int main( int argc, char** argv ) {
// create a window with appropriate size. Windows name is determined by file name
// supplied as an argument
cvNamedWindow( argv[1], CV_WINDOW_AUTOSIZE );
// open video
g_capture = cvCreateFileCapture( argv[1] );
// set read position in units of frames and retrieve total number of frames
int frames = (int) cvGetCaptureProperty(
g_capture,
CV_CAP_PROP_FRAME_COUNT
);
// do not create treackbar if video does not include an information
// about number of frames
if( frames!=0 ) {
cvCreateTrackbar(
"Position",
argv[1],
&g_slider_position,
frames,
onTrackbarSlide
);
}
// display video frame by frame
IplImage* frame;
while(1) {
frame = cvQueryFrame( g_capture );
if( !frame ) break;
cvShowImage( argv[1], frame );
// set trackbar to a current frame position
cvSetTrackbarPos("Position", argv[1], g_slider_position);
g_slider_position++;
char c = cvWaitKey(33);
// quit if ESC is pressed
if( c == 27 ) break;
}
// free memory
cvReleaseCapture( &g_capture );
cvDestroyWindow( argv[1] );
return(0);
}
void Update_Gui_Windows()
{
static int first = 1;
cvShowImage(eye_window, eye_image);
cvShowImage(original_eye_window, original_eye_image);
cvReleaseImage(&original_eye_image);
cvShowImage(scene_window, scene_image);
cvShowImage(ellipse_window, ellipse_image);
cvResizeWindow(eye_window,RESOLUTION_WIDTH,RESOLUTION_HEIGHT);
cvResizeWindow(original_eye_window,RESOLUTION_WIDTH,RESOLUTION_HEIGHT);
cvResizeWindow(scene_window,RESOLUTION_WIDTH,RESOLUTION_HEIGHT);
cvResizeWindow(ellipse_window,RESOLUTION_WIDTH,RESOLUTION_HEIGHT);
// only OpenCV 0.9.6 has the function of cvMoveWindow(), now we are using version 0.9.5
if (first) {
cvMoveWindow(eye_window, RESOLUTION_WIDTH, 0);
cvMoveWindow(scene_window, 2*RESOLUTION_WIDTH, 0);
cvMoveWindow(ellipse_window, RESOLUTION_WIDTH, RESOLUTION_HEIGHT);
first = 0;
}
cvSetTrackbarPos("Edge Threshold", control_window, pupil_edge_thres);
}
/**********************************************************
* Callback needed by OpenCV for controlling values set by
* the track bars.
*********************************************************/
void Recorder::onLowSlider(int val, void* userData) {
if(!Recorder::mParams->setLowLevel(val)) {
cvSetTrackbarPos("Low", "EVM", Recorder::mParams->getHighLevel());
}
Recorder::mParams->setLowLevel(Recorder::mLowLevel);
}
/**********************************************************
* Callback needed by OpenCV for controlling values set by
* the track bars.
*********************************************************/
void Recorder::onFilterSlider(int val, void* userData) {
if(!Recorder::mParams->setFilter(val)) {
cvSetTrackbarPos("Filter", "EVM", 0); //default to gaussian
Recorder::mParams->setFilter(0);
}
}
void cv::setTrackbarPos( const std::string& trackbarName, const std::string& winName, int value )
{
cvSetTrackbarPos(trackbarName.c_str(), winName.c_str(), value );
}
int main( int argc, char** argv ) {
int ikey=0;
char key;
IplImage *imCapt,*imDisp,*imDisp2;
static int tb1_val,tb2_val; /* Trackbar parameters */
timewin *tw;
buffer *bf_img;
bbuffer *bf_blobs;
int width,height;
if(kb_lowresfl) {
width=320;
height=240;
} else {
width=640;
height=480;
}
/* Set window title to a list of control keys */
const char *window1 = "Controls: (n)eighbours, (d)istance, (b)lur type, (h)igh-res, (c)olourspace, (r)eset, (ESC) exit";
const char *trackbar1 = "margin";
const char *trackbar2 = "timesteps";
int fno;
cvInitSystem( argc,argv );
/* Get an OpenCV camera handle */
cam = cvCreateCameraCapture(0);
/* Set size of image (appears to be ignored in Linux) */
cvSetCaptureProperty(cam, CV_CAP_PROP_FRAME_WIDTH, width);
cvSetCaptureProperty(cam, CV_CAP_PROP_FRAME_HEIGHT, height);
/* Create a window with slider */
cvNamedWindow(window1, CV_WINDOW_AUTOSIZE);
cvSetMouseCallback(window1,callback_mouse, NULL );
tb_margin = DEF_MARGIN; /* Default */
tb1_val=tb_margin/TB1_SCALE*TB1_MAX;
cvCreateTrackbar(trackbar1,window1,&tb1_val,TB1_MAX,callback_trackbar1);
tb2_val = tb_timesteps = DEF_TIMESTEPS; /* Default */
cvCreateTrackbar(trackbar2,window1,&tb2_val,TB2_MAX,callback_trackbar2);
cvMoveWindow(window1, 100, 45);
/* Allocate image buffers */
if(kb_lowresfl)
imDisp2 = cvCreateImage( cvSize(width*4,height*2), IPL_DEPTH_8U, 3);
else
imDisp2 = cvCreateImage( cvSize(width*2,height), IPL_DEPTH_8U, 3);
imDisp = cvCreateImage( cvSize(width*2,height), IPL_DEPTH_8U, 3);
bf_img = buffer_new(height,width,3);
bf_blobs = bbuffer_new(height,width,3);
tw=timewin_new(DEF_TIMESIZE);
fno=0;
key=(char)cvWaitKey(500);
while ( key !=27 ) {
imCapt = cvQueryFrame(cam);
buffer_iplcopy(bf_img,imCapt,1);
/* Detect blobs */
detect_and_render_blobs(bf_img,bf_blobs);
/* Display result */
flip_image(imCapt,imDisp);
paste_image(imDisp,bf_blobs,width);
if(kb_lowresfl) {
