objectdetector.cpp

void ObjectDetector::preview(cv::Mat &rgb, const std::vector<cv::Rect> &boxes, const std::vector<int> &labels, const std::vector<float> &confidences) const
{
    // This method is responsible for marking up the raw BGR frames with the inferences from the
    // neural network. Since all of our object detector networks output bounding boxes, labels, and confidences,
    // let's mark up the frames with those items.
    std::string artext = std::string("");
    for (std::size_t i = 0; i < boxes.size(); i++)
    {
        // Draw a bounding box around the detected object. Use a new color each time
        // up to some point, at which point we wrap around and start reusing colors.
        int color_index = labels[i] % label::colors().size();
        cv::rectangle(rgb, boxes[i], label::colors().at(color_index), 0.5);

        // Draw the label. Use the same color. If we can't figure out the label
        // (because the network output something unexpected, or there is no labels file),
        // we just use the class index.
        auto label = util::get_label(labels[i], this->class_labels) + ": " + util::to_string_with_precision(confidences[i]*100, 2) + "%";
        artext = ar::get_ar_label(util::get_label(labels[i], this->class_labels)) + ".";
        auto origin = boxes[i].tl() + cv::Point(3, 20);
        auto font = cv::FONT_HERSHEY_DUPLEX;
        auto fontscale = 0.5;
        auto color = cv::Scalar(0, 0, 0); //cv::Scalar(label::colors().at(color_index));
        auto thickness = 1;
        auto textline = cv::LINE_AA;
        cv::putText(rgb, label, origin, font, fontscale, color, thickness, textline);
        int width = 400;
        auto arcolor = cv::Scalar(0, 0, 0);
        std::string extract = artext;
        std::size_t substrlength = 40;
        if(extract.length() > substrlength) {
            std::size_t lineNumber = 50;
            
            if(extract.length() > 400) {
                extract = extract.substr(0, 400);
            }
            
            std::string remaining = extract;
            while (remaining.length() > substrlength)
            {
                std::string shortstr = remaining.substr(0,substrlength);
                remaining = remaining.substr(substrlength-1);
                cv::putText(rgb, shortstr, boxes[i].tl() + cv::Point(3, lineNumber), font, fontscale, arcolor, thickness, textline);
                lineNumber = lineNumber + 17;
            }
            cv::putText(rgb, remaining, boxes[i].tl() + cv::Point(3, lineNumber), font, fontscale, arcolor, thickness, textline);
            cv::Mat overlay;
            rgb.copyTo(overlay);
            double alpha = 0.4;  // Transparency factor.
            cv::Rect rect(boxes[i].tl().x, boxes[i].tl().y, width, 225);
            cv::rectangle(overlay, rect, cv::Scalar(231, 231, 231), -1);

            // blend the overlay with the rgb image
            cv::addWeighted(overlay, alpha, rgb, 1 - alpha, 0, rgb);
            cv::Rect boundryrect(boxes[i].tl().x, boxes[i].tl().y, width, 225);
            cv::rectangle(rgb, boundryrect, cv::Scalar(255, 255, 255), 2);
        }
    }
}