//更新场景图像
void MeasureMarkersWindow::updatePixmap(unsigned char* leftBuffer,
unsigned char* rightBuffer) {
QImage li = convertToQImage(leftBuffer);
QImage ri = convertToQImage(rightBuffer);
mLastLeft = li;
mLastRight = ri;
mLeftCameraPixmap->setPixmap(QPixmap::fromImage(li));
mRightCameraPixmap->setPixmap(QPixmap::fromImage(ri));
//更新图像
update();
}
void QOpenCvImageBox::putImage(IplImage *cvimage) {
if (isHsvAllImageConvertedEnabled()) {
// HSV conversion
hsvReduce(cvimage);
}
// Objs detection
if (isDetectionEnabled()) { // If I have a cascade file
if (detected_objs_array!=NULL) { // release the memory
delete [] detected_objs_array;
}
detected_objs_array=detect_objs(cvimage, storage, cascade, od_image_scale, objs_found, od_calc_time);
draw_objs(cvimage, objs_found, detected_objs_array, CV_RGB(255,0,0), od_image_scale, 0, 0);
// Sub Objs detection
if (isSubDetectionEnabled()) { // If I have a cascade file
for (int c=0; c<objs_found; c++) {
// Finding the image part
IplImage *cvSubImage=cvCreateImage(cvSize(detected_objs_array[0].width*od_image_scale, detected_objs_array[0].height*od_image_scale), IPL_DEPTH_8U, 3);
// Adapt the rect to the scale
CvRect scaledRect = cvRect(detected_objs_array[0].x*od_image_scale, detected_objs_array[0].y*od_image_scale, detected_objs_array[0].width*od_image_scale, detected_objs_array[0].height*od_image_scale);
// Setting the ROI
cvSetImageROI(cvimage, scaledRect);
// Copying a sub part
cvCopyImage(cvimage, cvSubImage);
// Resetting the ROI
cvResetImageROI(cvimage);
if (detected_sub_objs_array!=NULL) { // release the memory
delete [] detected_sub_objs_array;
}
detected_sub_objs_array=detect_objs(cvSubImage, sub_storage, sub_cascade, sub_od_image_scale, sub_objs_found, sub_od_calc_time);
ui->imageLabel->setPixmap(QPixmap::fromImage(convertToQImage(cvSubImage)));
draw_objs(cvimage, objs_found, detected_sub_objs_array, CV_RGB(0,255,0), sub_od_image_scale, scaledRect.x, scaledRect.y);
}
}
}
lucasKanadeOF(cvimage);
// Image conversion
ui->imageLabel->setPixmap(QPixmap::fromImage(convertToQImage(cvimage)));
}
//捕获一张图像
void MeasureMarkersWindow::capture() {
//先停止时钟
mTimer->stop();
static int COUNT = 0;
COUNT++;
QString name;
name.sprintf("%d", COUNT);
//先保存图像
QString leftname = mMeasureFolder + "left_" + name;
QString rightname = mMeasureFolder + "right_" + name;
mLastLeft.save(leftname + ".jpg");
mLastRight.save(rightname + ".jpg");
mImgWidth = mLastLeft.width();
mImgHeight = mLastLeft.height();
//读取图像，计算角点
cv::Mat li = cv::imread(leftname.toStdString() + ".jpg", CV_LOAD_IMAGE_UNCHANGED);
cv::Mat ri = cv::imread(rightname.toStdString() + ".jpg", CV_LOAD_IMAGE_UNCHANGED);
cv::Mat liGrey, riGrey;
cv::cvtColor(li, liGrey, cv::COLOR_BGR2GRAY);
cv::cvtColor(ri, riGrey, cv::COLOR_BGR2GRAY);
std::vector<cv::Point2f> left_markers = circleDetect(liGrey);
std::vector<cv::Point2f> right_markers = circleDetect(riGrey);
for (int i = 0; i < left_markers.size(); i++)
cv::circle(li, left_markers[i], 4, cv::Scalar(0, 0, 255), 3, 8, 0);
for (int i = 0; i < right_markers.size(); i++)
cv::circle(ri, right_markers[i], 4, cv::Scalar(0, 0, 255), 3, 8, 0);
//保存绘制的角点图像
cv::imwrite(leftname.toStdString() + ".bmp", li);
cv::imwrite(rightname.toStdString() + ".bmp", ri);
if (left_markers.size() == 2 && right_markers.size() == 2) {
//先暂停摄像头
preview();
//记录当前图像
mImgs.push_back(COUNT);
//显示绘制角点的图像
QImage lp = convertToQImage(li);
QImage rp = convertToQImage(ri);
mLeftCameraPixmap->setPixmap(QPixmap::fromImage(lp));
mRightCameraPixmap->setPixmap(QPixmap::fromImage(rp));
//提示找到角点
mStatusBar->showMessage(QString::fromWCharArray(L"成功找到标记点"));
int all = mImgs.size();
QString ta;
ta.sprintf(" %d/%d", all, all);
mCaps->setText(ta);
mSlider->setMaximum(mImgs.size());
mSlider->setValue(mImgs.size());
updateButtonState();
return;
} else {
//删除保存的图像
QFile::remove(leftname + ".jpg");
QFile::remove(rightname + ".jpg");