upsample_image(imDisp,imDisp2);
cvShowImage(window1, imDisp2);
} else {
cvShowImage(window1, imDisp);
}
ikey=cvWaitKey(5); /* Needed for highgui event processing */
if(ikey>0) {
key=(char)ikey;
if(key == 'n') {
kb_n8flag=1-kb_n8flag;
printf("n8flag=%d\n",kb_n8flag);
}
if(key == 'd') {
kb_normfl=1-kb_normfl;
printf("normfl=%d\n",kb_normfl);
}
if(key == 'b') {
kb_blurfl=1-kb_blurfl;
printf("blurfl=%d\n",kb_blurfl);
}
if(key =='c') {
kb_cspace=1-kb_cspace; /* Toggle colourspace */
printf("cspace=%d\n",kb_cspace);
}
if(key == 'r') {
tb_margin=DEF_MARGIN; /* Reset to default */
tb1_val=tb_margin/TB1_SCALE*TB1_MAX;
cvSetTrackbarPos(trackbar1,window1,tb1_val);
tb2_val=tb_timesteps=DEF_TIMESTEPS; /* Reset to default */
cvSetTrackbarPos(trackbar2,window1,tb2_val);
kb_n8flag=DEF_N8FLAG;
kb_normfl=DEF_NORMFL;
kb_blurfl=DEF_BLURFL;
printf("timesteps =%d\n",tb_timesteps);
printf("min_margin=%g\n",tb_margin);
printf("n8flag=%d\n",kb_n8flag);
printf("normfl=%d\n",kb_normfl);
printf("blurfl=%d\n",kb_blurfl);
cvWaitKey(1);
/* printf("tb1:%d\n",cvGetTrackbarPos(trackbar1,window1)); */
/* printf("tb2:%d\n",cvGetTrackbarPos(trackbar2,window1)); */
}
if(key == 'h') {
kb_lowresfl=1-kb_lowresfl; /* Toggle resolution */
if(kb_lowresfl) {
width=320;
height=240;
} else {
width=640;
height=480;
}
cvReleaseCapture(&cam);
cam = cvCreateCameraCapture(0);
/* Set size of image */
cvSetCaptureProperty(cam, CV_CAP_PROP_FRAME_WIDTH, width);
cvSetCaptureProperty(cam, CV_CAP_PROP_FRAME_HEIGHT, height);
/* Free image buffers */
cvReleaseImage( &imDisp );
buffer_free(bf_img);
bbuffer_free(bf_blobs);
/* Allocate image buffers */
imDisp = cvCreateImage( cvSize(width*2,height), IPL_DEPTH_8U, 3);
bf_img = buffer_new(height,width,3);
bf_blobs = bbuffer_new(height,width,3);
}
}
timewin_addtime(tw);
fno++;
if((fno%DEF_TIMESIZE)==0) printf("Frame rate %g Hz\n",timewin_rate(tw));
}
/* Clean up */
timewin_free(tw);
buffer_free(bf_img);
bbuffer_free(bf_blobs);
cvDestroyAllWindows();
cvReleaseCapture(&cam);
return 0;
}
void AdaptiveHistogramCamshift::AdaptHistogram(IplImage* hue, IplImage* mask, IplImage* out)
{
// Prepare to analyze new track window
const CvRect& updateHistRect = m_trackCompRect;
// Now subdivide the track window and sum all pixels in each square
// subdivision of size m_sBox using pixel values given by the
// current hustogram. When we are done, we will normalize the sum
// from each subdivision and then be able to tell roughly how
// similar each subregion is to the track histogram.
// Make sure box size is greater than or equal to 2, and protect from
// changes made in GUI
const int sBox = std::max(m_sBox, 2);
if (sBox != m_sBox)
{
m_sBox = sBox;
cvSetTrackbarPos(ControlNames[ControlName_SBox], m_controlsGUIWndName.c_str(), sBox);
}
std::vector<float> subdivs;
int numRows, numCols;
SubdivideSumTrackWnd(sBox, &numRows, &numCols, &subdivs);
// Check window is less than sBox in size.
if (subdivs.empty())
{
return;
}
// Histogram for image subdivisions
for (int i = 0; i < m_histDims; ++i)
{
float *bin = cvGetHistValue_1D(m_histTrackWnd, i);
*bin = 0;
}
// Find the max vlaue of the subdivisions
float maxVal = *std::max_element(subdivs.begin(), subdivs.end());;
// DEBUG maxval
//printf("maxVal: %f\n", maxVal);
// Step through all subdivisions and weight them into a new histogram
// if they are greater than minVal. The weight function is r^2 where
// r is the ratio of the subdivision value to the max subdivision
// value.
if (maxVal > 0)
{
float minVal = maxVal * 0.125f;
float* subdivsCur = &subdivs[0];
for (int i = 0; i < numRows; ++i)
{
for (int j = 0; j < numCols; ++j, ++subdivsCur)
{
// Create a box around this area
CvPoint roiP1 = cvPoint(updateHistRect.x + sBox * j, updateHistRect.y + sBox * i);
CvPoint roiP2 = cvPoint(roiP1.x + sBox, roiP1.y + sBox);
if (*subdivsCur < minVal)
{
if(*subdivsCur > (minVal * 0.0625))
{
// Get ratio to max subdivision
float ratioMaxSubdiv = *subdivsCur / maxVal;
// Get color of surrounding box
CvScalar boxColor = colors[GREEN];
for (int colorInd = 0; colorInd < 3; ++colorInd)
{
boxColor.val[colorInd] *= ratioMaxSubdiv;
}
// Draw the box (darker green means less weight)
if (out)
{
cvRectangle(out, roiP1, roiP2, boxColor, 1);
}
}
else
{
// Draw a red box around this subdivision since it is not used
if (out)
{
cvRectangle(out, roiP1, roiP2, colors[RED], 1 );
}
}
}
else
{
// Get ratio to max subdivision
float ratioMaxSubdiv = *subdivsCur / maxVal;
// Get weight into histogram of track window
float weightVal = ratioMaxSubdiv * ratioMaxSubdiv;
// DEBUG weights
//printf("w %d: %f\t", j, weightVal);
// Get color of surrounding box
CvScalar boxColor = colors[GREEN];
for (int colorInd = 0; colorInd < 3; ++colorInd)
{
boxColor.val[colorInd] *= ratioMaxSubdiv;
}
// Draw the box (darker green means less weight)
