialize.\n");
return -1;
}
// Get a image
IplImage* image = ardrone.getImage();
// Images
IplImage *gray = cvCreateImage(cvGetSize(image), image->depth, 1);
IplImage *smooth = cvCreateImage(cvGetSize(image), image->depth, 1);
IplImage *canny = cvCreateImage(cvGetSize(image), image->depth, 1);
// Canny thresholds
int th1 = 50, th2 = 100;
cvNamedWindow("canny");
cvCreateTrackbar("th1", "canny", &th1, 255);
cvCreateTrackbar("th2", "canny", &th2, 255);
// Main loop
while (1) {
// Key input
int key = cvWaitKey(1);
if (key == 0x1b) break;
// Update
if (!ardrone.update()) break;
// Get an image
image = ardrone.getImage();
// Convert to gray scale
cvCvtColor(image, gray, CV_BGR2GRAY);
// De-noising
cvSmooth(gray, smooth, CV_GAUSSIAN, 23, 23);
// Detect edges
cvCanny(smooth, canny, th1, th2, 3);
// Detect circles
CvMemStorage *storage = cvCreateMemStorage(0);
CvSeq *circles = cvHoughCircles(smooth, storage, CV_HOUGH_GRADIENT, 1.0, 10.0, MAX(th1,th2), 20);
// Draw circles
for (int i = 0; i < circles->total; i++) {
float *p = (float*) cvGetSeqElem(circles, i);
cvCircle(image, cvPoint(cvRound(p[0]), cvRound(p[1])), cvRound(p[2]), CV_RGB(0,255,0), 3, 8, 0);
}
// Release memory
cvReleaseMemStorage(&storage);
// Change camera
static int mode = 0;
if (key == 'c') ardrone.setCamera(++mode%4);
// Display the image
cvShowImage("camera", image);
cvShowImage("canny", canny);
}
// Release memories
cvReleaseImage(&gray);
cvReleaseImage(&smooth);
cvReleaseImage(&canny);
// See you
ardrone.close();
return 0;
}
int main(int argc, char* argv[])
{
// Default capture size - 640x480<br />
CvSize size = cvSize(640,480);
// Open capture device. 0 is /dev/video0, 1 is /dev/video1, etc.
CvCapture* capture = cvCaptureFromCAM( 0 );
if( !capture )
{
fprintf( stderr, "ERROR: capture is NULL \n" );
getchar();
return -1;
}
// Create a window in which the captured images will be presented
cvNamedWindow( "Camera", CV_WINDOW_AUTOSIZE );
cvNamedWindow( "HSV", CV_WINDOW_AUTOSIZE );
cvNamedWindow( "EdgeDetection", CV_WINDOW_AUTOSIZE );
// Detect a red ball
CvScalar hsv_min = cvScalar(150, 84, 130, 0);
CvScalar hsv_max = cvScalar(358, 256, 255, 0);
IplImage* hsv_frame = cvCreateImage(size, IPL_DEPTH_8U, 3);
IplImage* thresholded = cvCreateImage(size, IPL_DEPTH_8U, 1);
while( 1 )
{
// Get one frame
IplImage* frame = cvQueryFrame( capture );
if( !frame )
{
fprintf( stderr, "ERROR: frame is null...\n" );
getchar();
break;
}
// Covert color space to HSV as it is much easier to filter colors in the HSV color-space.
cvCvtColor(frame, hsv_frame, CV_BGR2HSV);
// Filter out colors which are out of range.
