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Home DnnOpenVinoDetector C++ lib. Objects detection based on Intel OpenVino API
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DnnOpenVinoDetector C++ lib. Objects detection based on Intel OpenVino API

€1,500.00

DnnOpenVinoDetector C++ library version 1.0.1 is designed for automatic detection of objects on videos through the utilization of neural networks.

LICENSE: We sell source code of this library as is, without future updates and technical support according to perpetual non-exclusive royalty-free license. You pay once and can use this library in your software and hardware products without limits. Please read the license agreement before purchasing: DOWNLOAD LICENSE. You can buy technical support service for this product.

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DnnOpenVinoDetector C++ library version 1.0.1 is designed for automatic detection of objects on videos through the utilization of neural networks.

LICENSE: We sell source code of this library as is, without future updates and technical support according to perpetual non-exclusive royalty-free license. You pay once and can use this library in your software and hardware products without limits. Please read the license agreement before purchasing: DOWNLOAD LICENSE. You can buy technical support service for this product.

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DnnOpenVinoDetector C++ library version 1.0.1 is designed for automatic detection of objects on videos through the utilization of neural networks.

LICENSE: We sell source code of this library as is, without future updates and technical support according to perpetual non-exclusive royalty-free license. You pay once and can use this library in your software and hardware products without limits. Please read the license agreement before purchasing: DOWNLOAD LICENSE. You can buy technical support service for this product.

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You can by this software online by card or you can buy the software by bank transfer. Bank transfer available only for companies. To buy software by bank transfer please send us request to info@constantrobotics.com. Also, you can buy technical support service for this product.

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Programmer’s manual: DOWNLOAD

Demo application to test library on your video and with your models (test model and video included): DOWNLOAD

Overview

DnnOpenVinoDetector C++ library version 1.0.1 is designed for automatic detection of objects on videos through the utilization of neural networks. The library is implemented in C++ (C++17 standard) and exclusively relies only on one third-party library, which is Intel's OpenVINO™ runtime. The library supports various neural network models, if only model is supported by OpenVINO and has standard one-batch output (eg. yolov5). NN model can be specified in detector parameters, library inherits its interface from the ObjectDetector class, offering flexible and customizable parameters. The library provides simple interface.

Simple interface

class DnnOpenVinoDetector : public ObjectDetector
{
public:
    /// Get string of current library version.
    static std::string getVersion();
    
    /// Init object detector.
    bool initObjectDetector(ObjectDetectorParams& params) override;
    
    /// Set object detector param.
    bool setParam(ObjectDetectorParam id, float value) override;
    
    /// Get object detector param value.
    float getParam(ObjectDetectorParam id) override;
    
    /// Get object detector params structure.
    void getParams(ObjectDetectorParams& params) override;
    
    /// Get list of objects.
    std::vector<Object> getObjects() override;
    
    /// Execute command.
    bool executeCommand(ObjectDetectorCommand id) override;
    
    /// Perform detection.
    bool detect(cr::video::Frame& frame) override;
    
    /// Set detection mask.
    bool setMask(cr::video::Frame mask) override;
    
    /// Decode command and execute command.
    bool decodeAndExecuteCommand(uint8_t* data, int size) override;
}

Simple example

#include <opencv2/opencv.hpp>
#include "DnnOpenVinoDetector.h"

int main(void)
{
    // Open video file "test.mp4".
    cv::VideoCapture videoSource;
    if (!videoSource.open("test.mp4"))
        return -1;

    // Create and init detector.
    cr::detector::DnnOpenVinoDetector detector;
    cr::detector::ObjectDetectorParams params;
    params.initString = "./yolov7s.onnx;640;640";
    params.maxObjectHeight = 96;
    params.maxObjectWidth = 96;
    params.minObjectHeight = 4;
    params.minObjectHeight = 4;
    params.type = 1;
    detector.initObjectDetector(params);

    // Create frames.
    cv::Mat frameBgrOpenCv;

    // Main loop.
    while (true) {
        // Capture next video frame.
        videoSource >> frameBgrOpenCv;
        if (frameBgrOpenCv.empty()) {
            // If we have video file we can set initial position to replay.
            detector.executeCommand(cr::detector::ObjectDetectorCommand::RESET);
            videoSource.set(cv::CAP_PROP_POS_FRAMES, 0);
            continue;
        }

        // Copy frame data from OpenCv frame to Frame.
        cr::video::Frame frameBgr;
        frameBgr.fourcc = cr::video::Fourcc::BGR24;
        frameBgr.width = frameBgrOpenCv.size().width;
        frameBgr.height = frameBgrOpenCv.size().height;
        frameBgr.size = frameBgr.width * frameBgr.height * 3;
        frameBgr.data = frameBgrOpenCv.data;

        // Detect objects.
        detector.detect(frameBgr);

        // Get list of objects.
        std::vector<cr::detector::Object> objects = detector.getObjects();

        // Draw detected objects.
        for (int n = 0; n < objects.size(); ++n) {
            rectangle(frameBgrOpenCv, cv::Rect(objects[n].x, objects[n].y,
                      objects[n].width, objects[n].height),
                      cv::Scalar(0, 0, 255), 1);
            putText(frameBgrOpenCv, std::to_string(objects[n].p),
                    cv::Point(objects[n].x, objects[n].y),
                    1, 1, cv::Scalar(0, 0, 255));
        }

        // Show video.
        cv::imshow("VIDEO", frameBgrOpenCv);
        // Wait ESC.
        if (cv::waitKey(1) == 27)
            return -1;
    }
    return 1;
}

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ConstantRobotics conducts scientific research in video processing, control protocols, and data exchange. Our diverse team of engineers develops software libraries and applications to simplify complex problems. Customers can test our libraries on their own data before making a purchase. Detailed documentation is available on our website. Our main focus is creating real-time algorithms that run on any platform.

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ConstantRobotics Sp. z o.o. Warsaw, Poland, VAT ID: PL5252930273, info@constantrobotics.com

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Our software libraries are distributed under perpetual licenses. We don't restrict distribution of software libraries as a part of your hardware and software products. Our library prices are the same for all our clients and are based on the following principle: you can create a counterpart of our algorithms with the same or better characteristics, but the cost of your own research will be significantly higher than buying ready-made libraries. By purchasing our libraries you get a solution with proven performance. Two licenses are available for our products: a perpetual license for the compiled version of the library and a perpetual license for the source code. You pay once at the time of purchase. Download licenses:

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