if (out)
{
cvRectangle(out, roiP1, roiP2, boxColor, 1);
}
// Weight this subdivision into the histogram for the track window
CvRect thisSubdivRect = cvRect(roiP1.x, roiP1.y, sBox, sBox);
cvSetImageROI(hue, thisSubdivRect);
cvSetImageROI(mask, thisSubdivRect);
cvCalcHist(&hue, m_histSubdiv, 0, mask);
cvResetImageROI(hue);
cvResetImageROI(mask);
// Weight this into the track window histogram
for (int binNum = 0; binNum < m_histDims; ++binNum)
{
float* thisBin = cvGetHistValue_1D(m_histTrackWnd, binNum);
*thisBin *= (1.0f - weightVal);
*thisBin += static_cast<float>(cvGetReal1D(m_histSubdiv->bins, binNum)) * weightVal;
}
}
}
// DEBUG weights
//printf("\n");
}
// DEBUG weights
//printf("\n");
}
// DEBUG histograms
//printf("Wnd BEFORE WT\n");
//for( int i = 0; i < m_histDims; i++ ) {
// float *bin = cvGetHistValue_1D( m_histTrackWnd, i );
// printf("%2d: %3.1f ", i, *bin);
// if( 0 == (i+1) % 8 ) {
// printf("\n");
// }
//}
// Now scale track window histogram to tracking histogram scale
float trackWndHistMaxVal;
cvGetMinMaxHistValue(m_histTrackWnd, 0, &trackWndHistMaxVal, 0, 0);
cvConvertScale(m_histTrackWnd->bins, m_histTrackWnd->bins,
trackWndHistMaxVal ? HIST_SCALE / trackWndHistMaxVal : 0., 0);
// Use aging to weight track window histogram into tracking histogram
float averageBin = 0;
for (int binNum = 0; binNum < m_histDims; ++binNum)
{
float* thisBin = cvGetHistValue_1D(m_hist, binNum);
*thisBin *= (1.0f - (m_ageRatio / 100.0f));
*thisBin += static_cast<float>(cvGetReal1D(m_histTrackWnd->bins, binNum)) *
(m_ageRatio / 100.0f);
averageBin += *thisBin;
}
averageBin /= m_histDims;
// DEBUG average bin
//printf("Avg bin: %f.\n", averageBin);
// See if this histogram is dying
//if( averageBin < SMALLEST_AVG_HIST_BIN ) {
// cvConvertScale( m_hist->bins, m_hist->bins, SMALLEST_AVG_HIST_BIN / averageBin, 0 );
// DEBUG averageBin
//printf("Hist saved for average bin: %f\n", averageBin);
//}
// DEBUG track hist
//printf("Track\n");
//for( int i = 0; i < m_histDims; i++ ) {
// float *bin = cvGetHistValue_1D( m_hist, i );
// printf("%2d: %3.1f ", i, *bin);
// if( 0 == (i+1) % 8 ) {
// printf("\n");
// }
//}
//printf("\n");
// Now compute histogram image
cvZero(m_histImg);
for (int i = 0; i < m_histDims; ++i)
{
const double raw = cvGetReal1D(m_hist->bins, i) * (m_histImg->height / HIST_SCALE);
const int val = cvRound(raw);
CvScalar color = hsv2rgb((i * m_histRanges[1]) / m_histDims);
cvRectangle(m_histImg,
cvPoint(i * m_binWidth, m_histImg->height),
cvPoint((i + 1) * m_binWidth, m_histImg->height - val),
color, -1, 8, 0);
}
// Show histogram
if (m_showHistogram)
{
ShowHistogram();
}
}
int
main (int argc, char **argv)
{
//読み込む動画ファイル名
char* filename;
char* imagename;
if (argc == 2){
filename = argv[1];
}else{
usage();
return -1;
}
printf ("########### #############\n"
"video_test, using OpenCV version %s (%d.%d.%d)\n",
CV_VERSION,
CV_MAJOR_VERSION, CV_MINOR_VERSION, CV_SUBMINOR_VERSION);
printf( "Hot keys: \n"
"\tESC - quit the program\n"
"\tp - play/stop\n"
"\ts - save current frame as jpg\n"
"\tother key - next frame\n"
"\n" );
double w = 320, h = 240;
int c;
//指定したAVIファイルが見つからない場合
if(NULL==(capture = cvCaptureFromAVI(filename))){
fprintf(stderr,"指定のaviファイル %s が見つかりませんでした．", filename);
return -1;
}
// キャプチャサイズを設定する．
cvSetCaptureProperty (capture, CV_CAP_PROP_FRAME_WIDTH, w);
cvSetCaptureProperty (capture, CV_CAP_PROP_FRAME_HEIGHT, h);
cvNamedWindow ("Capture", CV_WINDOW_AUTOSIZE);
//スライドバーとかつけちゃう
int frames = (int)cvGetCaptureProperty(capture, CV_CAP_PROP_FRAME_COUNT);
if(frames != 0){
cvCreateTrackbar("Position", "Capture", &slider_position, frames, onTrackBarSlide);
}
int play = 0;
// ビデオから画像をキャプチャする
while (1) {
frame = cvQueryFrame (capture);
slider_position = (int)cvGetCaptureProperty(capture, CV_CAP_PROP_POS_FRAMES);
cvSetTrackbarPos("Position", "Capture", slider_position);
cvShowImage ("Capture", frame);
if(play){
c = cvWaitKey (2);
}else{
c = cvWaitKey (0);
}
// ESC で終了
if (c == '\x1b')
break;
// キー入力色々
switch( (char) c ) {
case 'p':
play ^= 1;
break;
case 's':
//printf("%d\n", num);
// ↓なぜかBus error
//sprintf(imagename, "image_%d.jpg", num);
imagename = "image.jpg";
cvSaveImage(imagename, frame);
printf("Current frame is saved as %s\n", imagename);
break;
default:
;
}
}
cvReleaseCapture (&capture);
cvDestroyWindow ("Capture");
return 0;
}
void cv::setTrackbarPos( const String& trackbarName, const String& winName, int value )
{
CV_TRACE_FUNCTION();
cvSetTrackbarPos(trackbarName.c_str(), winName.c_str(), value );
}
void BinarizationViewer::showBinarizedImgs() {
Mat srcBGRImg, srcHSVImg, srcYCrCbImg;
Mat bgrChannelImgs[3], hsvChannelImgs[3], ycrcbChannelImgs[3];
vector<string> channelNames = {};
int trackbarInitValue = 128;
namedWindow("Blue", CV_WINDOW_AUTOSIZE);