cvInRangeS(hsv_frame, hsv_min, hsv_max, thresholded);
// Memory for hough circles
CvMemStorage* storage = cvCreateMemStorage(0);
// hough detector works better with some smoothing of the image
cvSmooth( thresholded, thresholded, CV_GAUSSIAN, 9, 9 );
CvSeq* circles = cvHoughCircles(thresholded, storage, CV_HOUGH_GRADIENT, 2,
thresholded->height/4, 100, 50, 10, 400);
for (int i = 0; i < circles->total; i++)
{
float* p = (float*)cvGetSeqElem( circles, i );
printf("Ball! x=%f y=%f r=%f\n\r", p[0],p[1],p[2] );
cvCircle( frame, cvPoint(cvRound(p[0]),cvRound(p[1])),
3, CV_RGB(0,255,0), -1, 8, 0 );
cvCircle( frame, cvPoint(cvRound(p[0]),cvRound(p[1])),
cvRound(p[2]), CV_RGB(255,0,0), 3, 8, 0 );
}
cvShowImage( "Camera", frame ); // Original stream with detected ball overlay
cvShowImage( "HSV", hsv_frame); // Original stream in the HSV color space
cvShowImage( "After Color Filtering", thresholded ); // The stream after color filtering</p>
cvReleaseMemStorage(&storage);
// Do not release the frame!
//If ESC key pressed, Key=0x10001B under OpenCV 0.9.7(linux version),
//remove higher bits using AND operator
if( (cvWaitKey(10) & 255) == 27 ) break;
}
// Release the capture device housekeeping
cvReleaseCapture( &capture );
cvDestroyWindow( "mywindow" );
return 0;
}
// initialize the main function
int main(int argc, char *argv[])
{
if (argc < 2)
{
printf("Usage: %s <img.jpg>\n", argv[0]);
return 1;
}
IplImage* picture = cvLoadImage(argv[1]);
IplImage* greyImg = cvCreateImage(cvGetSize(picture), IPL_DEPTH_8U, 1);
IplImage* cannyImg = cvCreateImage(cvGetSize(picture), IPL_DEPTH_8U, 1);
IplImage* drawnImg = cvCreateImage(cvGetSize(picture), IPL_DEPTH_8U, 3);
IplImage* contrastImg = cvCreateImage(cvGetSize(picture), IPL_DEPTH_8U, 1);
cvNamedWindow("Image", CV_WINDOW_AUTOSIZE);
cvNamedWindow("Canny", CV_WINDOW_AUTOSIZE);
cvNamedWindow("Threshold", CV_WINDOW_NORMAL);
cvCvtColor(picture, greyImg, CV_BGR2GRAY);
cvEqualizeHist(greyImg, greyImg);
CvMemStorage* storage = cvCreateMemStorage(0);
while (1) {
// Create trackbars
cvCopy(picture, drawnImg); // picture to be displayed
cvCreateTrackbar( "min_dist", "Image", &min_dist_switch_value, 49, switch_min_dist );
cvCreateTrackbar( "dp", "Image", &dp_switch_value, 9, switch_dp );
cvCreateTrackbar( "High", "Canny", &high_switch_value, 499, switch_callback_h );
cvCreateTrackbar( "Low", "Canny", &low_switch_value, 499, switch_callback_l );
cvCreateTrackbar( "Threshold", "Threshold", &threshold_switch_value, 199, switch_threshold );
cvCreateTrackbar( "Max", "Threshold", &threshold_max_switch_value, 500, switch_threshold_max );
int N = 7;
double dp = dpInt+1;
double min_dist = min_distInt+1;
double lowThresh = lowInt + 1;
double highTresh = highInt + 1;
double threshold = thresholdInt+1;
double threshold_max = threshold_maxInt+1;
cvThreshold(greyImg, contrastImg, threshold, threshold_max, CV_THRESH_TOZERO_INV);
cvCanny(contrastImg, cannyImg, lowThresh*N*N, highTresh*N*N, N);