//计数回到为初始值
COUNT--;
//弹出对话框，提示没有找到角点
mStatusBar->showMessage(QString::fromWCharArray(L"没有找到标记点"));
QMessageBox::StandardButton btn2 = QMessageBox::warning(
0, //父窗口
QString::fromWCharArray(L"没有找到标记点"), //标题栏
QString::fromWCharArray(L"在当前的图像中，没有找到对应的标记点")); //文本内容
//重新开始
mTimer->start();
}
}
void BlobTrackingNode::process(const cv::Mat &img_input, const cv::Mat &img_mask, cv::Mat &img_output)
{
//This is output event
QList<DetectedEvent> blobEvent;
cv::Mat newInput;
img_input.copyTo(newInput);
if(img_input.empty() || img_mask.empty()){
return;
}
loadConfig();
if(firstTime){
saveConfig();
}
IplImage* frame = new IplImage(img_input);
cvConvertScale(frame, frame, 1, 0);
IplImage* segmentated = new IplImage(img_mask);
IplConvKernel* morphKernel = cvCreateStructuringElementEx(5, 5, 1, 1, CV_SHAPE_RECT, NULL);
cvMorphologyEx(segmentated, segmentated, NULL, morphKernel, CV_MOP_OPEN, 1);
cv::Mat temp = cv::Mat(segmentated);
if(showBlobMask){
//cv::imshow("test",temp);
ownerPlugin->updateFrameViewer("Tracking Mask",convertToQImage(temp));
}
IplImage* labelImg = cvCreateImage(cvGetSize(frame), IPL_DEPTH_LABEL, 1);
cvb::CvBlobs blobs;
cvb::cvLabel(segmentated, labelImg, blobs);
cvb::cvFilterByArea(blobs, minArea, maxArea);
if(debugBlob){
cvb::cvRenderBlobs(labelImg, blobs, frame, frame, CV_BLOB_RENDER_BOUNDING_BOX|CV_BLOB_RENDER_CENTROID|CV_BLOB_RENDER_ANGLE|CV_BLOB_RENDER_TO_STD);
}
else{
cvb::cvRenderBlobs(labelImg, blobs, frame, frame, CV_BLOB_RENDER_BOUNDING_BOX|CV_BLOB_RENDER_CENTROID|CV_BLOB_RENDER_ANGLE);
}
cvb::cvUpdateTracks(blobs, tracks,threshold_distance, threshold_inactive);
//At this point, we have assigned each blob in current frame in to a track. so we can iterate through active tracks, and
// find out out blobs within one of those tracks. Following loop does that. This is helpfull to have more generalized idea about
// relationship between blobs with increasing time.
for (cvb::CvTracks::const_iterator track = tracks.begin(); track!=tracks.end(); ++track)
{
if((*track).second->active != 0){
for(std::map<cvb::CvLabel,cvb::CvBlob *>::iterator it = blobs.begin() ; it != blobs.end(); it++){
cvb::CvLabel label = (*it).first;
cvb::CvBlob * blob = (*it).second;
if((*track).second->label == label){
//qDebug()<< blob->minx <<","<<blob->miny;
//This is smoothed time tracked blob lables
blobEvent.append(DetectedEvent("blob",QString("%1,%2,%3,%4,%5,%6,%7,%8").arg(frameIndex).arg((*track).first).arg(blob->centroid.x).arg(blob->centroid.y).arg(blob->minx).arg(blob->miny).arg(blob->maxx).arg(blob->maxy),1.0));
}
}
}
}
if(debugTrack){
cvb::cvRenderTracks(tracks, frame, frame, CV_TRACK_RENDER_ID|CV_TRACK_RENDER_BOUNDING_BOX|CV_TRACK_RENDER_TO_STD);
}
else{
cvb::cvRenderTracks(tracks, frame, frame, CV_TRACK_RENDER_ID|CV_TRACK_RENDER_BOUNDING_BOX);
}
if(showFrameID){
cv::Mat temp = cv::Mat(frame);
cv::putText(temp,QString("%1").arg(frameIndex).toStdString(),cv::Point(40,120),cv::FONT_HERSHEY_PLAIN,2,cv::Scalar(0,255,0),2);
}
if(showOutput){
cv::Mat temp = cv::Mat(frame);
ownerPlugin->updateFrameViewer("Tracking Output",convertToQImage(temp));
//cvShowImage("Blob Tracking", frame);
}
cv::Mat img_result(frame);
cv::putText(img_result,QString("%1").arg(QString::number(frameIndex)).toUtf8().constData(), cv::Point(10,30), CV_FONT_HERSHEY_PLAIN,1.0, CV_RGB(255,255,255));
img_result.copyTo(img_output);
cvReleaseImage(&labelImg);
delete frame;
delete segmentated;
cvReleaseBlobs(blobs);
cvReleaseStructuringElement(&morphKernel);
firstTime = false;
frameIndex++;
QImage input((uchar*)newInput.data, newInput.cols, newInput.rows, newInput.step1(), QImage::Format_RGB888);
QImage output((uchar*)img_output.data, img_output.cols, img_output.rows, img_output.step1(), QImage::Format_RGB888);
QList<QImage> images;
images.append(input);
images.append(output);
emit generateEvent(blobEvent,images);
//emit generateEvent(blobEvent);
}