namedWindow("Green", CV_WINDOW_AUTOSIZE);
namedWindow("Red", CV_WINDOW_AUTOSIZE);
namedWindow("Hue", CV_WINDOW_AUTOSIZE);
namedWindow("Saturation", CV_WINDOW_AUTOSIZE);
namedWindow("Value", CV_WINDOW_AUTOSIZE);
namedWindow("Y", CV_WINDOW_AUTOSIZE);
namedWindow("Cr", CV_WINDOW_AUTOSIZE);
namedWindow("Cb", CV_WINDOW_AUTOSIZE);
cvCreateTrackbar("B_Threshold", "Blue", &trackbarInitValue, 255, onBlueTrackbar);
cvCreateTrackbar("G_Threshold", "Green", &trackbarInitValue, 255, onGreenTrackbar);
cvCreateTrackbar("R_Threshold", "Red", &trackbarInitValue, 255, onRedTrackbar);
cvCreateTrackbar("H_Threshold", "Hue", &trackbarInitValue, 255, onHueTrackbar);
cvCreateTrackbar("S_Threshold", "Saturation", &trackbarInitValue, 255, onSaturationTrackbar);
cvCreateTrackbar("V_Threshold", "Value", &trackbarInitValue, 255, onValueTrackbar);
cvCreateTrackbar("Y_Threshold", "Y", &trackbarInitValue, 255, onYTrackbar);
cvCreateTrackbar("Cr_Threshold", "Cr", &trackbarInitValue, 255, onCrTrackbar);
cvCreateTrackbar("Cb_Threshold", "Cb", &trackbarInitValue, 255, onCbTrackbar);
cvSetTrackbarPos("B_Threshold", "Blue", 128);
cvSetTrackbarPos("G_Threshold", "Green", 128);
cvSetTrackbarPos("R_Threshold", "Red", 128);
cvSetTrackbarPos("H_Threshold", "Hue", 128);
cvSetTrackbarPos("S_Threshold", "Saturation", 128);
cvSetTrackbarPos("V_Threshold", "Value", 128);
cvSetTrackbarPos("Y_Threshold", "Y", 128);
cvSetTrackbarPos("Cr_Threshold", "Cr", 128);
cvSetTrackbarPos("Cb_Threshold", "Cb", 128);
_isShowing = true;
while(_isShowing) {
srcBGRImg = _cameraManager.getFrame();
cvtColor(srcBGRImg, srcHSVImg, CV_BGR2HSV);
cvtColor(srcBGRImg, srcYCrCbImg, CV_BGR2YCrCb);
split(srcBGRImg, bgrChannelImgs);
split(srcHSVImg, hsvChannelImgs);
split(srcYCrCbImg, ycrcbChannelImgs);
threshold(bgrChannelImgs[0], bgrChannelImgs[0], binarizationViewerBlueThreshold, 255, CV_THRESH_BINARY);
threshold(bgrChannelImgs[1], bgrChannelImgs[1], binarizationViewerGgreenThreshold, 255, CV_THRESH_BINARY);
threshold(bgrChannelImgs[2], bgrChannelImgs[2], binarizationViewerRedThreshold, 255, CV_THRESH_BINARY);
threshold(hsvChannelImgs[0], hsvChannelImgs[0], binarizationViewerHueThreshold, 255, CV_THRESH_BINARY);
threshold(hsvChannelImgs[1], hsvChannelImgs[1], binarizationViewerSaturationThreshold, 255, CV_THRESH_BINARY);
threshold(hsvChannelImgs[2], hsvChannelImgs[2], binarizationViewerValueThreshold, 255, CV_THRESH_BINARY);
threshold(ycrcbChannelImgs[0], ycrcbChannelImgs[0], binarizationViewerYThreshold, 255, CV_THRESH_BINARY);
threshold(ycrcbChannelImgs[1], ycrcbChannelImgs[1], binarizationViewerCrThreshold, 255, CV_THRESH_BINARY);
threshold(ycrcbChannelImgs[2], ycrcbChannelImgs[2], binarizationViewerCbThreshold, 255, CV_THRESH_BINARY);
imshow("src", srcBGRImg);
imshow("Blue", bgrChannelImgs[0]);
imshow("Green", bgrChannelImgs[1]);
imshow("Red", bgrChannelImgs[2]);
imshow("Hue", hsvChannelImgs[0]);
imshow("Saturation", hsvChannelImgs[1]);
imshow("Value", hsvChannelImgs[2]);
imshow("Y", ycrcbChannelImgs[0]);
imshow("Cr", ycrcbChannelImgs[1]);
imshow("Cb", ycrcbChannelImgs[2]);
int key = waitKey(1);
if(key == 27) break;
}
destroyAllWindows();
}
/*
* -d 0,1,2,3,4 =>/dev/video0,video1,...
* -f static file
*
*/
int main (int argc, char * argv[]) {
//Two boolean variables
char quit = 0; //Exit main program loop?
char grab_frame = 1; //Do we grab a new frame from the camera?
int thresh1=DEFAULT_TRACKBAR_VAL, thresh2=DEFAULT_TRACKBAR_VAL; //These two variables will hold trackbar positions.
if(argc==1){
camID=0;
printf("set default camera 0\n");
}else if(option(argc,argv) < 0 ){
printf( "Wrong args!!!\n");
exit(EXIT_FAILURE);
}
//These are pointers to IPL images, which will hold the result of our calculations
IplImage *small_image = NULL; /*cvCreateImage(cvSize(IMG_WIDTH,IMG_HEIGHT),IPL_DEPTH_8U,3)*/; //size, depth, channels (RGB = 3)
IplImage *small_grey_image = NULL;/*cvCreateImage(cvGetSize(small_image), IPL_DEPTH_8U, 1)*/; //1 channel for greyscale
IplImage *edge_image = NULL; /*cvCreateImage(cvGetSize(small_image), IPL_DEPTH_8U, 1)*/; //We use cvGetSize to make sure the images are the same size.
//CvMemStorage and CvSeq are structures used for dynamic data collection. CvMemStorage contains pointers to the actual
//allocated memory, but CvSeq is used to access this data. Here, it will hold the list of image contours.
CvMemStorage *storage = cvCreateMemStorage(0);
CvSeq *contours = 0;
CvCapture *camera=NULL;
if(camID>=0){
camera = cvCreateCameraCapture(camID); //This function tries to connect to the first (0th) camera it finds and creates a structure to refer to it.
if(!camera){ //cvCreateCameraCapture failed, most likely there is no camera connected.
printf("Could not find a camera to capture from...\n"); //Notify the user...
return -1; //And quit with an error.