// CvSeq* circles =cvHoughCircles(greyImg, storage, CV_HOUGH_GRADIENT, 35, 25);
CvSeq* circles =cvHoughCircles(cannyImg, storage, CV_HOUGH_GRADIENT, dp, min_dist);
// dp is image resolution
// min_dist is the minimum distance between circles
for (int i = 0; i < (circles ? circles->total : 0); i++)
{
float* p = (float*)cvGetSeqElem( circles, i );
cvCircle( drawnImg, cvPoint(cvRound(p[0]),cvRound(p[1])),3, CV_RGB(0,255,0), -1, 8, 0 );
}
cvShowImage("Image", drawnImg);
cvShowImage("Canny", cannyImg);
cvShowImage("Threshold", contrastImg);
char b;
while (b != 98) {
b = cvWaitKey(1);
}
b=0;
}
}
int hue_circles_detector(const sensor_msgs::ImageConstPtr&
InputImage, std::vector<Circle> &myCircles)
{
IplImage *myImage = NULL;
cv::Mat inputImage;
cv::Mat hsvImage;
cv::Mat hueImage;
cv::Mat satImage;
cv::Mat binaryImage;
cv::Mat outputImage;
sensor_msgs::CvBridge bridge;
try
{
myImage = bridge.imgMsgToCv(InputImage, "bgr8");
}
catch (sensor_msgs::CvBridgeException& e)
{
ROS_ERROR("Could not convert from '%s' to 'bgr8'.", InputImage->encoding.c_str());
return -1;
}
cvNamedWindow("Input to hue circles detector");
cvNamedWindow("Circles");
cvNamedWindow("Working image");
cvStartWindowThread();
cvShowImage("Input to hue circles detector", myImage);
IplImage* CirclesImage = cvCloneImage(myImage); // just used to display our found circles
// create memory storage that will contain all the dynamic data
CvMemStorage* storage = 0;
storage = cvCreateMemStorage(0);
// Convert IplImage to cv::Mat
inputImage = cv::Mat (myImage).clone ();
// output = input
outputImage = inputImage.clone ();
// Convert Input image from BGR to HSV
cv::cvtColor (inputImage, hsvImage, CV_BGR2HSV);
// Zero Matrices
hueImage = cv::Mat::zeros(hsvImage.rows, hsvImage.cols, CV_8U);
satImage = cv::Mat::zeros(hsvImage.rows, hsvImage.cols, CV_8U);
binaryImage = cv::Mat::zeros(hsvImage.rows, hsvImage.cols, CV_8U);
// HSV Channel 0 -> hueImage & HSV Channel 1 -> satImage
int from_to[] = { 0,0, 1,1};
cv::Mat img_split[] = { hueImage, satImage};
cv::mixChannels(&hsvImage, 3,img_split,2,from_to,2);
// ****************************************************
// NOTE that i is ROWS and j is COLS
// This is not x,y, it is rows and cols
// 0,0 is upper left; 0, max is upper right; max, 0 is lower left; max,max is lower right
// ****************************************************
for(int i = 0; i < outputImage.rows; i++)
{
for(int j = 0; j < outputImage.cols; j++)
{
// The output pixel is white if the input pixel
// hue is green and saturation is reasonable
// in low light the tennis ball has a hue around 160 - 180, saturations around 30 to 40
// in normal light it has a hue around 20 - 40, saturations around 80 - 150
// in very high light, the tennis ball center goes full white, so saturation drops to <10
// in general, the background doesn't seem to come up too much with a very loose constraint
// on saturation, so it works to allow mostly any saturation value.
