void CApplication::displayWindow()
{
sf::VideoMode mode;
mode.width = m_settings.getValue("Window", "width", "800").toUnsignedInt32();
mode.height = m_settings.getValue("Window", "height", "600").toUnsignedInt32();
mode.bitsPerPixel = 32;
CString title = m_settings.getValue("TEngine", "title", "TEngine Application");
bool fullScreen = m_settings.getBooleanValue("Window", "fullscreen" , false);
displayWindow(mode, title, fullScreen);
}
//---------------------------------------------------------------------------
void File_Exr::Data_Parse()
{
if (CC4(Buffer+Buffer_Offset)==0x762F3101) //"v/1"+1 //Header
Header();
else if (name=="comments" && type=="string")
comments();
else if (name=="compression" && type=="compression" && Element_Size==1)
compression();
else if (name=="dataWindow" && type=="box2i" && Element_Size==16)
dataWindow();
else if (name=="displayWindow" && type=="box2i" && Element_Size==16)
displayWindow();
else if (name=="pixelAspectRatio" && type=="float" && Element_Size==4)
pixelAspectRatio();
else
Skip_XX(Element_Size, "value");
}
// Detect keypoints and find
cv::Mat AntiShake::antiShake(Mat &img_1, Mat &img_2, int matches_type, int featurePoints, int corePx,
double absoluteRelation) {
Mat workImage1, workImage2;
reduceDifferences(img_1, img_2, workImage1, workImage2, 7, 7); // STEPS 1 to 4 here
// STEP 5: KeyPoint Detection:
cv::FeatureDetector *detector = new cv::FastFeatureDetector(corePx, true);
std::vector<KeyPoint> keypoints_1, keypoints_2;
detector->detect(workImage1, keypoints_1);
detector->detect(workImage2, keypoints_2);
cout << "==== STEP 5 complete: keypoints detected, (keypoints1.size(), keypoints2.size()) = ("
<< keypoints_1.size() << ", " << keypoints_2.size() << ")" << endl;
delete (detector);
// STEP 6: Calculate descriptors (feature vectors)
cv::DescriptorExtractor *extractor = new cv::BriefDescriptorExtractor();
Mat descriptors_1, descriptors_2;
extractor->compute(workImage1, keypoints_1, descriptors_1);
extractor->compute(workImage2, keypoints_2, descriptors_2);
cout << "==== STEP 6 complete: extract descriptors" << endl;
delete (extractor);
// STEP 7: Get Matches
vector<DMatch> good_matches;
std::vector<Point2f> pts1, pts2;
this->getBestMatches(matches_type, featurePoints, good_matches, pts1, pts2, descriptors_1,
descriptors_2, keypoints_1, keypoints_2, workImage1.rows, workImage1.cols, absoluteRelation);
Mat img_matches;
drawMatches(workImage1, keypoints_1, workImage2, keypoints_2, good_matches, img_matches,
Scalar::all(-1), Scalar::all(-1), vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
if (shouldPrint)
displayWindow(img_matches, "MATCHES");
cout << "==== STEP 7 complete: finished matching descriptors: " << featurePoints << endl;
// STEP 8: Find Homography:
vector<uchar> inliers(pts1.size(), 0);
Mat homography = validateHomography(pts1, pts2, inliers, true);
cout << "==== STEP 8 complete: finished calculating right homographY." << endl;
return homography;
}
//---------------------------------------------------------------------------
void File_Exr::Data_Parse()
{
if (name_End==0)
ImageData();
else if (name=="channels" && type=="chlist")
channels();
else if (name=="comments" && type=="string")
comments();
else if (name=="compression" && type=="compression" && Element_Size==1)
compression();
else if (name=="dataWindow" && type=="box2i" && Element_Size==16)
dataWindow();
else if (name=="displayWindow" && type=="box2i" && Element_Size==16)
displayWindow();
else if (name=="pixelAspectRatio" && type=="float" && Element_Size==4)
pixelAspectRatio();
else
Skip_XX(Element_Size, "value");
}
/* arrange windows. arg:
* -1: arrange all windows
* != -1: arrange only this window id
*/
void arrange_window(pjsua_vid_win_id wid)
{
#if PJSUA_HAS_VIDEO
pjmedia_coord pos;
int i, last;
pos.x = 0;
pos.y = 10;
last = (wid == PJSUA_INVALID_ID) ? PJSUA_MAX_VID_WINS : wid;
for (i=0; i<last; ++i) {
pjsua_vid_win_info wi;
pj_status_t status;
status = pjsua_vid_win_get_info(i, &wi);
if (status != PJ_SUCCESS)
continue;
if (wid == PJSUA_INVALID_ID)
pjsua_vid_win_set_pos(i, &pos);
if (wi.show)
pos.y += wi.size.h;
}
if (wid != PJSUA_INVALID_ID)
pjsua_vid_win_set_pos(wid, &pos);
#ifdef USE_GUI
displayWindow(wid);
#endif
#else
PJ_UNUSED_ARG(wid);
#endif
}
// Shows the image in a window
void AntiShake::displayWindow(Mat image, string filename) {
displayWindow(image, filename, false);
}
int main(int argc,char* argv[] )
{
//!< In this variable the current frame is stored
cv::Mat frame;
cv::Mat sobel;
cv::Mat canny;
cv::Mat gray;
cv::Mat scharr;
cv::Mat laplacian;
std::string displayWindow("Display");
int cam;
bool exitVal = false ;
if ( argc <= 1) {
std::cout << "Usage : ./camera CAM_NUM" << std::endl;
std::cout << "CAM_NUM is the camera we wish to open!" << std::endl;
std::cout << "Default Laptop Camera will be opened!" << std::endl;
cam = 0;
}
else
cam = atoi(argv[1]);
cv::VideoCapture camera(cam);
if (!camera.isOpened()) {
std::cout << "Cannot open the video file" << std::endl;
return -1;
}
int KeyPressed=255;
int i=0;
std::cout << "Press esc if you want to stop the process" << std::endl;
char state;
while (true) {
camera.grab();
camera.retrieve(frame);
cv::imshow("BGR colorspace", frame);
//!< Apply Sobel edge detections algorithm
applySobel (frame, &sobel);
cv::imshow("Sobel algorithm", sobel);
//!< Apply Canny edge detection algorithm
cvtColor( frame, gray, CV_BGR2GRAY );
applyCanny( gray, &canny);
cv::imshow("Canny algorithm", canny);
//!< Apply Scharr edge detection algorithm
applyScharr (frame, &scharr);
cv::imshow("Scharr algorithm", scharr);
//!< Apply laplacian edge detection algorithm
applyLaplacian (frame, &laplacian);
cv::imshow("Laplacian algorithm", laplacian);
KeyPressed=cvWaitKey(10) & 255; //!< wait for 'esc' key press for 10 ms
switch (KeyPressed) {
case (char)27:
exitVal = true;
break;
default:
break;
}
if (exitVal) //!< KeyPressed==esc
break;
}
}
