124 lines
3.5 KiB
C++
124 lines
3.5 KiB
C++
// system includes
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#include <iostream>
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// library includes
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#include <opencv2/imgproc.hpp>
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#include <opencv2/features2d.hpp>
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#include <opencv2/imgproc/types_c.h>
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#include <opencv2/videoio.hpp>
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#include <opencv2/videoio/videoio_c.h>
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#define CVVISUAL_DEBUGMODE
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#include <opencv2/cvv/debug_mode.hpp>
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#include <opencv2/cvv/show_image.hpp>
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#include <opencv2/cvv/filter.hpp>
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#include <opencv2/cvv/dmatch.hpp>
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#include <opencv2/cvv/final_show.hpp>
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using namespace std;
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using namespace cv;
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template<class T> std::string toString(const T& p_arg)
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{
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std::stringstream ss;
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ss << p_arg;
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return ss.str();
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}
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int
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main(int argc, char** argv)
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{
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cv::Size* resolution = nullptr;
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// parser keys
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const char *keys =
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"{ help h usage ? | | show this message }"
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"{ width W | 0| camera resolution width. leave at 0 to use defaults }"
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"{ height H | 0| camera resolution height. leave at 0 to use defaults }";
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CommandLineParser parser(argc, argv, keys);
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if (parser.has("help")) {
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parser.printMessage();
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return 0;
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}
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int res_w = parser.get<int>("width");
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int res_h = parser.get<int>("height");
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// setup video capture
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cv::VideoCapture capture(0);
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if (!capture.isOpened()) {
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std::cout << "Could not open VideoCapture" << std::endl;
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return 1;
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}
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if (res_w>0 && res_h>0) {
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printf("Setting resolution to %dx%d\n", res_w, res_h);
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capture.set(CV_CAP_PROP_FRAME_WIDTH, res_w);
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capture.set(CV_CAP_PROP_FRAME_HEIGHT, res_h);
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}
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cv::Mat prevImgGray;
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std::vector<cv::KeyPoint> prevKeypoints;
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cv::Mat prevDescriptors;
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int maxFeatureCount = 500;
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Ptr<ORB> detector = ORB::create(maxFeatureCount);
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cv::BFMatcher matcher(cv::NORM_HAMMING);
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for (int imgId = 0; imgId < 10; imgId++) {
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// capture a frame
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cv::Mat imgRead;
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capture >> imgRead;
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printf("%d: image captured\n", imgId);
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std::string imgIdString{"imgRead"};
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imgIdString += toString(imgId);
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cvv::showImage(imgRead, CVVISUAL_LOCATION, imgIdString.c_str());
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// convert to grayscale
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cv::Mat imgGray;
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cv::cvtColor(imgRead, imgGray, COLOR_BGR2GRAY);
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cvv::debugFilter(imgRead, imgGray, CVVISUAL_LOCATION, "to gray");
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// detect ORB features
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std::vector<cv::KeyPoint> keypoints;
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cv::Mat descriptors;
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detector->detectAndCompute(imgGray, cv::noArray(), keypoints, descriptors);
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printf("%d: detected %zd keypoints\n", imgId, keypoints.size());
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// match them to previous image (if available)
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if (!prevImgGray.empty()) {
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std::vector<cv::DMatch> matches;
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matcher.match(prevDescriptors, descriptors, matches);
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printf("%d: all matches size=%zd\n", imgId, matches.size());
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std::string allMatchIdString{"all matches "};
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allMatchIdString += toString(imgId-1) + "<->" + toString(imgId);
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cvv::debugDMatch(prevImgGray, prevKeypoints, imgGray, keypoints, matches, CVVISUAL_LOCATION, allMatchIdString.c_str());
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// remove worst (as defined by match distance) bestRatio quantile
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double bestRatio = 0.8;
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std::sort(matches.begin(), matches.end());
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matches.resize(int(bestRatio * matches.size()));
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printf("%d: best matches size=%zd\n", imgId, matches.size());
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std::string bestMatchIdString{"best " + toString(bestRatio) + " matches "};
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bestMatchIdString += toString(imgId-1) + "<->" + toString(imgId);
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cvv::debugDMatch(prevImgGray, prevKeypoints, imgGray, keypoints, matches, CVVISUAL_LOCATION, bestMatchIdString.c_str());
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}
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prevImgGray = imgGray;
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prevKeypoints = keypoints;
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prevDescriptors = descriptors;
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}
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cvv::finalShow();
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return 0;
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}
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