if( (hueImage.at<uchar>(i,j) > 20 && hueImage.at<uchar>(i,j) < 40 && satImage.at<uchar>(i,j) > 5))
// || (hueImage.at<uchar>(i,j) > 160 && hueImage.at<uchar>(i,j) < 180 && satImage.at<uchar>(i,j) > 20 ))
binaryImage.at<uchar>(i,j) = 255;
else {
binaryImage.at<uchar>(i,j) = 0;
// Clear pixel blue output channel
outputImage.at<uchar>(i,j*3+0) = 0;
// Clear pixel green output channel
outputImage.at<uchar>(i,j*3+1) = 0;
// Clear pixel red output channel
outputImage.at<uchar>(i,j*3+2) = 0;
}
}
}
cv::Size strel_size;
strel_size.width = 3;
strel_size.height = 3;
cv::Mat strel = cv::getStructuringElement(cv::MORPH_ELLIPSE,strel_size);
cv::morphologyEx(binaryImage, binaryImage,cv::MORPH_OPEN,strel,cv::Point(-1, -1),3);
// Convert White on Black to Black on White by inverting the image
cv::bitwise_not(binaryImage,binaryImage);
// Blur the image to improve detection
cv::GaussianBlur(binaryImage, binaryImage, cv::Size(7, 7), 2, 2 );
cv::imshow ("Input to hue circles detector", inputImage);
// Display Binary Image
cv::imshow ("Working image", binaryImage);
// Display segmented image
//cv::imshow ("Circles", outputImage);
//start drawing all the circles
IplImage InputToHough = binaryImage;
CvSeq* circles =
cvHoughCircles( &InputToHough, storage, CV_HOUGH_GRADIENT, 1, 70, 140, 15, 20, 400);
//cvHoughCircles( &InputToHough, storage, CV_HOUGH_GRADIENT, 2, InputToHough.height/50, MIN_RADIUS, MAX_RADIUS );
//output all the circles detected
int NumCircles = circles->total;
//cout << "\n\nFound " << NumCircles << " circles" << endl;
if (NumCircles > MAX_CIRCLES) NumCircles = MAX_CIRCLES + 1; // so we don't print out too many
for( int i = 0; i < NumCircles; i++ ){
float* p = (float*)cvGetSeqElem( circles, i );
//cout << "x = " << p[0] << ", y = " << p[1]
// << ", radius = " << p[2] << endl;
cvCircle(CirclesImage,
cvPoint(cvRound(p[0]),
cvRound(p[1])),
cvRound(p[2]),
CV_RGB(0,255,0), 2, 8, 0 );
Circle myLocalCircle;
int myColor = 0, actualThreshold = 100;
myLocalCircle.setValues(cvRound(p[0]), cvRound(p[1]), cvRound(p[2]), myColor, actualThreshold);
myCircles.push_back(myLocalCircle);
} // ends for NumCircles
cvShowImage("Circles", CirclesImage);
return NumCircles;
}
//////////////////////
//
// 원 검출
//
//////////////////////
void ColorTracking::draw_circle(IplImage* image)
{
CvSeq* m_circle = NULL; // 원 정보
CvMemStorage* storage1 = NULL; // 메모리 할당
//검출된 원을 위한 메모리 공간 할당
storage1 = cvCreateMemStorage(0);
//원 갯수 저장 변수
circle_cnt = 0;
//원의 중심점을 검출하기 위한 누산기의 해상도
// 1이면 입력영상과 같은 크기, 2이면 입력 영상의 가로/세로의 반크기의 누산기
double dp = 1.5;
double min_dist = 300; //검출된 원의 중심 사이의 최소거리.작을 수록 많은 원이 검출 됨-?
double cannyThreshold = 100; //cvCanny 함수 임계값
double accThreshold = 50; //cvCanny 함수 축적평면의 임계값
int min_radius = 50; //최소 반지름
int max_radius = 150; //최대 반지름
int cx, cy = 0;
//소스영상, 메모리스토리지 포인터, 메소드인자, 영상의 해상도, 인접한 두 원사이의 최소거리
m_circle = cvHoughCircles(image, storage1, CV_HOUGH_GRADIENT,
dp,min_dist, cannyThreshold, accThreshold, min_radius, max_radius);
//원이 1개 라도 있으면
if(m_circle->total >0 )
{
// 데이터를 내보내기 위한 전역 선언한 시퀸스로 복사
circles = cvCloneSeq(m_circle, storage0);
//원 그리기
for(int k = 0; k < m_circle->total; k++)
{
float* circle;
int radius;
//검출된 원을 저장한 circles에서 원의 파라미터를 circle에 저장
//원의 중심 좌표 및 반지름이 배열에 순서대로 저장됨
