GraphSize OperationDrawer::drawOrSizeDiagram(DiagramDrawer &drawer,
OperationGraph &graph, const OperationDrawOptions &options, bool draw)
{
mCharHeight = static_cast<int>(drawer.getTextExtentHeight("W"));
int pad = mCharHeight / 3;
if(pad < 1)
pad = 1;
mPad = pad;
GraphPoint startpos(mCharHeight, mCharHeight);
GraphPoint pos = startpos;
GraphSize size;
GraphSize diagramSize;
int maxy = 0;
std::vector<int> classEndY;
for(size_t i=0; i<graph.mOpClasses.size(); i++)
{
OperationClass &opClass = graph.mOpClasses[i];
opClass.setPosition(pos);
size = drawClass(drawer, opClass, options, draw);
size_t condDepth = graph.getNestDepth(i);
size.x += static_cast<int>(condDepth) * mPad;
opClass.setSize(size);
pos.x += size.x + mCharHeight;
classEndY.push_back(startpos.y + size.y);
if(size.y > maxy)
maxy = size.y;
}
diagramSize.x = pos.x;
pos = startpos;
pos.y = startpos.y + maxy; // space between class rect and operations
std::set<const OperationDefinition*> drawnOperations;
for(const auto &oper : graph.mOperations)
{
if(drawnOperations.find(oper) == drawnOperations.end())
{
size = drawOperation(drawer, pos, *oper, graph, options,
drawnOperations, draw);
pos.y += size.y;
}
}
if(draw)
{
drawLifeLines(drawer, graph.mOpClasses, classEndY, pos.y);
}
diagramSize.y = pos.y + mCharHeight;
return diagramSize;
}
int main( )
{
// init input video source
// cvCaptureFromFile
// cv::VideoCapture captureInput("/Users/andriybas/Downloads/elephant_wild_life.m4v");
// cv::VideoCapture captureInput("/Users/andriybas/Documents/test.mov");
cv::VideoCapture captureInput(0);
if (!captureInput.isOpened()) {
std::cout << "Could not open input source" << std::endl;
return -1;
}
double fps = captureInput.get(CV_CAP_PROP_FPS); //get the frames per seconds of the video
std::cout << "Frame per seconds : " << fps << std::endl;
cv::namedWindow("window1", CV_WINDOW_AUTOSIZE);
int frameCount = 0;
// loading classifiers
cv::CascadeClassifier face_classifier(FACE_DETECT_CLASSIFIER_PATH);
cv::CascadeClassifier profile_face_classifier(PROFILE_FACE_DETECT_CLASSIFIER_PATH);
cv::CascadeClassifier elephant_classifier(ELEPHANT_DETECT_CLASSIFIER_PATH);
cv::CascadeClassifier banana_classifier(BANANA_DETECT_CLASSIFIER_PATH);
// creating detectors
Detector faceDetector(face_classifier, "face");
faceDetector.setScaleFactor(2);
// Detector faceProfileDetector(profile_face_classifier, "face_profile");
Detector elephantDetector(elephant_classifier, "elephant");
elephantDetector.setScaleFactor(3);
elephantDetector.setMinNeighbours(4);
Detector bananaDetector(banana_classifier, "banana");
bananaDetector.setScaleFactor(2);
bananaDetector.setMinNeighbours(6);
// init cascade
DetectCascade detectCascade;
detectCascade.addDetector(faceDetector);
// detectCascade.addDetector(faceProfileDetector);
detectCascade.addDetector(elephantDetector);
detectCascade.addDetector(bananaDetector);
VideoClassifier videoClassifier;
DetectedResults detectedObjects;
cv::Mat frame;
long totalTime = 0;
int detectedFrames = 0;
while(true)
{
captureInput >> frame;
if (frameCount < SKIP_COUNT) {
frameCount++;
} else {
frameCount = 0;
std::chrono::high_resolution_clock::time_point t1 = std::chrono::high_resolution_clock::now();
detectedObjects = detectCascade.detect(frame);
std::chrono::high_resolution_clock::time_point t2 = std::chrono::high_resolution_clock::now();
auto duration = std::chrono::duration_cast<std::chrono::milliseconds>( t2 - t1 ).count();
// std::cout << duration << std::endl;
totalTime += duration;
detectedFrames++;
videoClassifier.addFrame(detectedObjects);
}
drawDetectedFrames(frame, detectedObjects);
drawTags(frame, detectedObjects);
std::string videoClass = videoClassifier.getVideoClass();
drawClass(frame, videoClass);
imshow("Video classifier", frame );
if (detectedFrames > 100) {
std::cout << "Average frame detect: " << 1.0 * totalTime / detectedFrames << "\n";
detectedFrames = 0;
totalTime = 0;
}
// Press 'c' to escape
// if(waitKey(1) == 'c') break;
}
cv::waitKey(0);
return 0;
}