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#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/dnn.hpp>
#include <iostream>
#include <cstdlib>
int main(int argc, char **argv)
{
if (argc < 4)
{
std::cerr << "Usage " << argv[0] << ": "
<< "<model-definition-file> " << " "
<< "<model-weights-file> " << " "
<< "<test-image>\n";
return -1;
}
cv::String model_prototxt = argv[1];
cv::String model_binary = argv[2];
cv::String test_image = argv[3];
cv::dnn::Net net = cv::dnn::readNetFromCaffe(model_prototxt, model_binary);
if (net.empty())
{
std::cerr << "Couldn't load the model !\n";
return -2;
}
cv::Mat img = cv::imread(test_image);
if (img.empty())
{
std::cerr << "Couldn't load image: " << test_image << "\n";
return -3;
}
cv::Mat input_blob = cv::dnn::blobFromImage(
img, 1.0, cv::Size(416, 416), cv::Scalar(104, 117, 123), false);
cv::Mat prob;
cv::TickMeter t;
net.setInput(input_blob);
t.start();
prob = net.forward("predictions");
t.stop();
int prob_size[3] = {1000, 1, 1};
cv::Mat prob_data(3, prob_size, CV_32F, prob.ptr<float>(0));
double max_prob = -1.0;
int class_idx = -1;
for (int idx = 0; idx < prob.size[1]; ++idx)
{
double current_prob = prob_data.at<float>(idx, 0, 0);
if (current_prob > max_prob)
{
max_prob = current_prob;
class_idx = idx;
}
}
std::cout << "Best class Index: " << class_idx << "\n";
std::cout << "Time taken: " << t.getTimeSec() << "\n";
std::cout << "Probability: " << max_prob * 100.0<< "\n";
return 0;
}
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