circle = (float*)cvGetSeqElem(m_circle, k);
cx = cvRound(circle[0]); //중심점 x 좌표
cy = cvRound(circle[1]); //중심점 y 좌표
radius = cvRound(circle[2]); //반지름
//원그리기
if(radius > min_radius && radius < max_radius)
{
//중심점
cvCircle(m_orig_img, cvPoint(cx, cy), 3, CV_RGB(240,0,255), -1, 8, 0);
//검출라인
cvCircle(m_orig_img, cvPoint(cx, cy), radius, CV_RGB(255,255,255), 3, 8, 0);
}
}
}
else // 원이 없으면
{
circles = NULL;
circle_cnt = 0;
}
cvReleaseMemStorage(&storage1);
}
int snaps_nav(struct snaps_nav_state_struct* nav_state, time_t *ptr_framestamptime){
//Get frame from camera
for (int i=0; i<6; i++){
img = cvQueryFrame( capture );
if ( !img ) {
fprintf( stderr, "ERROR: frame is null...\n" );
getchar();
break;
}
}
timestamp_frame(ptr_framestamptime);
//Crop Image code
cvSetImageROI(img,cvRect(1,1,540,380));
cvCopy(img, Cropped, NULL);
//Change the color format from BGR to HSV
cvCvtColor(Cropped, imgHSV, CV_BGR2HSV);
//copy original img to be displayed in drawn Targets/DM img
cvCopy(Cropped, TimgDrawn, NULL );
cvInRangeS(imgHSV, cvScalar(T_range_low,0,0,0), cvScalar(T_range_high,255,255,0), TargetsFilter);
cvInRangeS(imgHSV, cvScalar(DM_range_low,0,0,0), cvScalar(DM_range_high,255,255,0), DMFilter);
//Magenta Marker Image Processing
cvErode(TargetsFilter, TargetsFilter, 0, 1);
cvDilate(TargetsFilter, TargetsFilter, NULL, 1); //Dilate image
cvSmooth(TargetsFilter, TargetsFilter, CV_GAUSSIAN, 3, 0, 0.0, 0.0); //Smooth Target image*/
//Orange Target Image Processing
cvErode(DMFilter, DMFilter, 0, 1);
cvDilate(DMFilter, DMFilter, NULL, 1); //Dilate image
//cvSmooth(DMFilter, DMFilter, CV_GAUSSIAN, 3, 0, 0.0, 0.0); //Smooth DM image
//Show filtered Images
cvShowImage("TargetsFilter", TargetsFilter); //Show Targets filter image
cvShowImage("DMFilter", DMFilter); //Show DM filter image //Show Noise Filter
//Perform Canny on Images
cvCanny(TargetsFilter, TimgCanny, T_canny_low, T_canny_high, 3); // Apply canny filter to the targets image
cvCanny(DMFilter, DMimgCanny, DM_canny_low, DM_canny_high, 3); // Apply canny filter to the DM image
cvShowImage("TCannyImage", TimgCanny);
cvShowImage("DMCannyImage", DMimgCanny);
// Find and Draw circles for the Targets image
CvPoint Tpt;
CvSeq* TimgHCirc = cvHoughCircles(
TimgCanny, TcircStorage, CV_HOUGH_GRADIENT, // in, out, method,
2, //precision of the accumulator (2x the input image)
T_rad_max*4, //min dist between circles
T_tol_max, T_tol_min, //parm1, parm2
T_rad_min, T_rad_max); //min radius, max radius
for (int i = 0; i < TimgHCirc->total; i++) {
float* p = (float*) cvGetSeqElem(TimgHCirc, i);
// To get the circle coordinates
CvPoint pt = cvPoint(cvRound(p[0]), cvRound(p[1]));
// Draw center of circles in green
cvCircle(TimgDrawn, pt, 1, CV_RGB(0,255,0), -1, 8, 0 );
cvCircle(TimgDrawn, pt, cvRound(p[2]), CV_RGB(255,255,0), 2, 8, 0); // img, center, radius, color, thickness, line type, shift
Tpt = cvPoint(cvRound(p[0]), cvRound(p[1]));
if (i == 0){
Tpt = cvPoint(cvRound(p[0]), cvRound(p[1]));
printf("Magenta Marker (x,y) - (%d, %d) \n", Tpt.x, Tpt.y);
}
else {printf("TM - There is an extra point frame not good");
}
} // end of for
// Find and Draw circles for the DM image
CvPoint DMpt;
CvSeq* DMimgHCirc = cvHoughCircles(
