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I downloaded MobileNetSSD_deploy.caffemodel from https://github.com/chuanqi305/MobileNet-SSD I renamed deploy.prototxt to MobileNetSSD_deploy.txt. I used the supplied routine in OpenCvDnn example - I succeeded using Google Net caffe model. I changed the code to load the model - succeeded loading. I changed to : Mat inputBlob = blobFromImage(img, 1, Size(300,300), Scalar(104, 117, 123)); //Convert Mat to batch of images

cv::Mat prob = net.forward("detection_out"); I get an assertion at getMaxClass(prob, &classId, &classProb) Seem like prob not created at the forward. I am using 3.4.1 on windows 7 with vs2015. The full code: cv::String modelTxt = "MobileNetSSD_deploy.txt"; cv::String modelBin = "MobileNetSSD_deploy.caffemodel"; Net net = dnn::readNetFromCaffe(modelTxt, modelBin); if (net.empty()) { std::cerr << "Can't load network by using the following files: " << std::endl; std::cerr << "prototxt: " << modelTxt << std::endl; std::cerr << "caffemodel: " << modelBin << std::endl; std::cerr << "bvlc_googlenet.caffemodel can be downloaded here:" << std::endl; std::cerr << "http://dl.caffe.berkeleyvision.org/bvlc_googlenet.caffemodel" << std::endl; exit(-1); } std::cout << "Network loaded successfuly\n"; cv::String imageFile = "Goose.bmp"; // cv::String imageFile = "space_shuttle.jpg"; Mat img = imread(imageFile, IMREAD_UNCHANGED); int nChan = img.channels(); cout << nChan;

if (img.empty())
{
    std::cerr << "Can't read image from the file: " << imageFile << std::endl;
    exit(-1);
}
//GoogLeNet accepts only 224x224 RGB-images
Mat inputBlob = blobFromImage(img, 1, Size(300, 300), Scalar(104, 117, 123));   //Convert Mat to batch of images

net.setInput(inputBlob, "data");        //set the network input
cv::Mat prob = net.forward("detection_out");                          //compute output
int classId;
double classProb;
getMaxClass(prob, &classId, &classProb);//find the best class
std::vector<String> classNames = readClassNames();
std::cout << "Best class: #" << classId << " '" << classNames.at(classId) << "'" << std::endl;
std::cout << "Probability: " << classProb * 100 << "%" << std::endl;

I downloaded MobileNetSSD_deploy.caffemodel from https://github.com/chuanqi305/MobileNet-SSD I renamed deploy.prototxt to MobileNetSSD_deploy.txt. I used the supplied routine in OpenCvDnn example - I succeeded using Google Net caffe model. I changed the code to load the model - succeeded loading. I changed to : :

Mat inputBlob = blobFromImage(img, 1, Size(300,300), Size(*300,300*), Scalar(104, 117, 123));   //Convert Mat to batch of images
 
images

cv::Mat prob = net.forward("detection_out");

I get an assertion at getMaxClass(prob, &classId, &classProb) &classProb) Seem like prob not created at the forward. I am using 3.4.1 on windows 7 with vs2015. vs2015.

The full code: code:

 cv::String modelTxt = "MobileNetSSD_deploy.txt";
 cv::String modelBin = "MobileNetSSD_deploy.caffemodel";
 Net net = dnn::readNetFromCaffe(modelTxt, modelBin);
 if (net.empty())
 {
     std::cerr << "Can't load network by using the following files: " << std::endl;
     std::cerr << "prototxt:   " << modelTxt << std::endl;
     std::cerr << "caffemodel: " << modelBin << std::endl;
     std::cerr << "bvlc_googlenet.caffemodel can be downloaded here:" << std::endl;
     std::cerr << "http://dl.caffe.berkeleyvision.org/bvlc_googlenet.caffemodel" << std::endl;
     exit(-1);
 }
 std::cout << "Network loaded successfuly\n";
 cv::String imageFile = "Goose.bmp";
 //      cv::String imageFile = "space_shuttle.jpg";
 Mat img = imread(imageFile, IMREAD_UNCHANGED);
 int nChan = img.channels();
 cout << nChan;
 
nChan;

if (img.empty())
{
    std::cerr << "Can't read image from the file: " << imageFile << std::endl;
    exit(-1);
}
//GoogLeNet accepts only 224x224 RGB-images
Mat inputBlob = blobFromImage(img, 1, Size(300, 300), Scalar(104, 117, 123));   //Convert Mat to batch of images

net.setInput(inputBlob, "data");        //set the network input
cv::Mat prob = net.forward("detection_out");                          //compute output
int classId;
double classProb;
getMaxClass(prob, &classId, &classProb);//find the best class
std::vector<String> classNames = readClassNames();
std::cout << "Best class: #" << classId << " '" << classNames.at(classId) << "'" << std::endl;
std::cout << "Probability: " << classProb * 100 << "%" << std::endl;