Method detectObjectsClip

src/CVObjectDetection.cpp:46–95

}

void CVObjectDetection::detectObjectsClip(openshot::Clip &video, size_t _start, size_t _end, bool process_interval)
{

    start = _start; end = _end;

    video.Open();

    if(error){
        return;
    }

    processingController->SetError(false, "");

    // Load names of classes
    std::ifstream ifs(classesFile.c_str());
    std::string line;
    while (std::getline(ifs, line)) classNames.push_back(line);

    // Load the network
    if(classesFile == "" || modelConfiguration == "" || modelWeights == "")
        return;
    net = cv::dnn::readNetFromDarknet(modelConfiguration, modelWeights);
    setProcessingDevice();

    size_t frame_number;
    if(!process_interval || end <= 1 || end-start == 0){
        // Get total number of frames in video
        start = (int)(video.Start() * video.Reader()->info.fps.ToFloat());
        end = (int)(video.End() * video.Reader()->info.fps.ToFloat());
    }

    for (frame_number = start; frame_number <= end; frame_number++)
    {
         // Stop the feature tracker process
        if(processingController->ShouldStop()){
            return;
        }

        std::shared_ptr<openshot::Frame> f = video.GetFrame(frame_number);

        // Grab OpenCV Mat image
        cv::Mat cvimage = f->GetImageCV();

        DetectObjects(cvimage, frame_number);

        // Update progress
        processingController->SetProgress(uint(100*(frame_number-start)/(end-start)));

    }
}

void CVObjectDetection::DetectObjects(const cv::Mat &frame, size_t frameId){
    // Get frame as OpenCV Mat