DMimgCanny, DMcircStorage, CV_HOUGH_GRADIENT, // in, out, method,
2, //precision of the accumulator (2x the input image)
DM_rad_max*4, //min dist between circles
DM_tol_max, DM_tol_min, //parm1, parm2
DM_rad_min, DM_rad_max); //min radius, max radius
for (int i=0; i<DMimgHCirc->total; i++) {
float* p = (float*) cvGetSeqElem(DMimgHCirc, i);
CvPoint pt = cvPoint(cvRound(p[0]), cvRound(p[1]));
// Draw center of circles in green
cvCircle(TimgDrawn, pt, 1, CV_RGB(255,0,0), -1, 8, 0 );
cvCircle(TimgDrawn, pt, cvRound(p[2]), CV_RGB(255,127,0), 2, 8, 0); // img, center, radius, color, thickness, line type, shift
if (i == 0){
DMpt = cvPoint(cvRound(p[0]), cvRound(p[1]));
printf("Red Marker(x,y) - (%d, %d)\n", DMpt.x, DMpt.y);
}
else {printf("DM - There is an extra point frame not good");
}
} // end of for
//Draw line in between points
cvLine(TimgDrawn, Tpt, DMpt, CV_RGB(0,255,0), 1, 8, 0);
d = sqrt(pow(Tpt.x-DMpt.x, 2)+pow(Tpt.y-DMpt.y, 2)); //distance in between points
printf("Distance in between tagets %d \n", d);
//Magenta target coordinates
int MT_pt_x = Tpt.x;
int MT_pt_y = Tpt.y;
//Orange target coordinates
int OT_pt_x = DMpt.x;
int OT_pt_y = DMpt.y;
//Minimum of the two coordinates
int x_min;
int x_max;
int y_min;
int y_max;
if (MT_pt_x > OT_pt_x){
x_min = OT_pt_x;
x_max = MT_pt_x;
}
else{
x_min = MT_pt_x;
x_max = OT_pt_x;
}
//printf("x_min %d \n", x_min);
//printf("x_max %d \n", x_max);
if (MT_pt_y > OT_pt_y){
y_min = OT_pt_y;
y_max = MT_pt_y;
}
else{
y_min = MT_pt_y;
y_max = OT_pt_y;
}
//printf("y_min %d", y_min);
//printf("y_max %d", y_max);
//Center of targets point (CT)
int CT_pt_x = (((x_max - x_min)/2) + x_min);
int CT_pt_y = (((y_max - y_min)/2) + y_min);
printf("Center coordinate (x, y) - (%d, %d) \n", CT_pt_x, CT_pt_y);
//Draw halfway targets point
CvPoint CT_pt = cvPoint(cvRound(CT_pt_x), cvRound(CT_pt_y));
cvCircle(img, CT_pt, 2, CV_RGB(255,0,0), -1, 8, 0);
//Orientation
int orientation_x = (OT_pt_x - CT_pt_x);
int orientation_y = (CT_pt_y - OT_pt_y);
double Theta = (((atan2(orientation_y, orientation_x )) * (180/3.14))+360);
//if
printf("Orientation %f Degrees \n", Theta);
//cvResetImageROI(img);
cvShowImage("TDrawnImage", TimgDrawn);
//cvShowImage("DMDrawnImage", DMimgDrawn);
//clear memory for target and DM circle finder
//note: this may not be necessary
cvClearMemStorage(TcircStorage);
cvClearMemStorage(DMcircStorage);
return 0;
}
int main(int argc, char* argv[])
{
int height,width,step,channels; //parameters of the image we are working on
int i,j,k,t1min=0,t1max=0,t2min=0,t2max=0,t3min=0,t3max=0; // other variables used
CvMat* threshold_matrix = cvCreateMat(2,3,CV_32FC1);
CvFileStorage* temp = cvOpenFileStorage("threshold_matrix.xml",NULL,CV_STORAGE_READ);
// Load the previous values of the threshold if they exist
if(temp)
{
threshold_matrix = (CvMat*)cvLoad("threshold_matrix.xml");
t1min =(int) CV_MAT_ELEM(*threshold_matrix,float,0,0) ;t2min =(int) CV_MAT_ELEM(*threshold_matrix,float,0,1) ;t3min =(int) CV_MAT_ELEM(*threshold_matrix,float,0,2);
t1max =(int) CV_MAT_ELEM(*threshold_matrix,float,1,0) ;t2max =(int) CV_MAT_ELEM(*threshold_matrix,float,1,1) ;t3max =(int) CV_MAT_ELEM(*threshold_matrix,float,1,2) ;
}
// Open capture device. 0 is /dev/video0, 1 is /dev/video1, etc.