}
}
cvNamedWindow(MAIN_WINNAME, CV_WINDOW_AUTOSIZE); //Here we create a window and give it a name. The second argument tells the window to not automatically adjust its size.
//We add two trackbars (sliders) to the window. These will be used to set the parameters for the Canny edge detection.
cvCreateTrackbar("Thresh1", MAIN_WINNAME, &thresh1, 256, 0);
cvCreateTrackbar("Thresh2", MAIN_WINNAME, &thresh2, 256, 0);
//Set the trackbar position to the default value.
cvSetTrackbarPos("Thresh1", MAIN_WINNAME, DEFAULT_TRACKBAR_VAL); //Trackbar name, window name, position
cvSetTrackbarPos("Thresh2", MAIN_WINNAME, DEFAULT_TRACKBAR_VAL);
//Now set the mouse callback function. We need to pass the location of the contours so that it will be able to access this information.
cvSetMouseCallback(MAIN_WINNAME, onMouse, &contours); //Window name, function pointer, user-defined parameters.
IplImage *frame=NULL; //This will point to the IPL image we will retrieve from the camera.
IplImage *frame_org=NULL;
if(camID < 0){
frame_org = cvLoadImage(orgFile, CV_LOAD_IMAGE_UNCHANGED);
frame = cvLoadImage(inFile, CV_LOAD_IMAGE_UNCHANGED);
}
//This is the main program loop. We exit the loop when the user sets quit to true by pressing the "esc" key
while(!quit){
int c =0;
if(camID >= 0){
c=cvWaitKey(30); //Wait 30 ms for the user to press a key.
//Respond to key pressed.
switch(c){
case 32: //Space
grab_frame = !grab_frame; //Reverse the value of grab_frame. That way, the user can toggle by pressing the space bar.
break;
case 27: //Esc: quit application when user presses the 'esc' key.
quit = 1; //Get out of loop
break;
};
//If we don't have to grab a frame, we're done for this pass.
if(!grab_frame)continue;
//Grab a frame from the camera.
frame = cvQueryFrame(camera);
if(!frame) continue; //Couldn't get an image, try again next time.
}
//In computer vision, it's always better to work with the smallest images possible, for faster performance.
//cvResize will use inter-linear interpolation to fit frame into small_image.
if(small_image==NULL){
small_image = cvCreateImage(cvSize(frame->width,frame->height),IPL_DEPTH_8U,3); //size, depth, channels (RGB = 3)
printf("w=%d, h=%d\n", frame->width,frame->height);
}
if(small_grey_image==NULL) small_grey_image=cvCreateImage(cvGetSize(small_image), IPL_DEPTH_8U, 1);
if(edge_image==NULL) edge_image = cvCreateImage(cvGetSize(small_image), IPL_DEPTH_8U, 1);
cvResize(frame, small_image, CV_INTER_LINEAR);
//Many computer vision algorithms do not use colour information. Here, we convert from RGB to greyscale before processing further.
cvCvtColor(small_image, small_grey_image, CV_RGB2GRAY);
//We then detect edges in the image using the Canny algorithm. This will return a binary image, one where the pixel values will be 255 for
//pixels that are edges and 0 otherwise. This is unlike other edge detection algorithms like Sobel, which compute greyscale levels.
cvCanny(small_grey_image, edge_image, (double)thresh1, (double)thresh2, 3); //We use the threshold values from the trackbars and set the window size to 3
//The edges returned by the Canny algorithm might have small holes in them, which will cause some problems during contour detection.
//The simplest way to solve this problem is to "dilate" the image. This is a morphological operator that will set any pixel in a binary image to 255 (on)
//if it has one neighbour that is not 0. The result of this is that edges grow fatter and small holes are filled in.
//We re-use small_grey_image to store the results, as we won't need it anymore.
cvDilate(edge_image, small_grey_image, 0, 1);
//Once we have a binary image, we can look for contours in it. cvFindContours will scan through the image and store connected contours in "sorage".
//"contours" will point to the first contour detected. CV_RETR_TREE means that the function will create a contour hierarchy. Each contour will contain
//a pointer to contours that are contained inside it (holes). CV_CHAIN_APPROX_NONE means that all the contours points will be stored. Finally, an offset
//value can be specified, but we set it to (0,0).
cvFindContours(small_grey_image, storage, &contours, sizeof(CvContour), CV_RETR_TREE,
CV_CHAIN_APPROX_NONE, cvPoint(0,0));
CvContour *max_contour = LargestContour(&contours);
//This function will display contours on top of an image. We can specify different colours depending on whether the contour in a hole or not.
cvDrawContours(small_image, contours, CV_RGB(255,0,0), CV_RGB(0,255,0), MAX_CONTOUR_LEVELS,
1, CV_AA, cvPoint(0,0));
//Finally, display the image in the window.
cvShowImage(MAIN_WINNAME, small_image);
if(camID< 0){
//draw the max contour on the original
cvDrawContours(frame_org, (CvSeq *)max_contour, CV_RGB(0, 255,0), CV_RGB(0,200,0),
0, 1, CV_AA, cvPoint(roi_x,roi_y));
cvShowImage(orgFile, frame_org);
c=cvWaitKey(0); //Wait 30 ms for the user to press a key.
//Respond to key pressed.
if(c == 27) quit = 1; //Get out of loop
}
}
//Clean up before quitting.
cvDestroyAllWindows(); //This function releases all the windows created so far.
cvReleaseCapture(&camera); //Release the camera capture structure.
//release memory
cvReleaseMemStorage(&storage);
//Release images
cvReleaseImage(&small_image); //We pass a pointer to a pointer, because cvReleaseImage will set the image pointer to 0 for us.
cvReleaseImage(&small_grey_image);
cvReleaseImage(&edge_image);
if( (camID < 0) && frame ){
cvReleaseImage(&frame);
}
return 0; //We're done.
