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https://github.com/opencv/opencv_contrib.git
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155 lines
4.5 KiB
C++
155 lines
4.5 KiB
C++
#include <opencv2/dnn.hpp>
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#include <opencv2/imgproc.hpp>
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#include <opencv2/highgui.hpp>
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using namespace cv;
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using namespace cv::dnn;
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#include <fstream>
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#include <iostream>
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#include <cstdlib>
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using namespace std;
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//static void colorizeSegmentation(dnn::Blob& score,
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// const vector<cv::Vec3b>& colors,
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// cv::Mat& segm)
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//{
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// const int rows = score.rows();
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// const int cols = score.cols();
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// const int chns = score.channels();
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// cv::Mat maxCl(rows, cols, CV_8UC1);
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// cv::Mat maxVal(rows, cols, CV_32FC1);
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// for (int ch = 0; ch < chns; ch++)
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// {
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// for (int row = 0; row < rows; row++)
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// {
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// const float* ptrScore = score.ptrf(0, ch, row);
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// uchar* ptrMaxCl = maxCl.ptr<uchar>(row);
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// float* ptrMaxVal = maxVal.ptr<float>(row);
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// for (int col = 0; col < cols; col++)
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// {
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// if (ptrScore[col] > ptrMaxVal[col])
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// {
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// ptrMaxVal[col] = ptrScore[col];
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// ptrMaxCl[col] = ch;
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// }
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// }
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// }
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// }
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// segm.create(rows, cols, CV_8UC3);
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// for (int row = 0; row < rows; row++)
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// {
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// const uchar* ptrMaxCl = maxCl.ptr<uchar>(row);
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// cv::Vec3b* ptrSegm = segm.ptr<cv::Vec3b>(row);
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// for (int col = 0; col < cols; col++)
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// {
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// ptrSegm[col] = colors[ptrMaxCl[col]];
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// }
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// }
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//}
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const char* about = "This sample uses Single-Shot Detector to detect objects "
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"from camera\n"; // TODO: link
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const char* params
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= "{ help | help | false | print usage }"
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"{ proto | model prototxt file | | model configuration }"
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"{ model | caffemodel file | | model weights }";
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int main(int argc, char** argv)
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{
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cv::CommandLineParser parser(argc, argv, params);
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if (parser.get<bool>("help"))
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{
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std::cout << about << std::endl;
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parser.printMessage();
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return 0;
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}
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String modelConfiguration = parser.get<string>("proto");
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String modelBinary = parser.get<string>("model");
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//! [Create the importer of Caffe model]
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Ptr<dnn::Importer> importer;
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// Import Caffe SSD model
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try
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{
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importer = dnn::createCaffeImporter(modelConfiguration, modelBinary);
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}
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catch (const cv::Exception &err) //Importer can throw errors, we will catch them
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{
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cerr << err.msg << endl;
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}
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//! [Create the importer of Caffe model]
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if (!importer)
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{
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cerr << "Can't load network by using the following files: " << endl;
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cerr << "prototxt: " << modelConfiguration << endl;
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cerr << "caffemodel: " << modelBinary << endl;
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cerr << "Models can be downloaded here:" << endl;
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cerr << "https://github.com/weiliu89/caffe/tree/ssd#models" << endl;
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exit(-1);
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}
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//! [Initialize network]
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dnn::Net net;
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importer->populateNet(net);
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importer.release(); //We don't need importer anymore
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//! [Initialize network]
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VideoCapture camera;
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if (!camera.open(0))
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{
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cout << "Unable to open camera stream" << endl;
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return 0;
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}
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size_t i = 0;
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for (;; )
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{
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Mat frame;
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camera >> frame;
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if (frame.empty())
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break;
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//! [Prepare blob]
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resize(frame, frame, Size(300, 300)); //SSD accepts 300x300 RGB-images
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dnn::Blob inputBlob = dnn::Blob(frame); //Convert Mat to dnn::Blob image
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//! [Prepare blob]
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std::ostringstream stream;
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stream << "folder/" << i << ".jpg";
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imwrite(stream.str(), frame);
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//! [Set input blob]
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net.setBlob(".data", inputBlob); //set the network input
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//! [Set input blob]
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//! [Make forward pass]
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net.forward(); //compute output
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//! [Make forward pass]
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// //! [Gather output]
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// dnn::Blob detection = net.getBlob("detection_out");
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// // cv::Mat colorize;
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// // colorizeSegmentation(score, colors, colorize);
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// // cv::Mat show;
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// // cv::addWeighted(img, 0.4, colorize, 0.6, 0.0, show);
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// // cv::imshow("show", show);
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// // cv::waitKey(0);
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// // return 0;
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// imshow("frame", frame);
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// if (waitKey(1) == 27)
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// break; // stop capturing by pressing ESC
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}
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camera.release();
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} // main
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