CvCapture* capture = cvCaptureFromCAM( 1 );
if( !capture )
{
fprintf( stderr, "ERROR: capture is NULL \n" );
getchar();
return -1;
}
// grab an image from the capture
IplImage* frame = cvQueryFrame( capture );
// Create a window in which the captured images will be presented
cvNamedWindow( "Camera", CV_WINDOW_AUTOSIZE );
cvNamedWindow( "HSV", CV_WINDOW_AUTOSIZE );
cvNamedWindow( "F1", CV_WINDOW_AUTOSIZE );
cvNamedWindow( "F2", CV_WINDOW_AUTOSIZE );
cvNamedWindow( "F3", CV_WINDOW_AUTOSIZE );
//cvNamedWindow( "EdgeDetection", CV_WINDOW_AUTOSIZE );
/// Create Trackbars
char TrackbarName1[50]="t1min";
char TrackbarName2[50]="t1max";
char TrackbarName3[50]="t2min";
char TrackbarName4[50]="t2max";
char TrackbarName5[50]="t3min";
char TrackbarName6[50]="t3max";
cvCreateTrackbar( TrackbarName1, "F1", &t1min, 260 , NULL );
cvCreateTrackbar( TrackbarName2, "F1", &t1max, 260, NULL );
cvCreateTrackbar( TrackbarName3, "F2", &t2min, 260 , NULL );
cvCreateTrackbar( TrackbarName4, "F2", &t2max, 260, NULL );
cvCreateTrackbar( TrackbarName5, "F3", &t3min, 260 , NULL );
cvCreateTrackbar( TrackbarName6, "F3", &t3max, 260, NULL );
// Load threshold from the slider bars in these 2 parameters
CvScalar hsv_min = cvScalar(t1min, t2min, t3min, 0);
CvScalar hsv_max = cvScalar(t1max, t2max ,t3max, 0);
// get the image data
height = frame->height;
width = frame->width;
step = frame->widthStep;
// capture size -
CvSize size = cvSize(width,height);
// Initialize different images that are going to be used in the program
IplImage* hsv_frame = cvCreateImage(size, IPL_DEPTH_8U, 3); // image converted to HSV plane
IplImage* thresholded = cvCreateImage(size, IPL_DEPTH_8U, 1); // final thresholded image
IplImage* thresholded1 = cvCreateImage(size, IPL_DEPTH_8U, 1); // Component image threshold
IplImage* thresholded2 = cvCreateImage(size, IPL_DEPTH_8U, 1);
IplImage* thresholded3 = cvCreateImage(size, IPL_DEPTH_8U, 1);
IplImage* filtered = cvCreateImage(size, IPL_DEPTH_8U, 1); //smoothed image
while( 1 )
{
// Load threshold from the slider bars in these 2 parameters
hsv_min = cvScalar(t1min, t2min, t3min, 0);
hsv_max = cvScalar(t1max, t2max ,t3max, 0);
// Get one frame
frame = cvQueryFrame( capture );
if( !frame )
{
fprintf( stderr, "ERROR: frame is null...\n" );
getchar();
break;
}
// Covert color space to HSV as it is much easier to filter colors in the HSV color-space.