}
/*
* Update's trackbar positions for variables that can be changed by the software
*
*/
void UpdateGUI(Experiment* exp) {
cvSetTrackbarPos("DLPFlashOn", exp->WinCon1, (exp->Params->DLPOnFlash));
cvSetTrackbarPos("DLPOn", exp->WinCon1, (exp->Params->DLPOn));
/** Illumination Controls **/
cvSetTrackbarPos("x", exp->WinCon1, (exp->Params->IllumSquareOrig.x));
cvSetTrackbarPos("y", exp->WinCon1, (exp->Params->IllumSquareOrig.y));
cvSetTrackbarPos("xRad", exp->WinCon1, (exp->Params->IllumSquareRad.width));
cvSetTrackbarPos("yRad", exp->WinCon1, (exp->Params->IllumSquareRad.height));
cvSetTrackbarPos("IllumSweepHT", exp->WinCon1, (exp->Params->IllumSweepHT));
cvSetTrackbarPos("IllumSweepOn", exp->WinCon1, (exp->Params->IllumSweepOn));
/** Threshold **/
cvSetTrackbarPos("Threshold", exp->WinCon1, (exp->Params->BinThresh));
cvSetTrackbarPos("Gauss=x*2+1",exp->WinCon1, exp->Params->GaussSize);
/** Updated Temporal IQ **/
/** Temporal Coding **/
cvSetTrackbarPos("TemporalIQ", exp->WinCon1, (exp->Params->TemporalOn));
cvSetTrackbarPos("IllumDuration", exp->WinCon1,
(exp->Params->IllumDuration));
/** Protocol Stuff **/
/** If we have loaded a protocol, update protocol specific sliders **/
if (exp->pflag) {
cvSetTrackbarPos("Protocol", exp->WinCon2, exp->Params->ProtocolUse);
cvSetTrackbarPos("ProtoStep", exp->WinCon2,
(exp->Params->ProtocolStep));
}
/** Floodlight **/
cvSetTrackbarPos("FloodLight", exp->WinCon2,exp->Params->IllumFloodEverything);
/** Record **/
cvSetTrackbarPos("RecordOn", exp->WinCon1, (exp->Params->Record));
/** Record **/
cvSetTrackbarPos("On", exp->WinCon1, (exp->Params->OnOff));
/**Stage Speed **/
cvSetTrackbarPos("StageSpeed",exp->WinCon1,(exp->Params->stageSpeedFactor));
return;
}
// Runs the dot detector and sends detected dots to server on port TODO Implement headless. Needs more config options and/or possibly a config file first though
int run( const char *serverAddress, const int serverPort, char headless ) {
char calibrate_exposure = 0, show = ~0, flip = 0, vflip = 0, done = 0, warp = 0; //"Boolean" values used in this loop
char noiceReduction = 2; //Small counter, so char is still ok.
int i, sockfd; //Generic counter
int dp = 0, minDist = 29, param1 = 0, param2 = 5; // Configuration variables for circle detection
int minDotRadius = 1;
int detected_dots; //Detected dot counter
int returnValue = EXIT_SUCCESS;
int captureControl; //File descriptor for low-level camera controls
int currentExposure = 150;
int maxExposure = 1250; //Maximum exposure supported by the camera TODO Get this from the actual camera
Color min = { 0, 70, 0, 0 }; //Minimum color to detect
Color max = { 255, 255, 255, 0 }; //Maximum color to detect
CvScalar colorWhite = cvScalar( WHITE ); //Color to draw detected dots on black and white surface
BoundingBox DD_mask; //The box indicating what should and what should not be considered for dot search
BoundingBox DD_transform; //The box indicating the plane we are looking at( and as such is the plane we would transform from )
BoundingBox DD_transform_to; //The plane we are transforming to
CvCapture *capture = NULL; //The camera
CvMemStorage *storage; //Low level memory area used for dynamic structures in OpenCV
CvSeq *seq; //Sequence to store detected dots in
IplImage *grabbedImage = NULL; //Raw image from camera( plus some overlay in the end )
IplImage *imgThreshold = NULL; //Image with detected dots
IplImage *mask = NULL; //Mask to be able to remove uninteresting areas
IplImage *coloredMask = NULL; //Mask to be able to indicate above mask on output image
CvFont font; //Font for drawing text on images
SendQueue *queue; //Head of the linked list that is the send queue
char strbuf[255]; //Generic buffer for text formatting( with sprintf())
struct timeval oldTime, time, diff; //Structs for measuring FPS
float lastKnownFPS = 0; //Calculated FPS
CvMat* pointRealMat = cvCreateMat( 1,1,CV_32FC2 ); //Single point matrix for point transformation
CvMat* pointTransMat = cvCreateMat( 1,1,CV_32FC2 ); //Single point matrix for point transformation
CvMat* transMat = cvCreateMat( 3,3,CV_32FC1 ); //Translation matrix for transforming input to a straight rectangle
ClickParams clickParams = { TOP_LEFT, NULL, &DD_transform_to, transMat }; //Struct holding data needed by mouse-click callback function
// Set up network
sockfd = initNetwork( serverAddress, serverPort );
if( sockfd == -1 ) {
fprintf( stderr, "ERROR: initNetwork returned -1\n");
return EXIT_FAILURE;
}
queue = initSendQueue();
if( openCamera( &capture, &captureControl ) == 0 ) {
fprintf( stderr, "ERROR: capture is NULL \n" );
return EXIT_FAILURE;
}
if( ( disableAutoExposure( captureControl ) ) == -1 ) {
fprintf( stderr, "ERROR: Cannot disable auto exposure \n" );
//return EXIT_FAILURE;
}
if( ( updateAbsoluteExposure( captureControl, currentExposure ) ) == 0 ) {
fprintf( stderr, "ERROR: Cannot set exposure\n");
}
// Create a window in which the captured images will be presented
cvNamedWindow( imagewindowname, CV_WINDOW_AUTOSIZE | CV_WINDOW_KEEPRATIO | CV_GUI_NORMAL );
// Create a window to hold the configuration sliders and the detection frame TODO This is kind of a hack. Make a better solution
cvNamedWindow( configwindowname, CV_WINDOW_AUTOSIZE | CV_WINDOW_KEEPRATIO | CV_GUI_NORMAL );
// Create a window to hold the transformed image. Handy to see how the dots are translated, but not needed for functionality
if( warp ) cvNamedWindow( warpwindowname, CV_WINDOW_AUTOSIZE | CV_WINDOW_KEEPRATIO | CV_GUI_NORMAL );
// Create sliders to adjust the lower color boundry
cvCreateTrackbar( red_lable , configwindowname, &min.red, 255, NULL );
cvCreateTrackbar( green_lable, configwindowname, &min.green, 255, NULL );
cvCreateTrackbar( blue_lable , configwindowname, &min.blue, 255, NULL );
//Create sliters for the contour based dot detection
cvCreateTrackbar( min_area_lable, configwindowname, &minDotRadius,255, NULL );
/* Slider for manual exposure setting */
cvCreateTrackbar( exposure_lable, configwindowname, ¤tExposure, maxExposure, NULL );
//Create the memory storage
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 );
// Grab an initial image to be able to fetch image size before the main loop.
grabbedImage = cvQueryFrame( capture );
//Move the two windows so both are visible at the same time
cvMoveWindow( imagewindowname, 0, 10 );
cvMoveWindow( configwindowname, grabbedImage->width+2, 10 );
//TODO Move these three inits to a function
// Set masking defaults TODO load from file? Specify file for this file loading?
