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