cvCvtColor(frame, hsv_frame, CV_BGR2HSV);
// Filter out colors which are out of range.
cvInRangeS(hsv_frame, hsv_min, hsv_max, thresholded);
// the below lines of code is for visual purpose only remove after calibration
//--------------FROM HERE-----------------------------------
//Split image into its 3 one dimensional images
cvSplit( hsv_frame,thresholded1, thresholded2, thresholded3, NULL );
// Filter out colors which are out of range.
cvInRangeS(thresholded1,cvScalar(t1min,0,0,0) ,cvScalar(t1max,0,0,0) ,thresholded1);
cvInRangeS(thresholded2,cvScalar(t2min,0,0,0) ,cvScalar(t2max,0,0,0) ,thresholded2);
cvInRangeS(thresholded3,cvScalar(t3min,0,0,0) ,cvScalar(t3max,0,0,0) ,thresholded3);
//-------------REMOVE OR COMMENT AFTER CALIBRATION TILL HERE ------------------
// Memory for hough circles
CvMemStorage* storage = cvCreateMemStorage(0);
// hough detector works better with some smoothing of the image
cvSmooth( thresholded, thresholded, CV_GAUSSIAN, 9, 9 );
//hough transform to detect circle
CvSeq* circles = cvHoughCircles(thresholded, storage, CV_HOUGH_GRADIENT, 2,
thresholded->height/4, 100, 50, 10, 400);
for (int i = 0; i < circles->total; i++)
{ //get the parameters of circles detected
float* p = (float*)cvGetSeqElem( circles, i );
printf("Ball! x=%f y=%f r=%f\n\r",p[0],p[1],p[2] );
// draw a circle with the centre and the radius obtained from the hough transform
cvCircle( frame, cvPoint(cvRound(p[0]),cvRound(p[1])), //plot centre
2, CV_RGB(255,255,255),-1, 8, 0 );
cvCircle( frame, cvPoint(cvRound(p[0]),cvRound(p[1])), //plot circle
cvRound(p[2]), CV_RGB(0,255,0), 2, 8, 0 );
}
/* for testing purpose you can show all the images but when done with calibration
only show frame to keep the screen clean */
cvShowImage( "Camera", frame ); // Original stream with detected ball overlay
cvShowImage( "HSV", hsv_frame); // Original stream in the HSV color space
cvShowImage( "After Color Filtering", thresholded ); // The stream after color filtering
cvShowImage( "F1", thresholded1 ); // individual filters
cvShowImage( "F2", thresholded2 );
cvShowImage( "F3", thresholded3 );
//cvShowImage( "filtered", thresholded );
cvReleaseMemStorage(&storage);
//If ESC key pressed, Key=0x10001B under OpenCV 0.9.7(linux version),
//remove higher bits using AND operator
if( (cvWaitKey(10) & 255) == 27 ) break;
}
//Save the threshold values before exiting
*((float*)CV_MAT_ELEM_PTR( *threshold_matrix, 0, 0 ) ) = t1min ;*((float*)CV_MAT_ELEM_PTR( *threshold_matrix, 0, 1 ) ) = t2min ;*((float*)CV_MAT_ELEM_PTR( *threshold_matrix, 0, 2 ) ) = t3min ;
*((float*)CV_MAT_ELEM_PTR( *threshold_matrix, 1, 0 ) ) = t1max ;*((float*)CV_MAT_ELEM_PTR( *threshold_matrix, 1, 1 ) ) = t2max ;*((float*)CV_MAT_ELEM_PTR( *threshold_matrix, 1, 2 ) ) = t3max ;
cvSave("threshold_matrix.xml",threshold_matrix);
// Release the capture device housekeeping
cvReleaseCapture( &capture );
cvDestroyWindow( "mywindow" );
return 0;
}