DD_mask.topLeft.x = 0;
DD_mask.topLeft.y = 0;
DD_mask.topRight.x = grabbedImage->width-1;
DD_mask.topRight.y = 0;
DD_mask.bottomLeft.x = 0;
DD_mask.bottomLeft.y = grabbedImage->height-1;
DD_mask.bottomRight.x = grabbedImage->width-1;
DD_mask.bottomRight.y = grabbedImage->height-1;
// Set transformation defaults TODO load from file? Specify file for this file loading?
DD_transform.topLeft.x = 0;
DD_transform.topLeft.y = 0;
DD_transform.topRight.x = grabbedImage->width-1;
DD_transform.topRight.y = 0;
DD_transform.bottomLeft.x = 0;
DD_transform.bottomLeft.y = grabbedImage->height-1;
DD_transform.bottomRight.x = grabbedImage->width-1;
DD_transform.bottomRight.y = grabbedImage->height-1;
// Set the transformation destination
DD_transform_to.topLeft.x = 0;
DD_transform_to.topLeft.y = 0;
DD_transform_to.topRight.x = grabbedImage->width-1;
DD_transform_to.topRight.y = 0;
DD_transform_to.bottomLeft.x = 0;
DD_transform_to.bottomLeft.y = grabbedImage->height-1;
DD_transform_to.bottomRight.x = grabbedImage->width-1;
DD_transform_to.bottomRight.y = grabbedImage->height-1;
calculateTransformationMatrix( &DD_transform, &DD_transform_to, transMat );
// Set callback function for mouse clicks
cvSetMouseCallback( imagewindowname, calibrateClick, ( void* ) &clickParams );
gettimeofday( &oldTime, NULL );
// Main loop. Grabbs an image from cam, detects dots, sends dots,and prints dots to images and shows to user
while( !done ) {
//PROFILING_PRO_STAMP(); //Uncomment this and the one in the end of the while-loop, and comment all other PROFILING_* to profile main-loop
// ------ Common actions
cvClearMemStorage( storage );
detected_dots = 0;
//Grab a fram from the camera
PROFILING_PRO_STAMP();
grabbedImage = cvQueryFrame( capture );
PROFILING_POST_STAMP( "cvQueryFrame");
if( grabbedImage == NULL ) {
fprintf( stderr, "ERROR: frame is null...\n" );
getchar();
returnValue = EXIT_FAILURE;
break;
}
//Flip images to act as a mirror.
if( show && flip ) {
cvFlip( grabbedImage, grabbedImage, 1 );
}
if( show && vflip ) {
cvFlip( grabbedImage, grabbedImage, 0 );
}
// ------ State based actions
switch( state ) {
case GRAB_DOTS:
//Create detection image
imgThreshold = cvCreateImage( cvGetSize( grabbedImage ), 8, 1 );
cvInRangeS( grabbedImage, cvScalar( DD_COLOR( min )), cvScalar( DD_COLOR( max )), imgThreshold );
//Mask away anything not in our calibration area
mask = cvCreateImage( cvGetSize( grabbedImage ), 8, 1 );
cvZero( mask );
cvFillConvexPoly( mask, ( CvPoint* ) &DD_mask, 4, cvScalar( WHITE ), 1, 0 );
cvAnd( imgThreshold, mask, imgThreshold, NULL );
// Invert mask, increase the number of channels in it and overlay on grabbedImage //TODO Tint the mask red before overlaying
cvNot( mask, mask );
coloredMask = cvCreateImage( cvGetSize( grabbedImage ), grabbedImage->depth, grabbedImage->nChannels );
cvCvtColor( mask, coloredMask, CV_GRAY2BGR );
cvAddWeighted( grabbedImage, 0.95, coloredMask, 0.05, 0.0, grabbedImage );
// Reduce noise.
// Erode is kind of floor() of pixels, dilate is kind of ceil()
// I'm not sure which gives the best result.
switch( noiceReduction ) {
case 0: break; //No noice reduction at all
case 1: cvErode( imgThreshold, imgThreshold, NULL, 2 ); break;
case 2: cvDilate( imgThreshold, imgThreshold, NULL, 2 ); break;
}
// Warp the warp-image. We are reusing the coloredMask variable to save some space
PROFILING_PRO_STAMP();
if( show && warp ) cvWarpPerspective( grabbedImage, coloredMask, transMat, CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS, cvScalarAll( 0 ));
PROFILING_POST_STAMP( "Warping perspective" );
// Find all dots in the image
PROFILING_PRO_STAMP();
// Clear old data from seq
seq = 0;
// Find the dots
cvFindContours(
imgThreshold,
storage,
&seq,
sizeof( CvContour ),
CV_RETR_LIST,
CV_CHAIN_APPROX_SIMPLE,
cvPoint( 0,0 )
);
// cvFindContours destroys the original image, so we wipe it here
// and then repaints the detected dots later
cvZero( imgThreshold );
PROFILING_POST_STAMP( "Dot detection" );
//Process all detected dots
PROFILING_PRO_STAMP();
for( ; seq != 0; seq = seq->h_next ) {
// Calculate radius of the detected contour
CvRect rect =( ( CvContour * )seq )->rect;
float relCenterX = rect.width / 2;
float relCenterY = rect.height / 2;
// Make sure the dot is big enough
if( relCenterX < minDotRadius || relCenterY < minDotRadius ) {
continue;
}
// Note that we have found another dot
++detected_dots;
// Transform the detected dot according to transformation matrix.
float absCenter[] = { rect.x + relCenterX, rect.y + relCenterY };
pointRealMat->data.fl = absCenter;
cvPerspectiveTransform( pointRealMat, pointTransMat, transMat );
// Draw the detected contour back to imgThreshold
// Draw the detected dot both to real image and to warped( if warp is active )
if( show ) {
cvDrawContours( imgThreshold, seq, colorWhite, colorWhite, -1, CV_FILLED, 8, cvPoint( 0,0 ) );
drawCircle( absCenter[0], absCenter[1], ( relCenterX + relCenterY ) / 2, grabbedImage );
if( warp ) {
drawCircle( pointTransMat->data.fl[0], pointTransMat->data.fl[1], ( relCenterX + relCenterY ) / 2, coloredMask );
}
}
// Add detected dot to to send queue
addPointToSendQueue( pointTransMat->data.fl, queue );
}
PROFILING_POST_STAMP("Painting dots");
//Calculate framerate
gettimeofday( &time, NULL );
timeval_subtract( &diff, &time, &oldTime );
lastKnownFPS = lastKnownFPS * 0.7 + ( 1000000.0 / diff.tv_usec ) * 0.3; //We naïvly assume we have more then 1 fps
oldTime = time;
//Send the dots detected this frame to the server
PROFILING_PRO_STAMP();
sendQueue( sockfd, queue );
clearSendQueue( queue );
PROFILING_POST_STAMP( "Sending dots" );
/* If calibrating, do the calibration */
if( calibrate_exposure ) {
int ret;
ret = calibrateExposureLow( captureControl, detected_dots, ¤tExposure, DD_MAX_EXPOSURE, lastKnownFPS );
switch( ret ) {
case 0: // We are done. Let's leave calibration mode
calibrate_exposure = 0;
printf( "done\n" );
break;
case -1: // We hit the upper limit with no detected dots
fprintf( stderr, "Reached upper limit (%d). Aborting!\n", DD_MAX_EXPOSURE );
calibrate_exposure = 0;
break;
case -2: // We hit lower limit with more then one dot detected
fprintf( stderr, "Too bright. More then one dot found even with minimal exposure. Aborting!\n");
calibrate_exposure = 0;
break;
case -3: //No conclusive results.
fprintf( stderr, "No conclusive results. Giving up\n" );
calibrate_exposure = 0;
break;
}
}
break; //End of GRAB_DOTS
case SELECT_TRANSFORM:
//Falling through here. Poor man's multi-case clause. Not putting this in default as we might
//want to do different things in these two some day.
case SELECT_MASK:
snprintf( strbuf, sizeof( strbuf ), "Select %s point", pointTranslationTable[clickParams.currentPoint]);
cvDisplayOverlay( imagewindowname, strbuf, 5 );
break; //End of SELECT_MASK and SELECT_TRANSFORM
}
// Paint the corners of the detecting area and the calibration area
paintOverlayPoints( grabbedImage, &DD_transform );
//Print some statistics to the image
if( show ) {
snprintf( strbuf, sizeof( strbuf ), "Dots: %i", detected_dots ); //Print number of detected dots to the screen
cvPutText( grabbedImage, strbuf, cvPoint( 10, 20 ), &font, cvScalar( WHITE ));
snprintf( strbuf, sizeof( strbuf ), "FPS: %.1f", lastKnownFPS );
cvPutText( grabbedImage, strbuf, cvPoint( 10, 40 ), &font, cvScalar( WHITE ));
cvCircle( grabbedImage, cvPoint( 15, 55 ), minDotRadius, cvScalar( min.blue, min.green, min.red, min.alpha ), -1, 8, 0 ); // Colors given in order BGR-A, Blue, Green, Red, Alpha
}
//Show images
PROFILING_PRO_STAMP();
if( show ) {
cvShowImage( configwindowname, imgThreshold );
cvShowImage( imagewindowname, grabbedImage );
if( warp ) cvShowImage( warpwindowname, coloredMask );
}
PROFILING_POST_STAMP("Showing images");
//Release the temporary images
cvReleaseImage( &imgThreshold );
cvReleaseImage( &mask );
cvReleaseImage( &coloredMask );
/* Update exposure if needed */
updateAbsoluteExposure( captureControl, currentExposure );
cvSetTrackbarPos( exposure_lable, configwindowname, currentExposure );
//If ESC key pressed, Key=0x10001B under OpenCV 0.9.7( linux version ),
//remove higher bits using AND operator
i = ( cvWaitKey( 10 ) & 0xff );
switch( i ) {
case 'g':
makeCalibrate( &DD_transform, &DD_transform_to, transMat, capture, captureControl, 20 );
updateAbsoluteExposure( captureControl, currentExposure+1 );
break;
case 'e':
toggleCalibrationMode( &calibrate_exposure, ¤tExposure );
break; /* Toggles calibration mode */
case 'c':
openCamera( &capture, &captureControl );
break;
case 's':
show = ~show;
break; //Toggles updating of the image. Can be useful for performance of slower machines... Or as frame freeze
case 'm':
state = SELECT_MASK;
clickParams.currentPoint = TOP_LEFT;
clickParams.DD_box = &DD_mask;
break; //Starts selection of masking area. Will return to dot detection once all four points are set
case 't':
state = SELECT_TRANSFORM;
clickParams.currentPoint = TOP_LEFT;
clickParams.DD_box = &DD_transform;
break; //Starts selection of the transformation area. Returns to dot detection when done.
case 'f':
flip = ~flip;
break; //Toggles horizontal flipping of the image
case 'v':
vflip = ~vflip;
break; //Toggles vertical flipping of the image
case 'w':
warp = ~warp;
toggleWarpOutput( warp );
break; //Toggles showing the warped image
case 'n':
noiceReduction = ( noiceReduction + 1 ) % 3;
break; //Cycles noice reduction algorithm
case 'q': //falling through here to quit
case 27:
done = 1;
break; //ESC. Kills the whole thing( in a nice and controlled manner )
}
fflush( stdout ); //Make sure everything in the buffer is printed before we go on
//PROFILING_POST_STAMP("Main loop");
} //End of main while-loop
// Release the capture device and do some housekeeping
cvReleaseImage( &grabbedImage );
cvReleaseCapture( &capture );
cvReleaseMemStorage( &storage );
cvDestroyWindow( imagewindowname );
cvDestroyWindow( configwindowname );
if( warp ) cvDestroyWindow( warpwindowname ); //If now warp it is already destroyed
destroySendQueue( queue );
close( sockfd );
close( captureControl );
return returnValue;
}