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我正在使用opencv网站的detect_markers.cpp使用相机检测标记的姿势。编译后没有错误我得到了这个，所以我如何输入参数？ http://docs.opencv.org/3.1.0/d5/dae/tutorial_aruco_detection.html关于在opencv aruco中使用detect_markers.cpp的问题？
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#include <opencv2/highgui.hpp>
#include <opencv2/aruco.hpp>
#include <iostream>
#include <opencv/cv.h>
#include <opencv/cvaux.h>
#include <opencv/highgui.h>
using namespace std;
using namespace cv;
namespace {
const char* about = "Basic marker detection";
const char* keys =
"{d | | dictionary: DICT_4X4_50=0, DICT_4X4_100=1, DICT_4X4_250=2,"
"DICT_4X4_1000=3, DICT_5X5_50=4, DICT_5X5_100=5, DICT_5X5_250=6, DICT_5X5_1000=7, "
"DICT_6X6_50=8, DICT_6X6_100=9, DICT_6X6_250=10, DICT_6X6_1000=11, DICT_7X7_50=12,"
"DICT_7X7_100=13, DICT_7X7_250=14, DICT_7X7_1000=15, DICT_ARUCO_ORIGINAL = 16}"
"{v | | Input from video file, if ommited, input comes from camera }"
"{ci | 0 | Camera id if input doesnt come from video (-v) }"
"{c | | Camera intrinsic parameters. Needed for camera pose }"
"{l | 0.1 | Marker side lenght (in meters). Needed for correct scale in camera pose }"
"{dp | | File of marker detector parameters }"
"{r | | show rejected candidates too }";
}
/**
*/
static bool readCameraParameters(string filename, Mat &camMatrix, Mat &distCoeffs) {
FileStorage fs(filename, FileStorage::READ);
if(!fs.isOpened())
return false;
fs["camera_matrix"] >> camMatrix;
fs["distortion_coefficients"] >> distCoeffs;
return true;
}
/**
*/
static bool readDetectorParameters(string filename, Ptr<aruco::DetectorParameters> ¶ms) {
FileStorage fs(filename, FileStorage::READ);
if(!fs.isOpened())
return false;
fs["adaptiveThreshWinSizeMin"] >> params->adaptiveThreshWinSizeMin;
fs["adaptiveThreshWinSizeMax"] >> params->adaptiveThreshWinSizeMax;
fs["adaptiveThreshWinSizeStep"] >> params->adaptiveThreshWinSizeStep;
fs["adaptiveThreshConstant"] >> params->adaptiveThreshConstant;
fs["minMarkerPerimeterRate"] >> params->minMarkerPerimeterRate;
fs["maxMarkerPerimeterRate"] >> params->maxMarkerPerimeterRate;
fs["polygonalApproxAccuracyRate"] >> params->polygonalApproxAccuracyRate;
fs["minCornerDistanceRate"] >> params->minCornerDistanceRate;
fs["minDistanceToBorder"] >> params->minDistanceToBorder;
fs["minMarkerDistanceRate"] >> params->minMarkerDistanceRate;
fs["doCornerRefinement"] >> params->doCornerRefinement;
fs["cornerRefinementWinSize"] >> params->cornerRefinementWinSize;
fs["cornerRefinementMaxIterations"] >> params->cornerRefinementMaxIterations;
fs["cornerRefinementMinAccuracy"] >> params->cornerRefinementMinAccuracy;
fs["markerBorderBits"] >> params->markerBorderBits;
fs["perspectiveRemovePixelPerCell"] >> params->perspectiveRemovePixelPerCell;
fs["perspectiveRemoveIgnoredMarginPerCell"] >> params->perspectiveRemoveIgnoredMarginPerCell;
fs["maxErroneousBitsInBorderRate"] >> params->maxErroneousBitsInBorderRate;
fs["minOtsuStdDev"] >> params->minOtsuStdDev;
fs["errorCorrectionRate"] >> params->errorCorrectionRate;
return true;
}
/**
*/
int main(int argc, char *argv[]) {
CommandLineParser parser(argc, argv, keys);
parser.about(about);
if(argc < 2) {
parser.printMessage();
return 0;
}
int dictionaryId = parser.get<int>("d");
bool showRejected = parser.has("r");
bool estimatePose = parser.has("c");
float markerLength = parser.get<float>("l");
Ptr<aruco::DetectorParameters> detectorParams = aruco::DetectorParameters::create();
if(parser.has("dp")) {
bool readOk = readDetectorParameters(parser.get<string>("dp"), detectorParams);
if(!readOk) {
cerr << "Invalid detector parameters file" << endl;
return 0;
}
}
detectorParams->doCornerRefinement = true; // do corner refinement in markers
int camId = parser.get<int>("ci");
String video;
if(parser.has("v")) {
video = parser.get<String>("v");
}
if(!parser.check()) {
parser.printErrors();
return 0;
}
Ptr<aruco::Dictionary> dictionary =
aruco::getPredefinedDictionary(aruco::PREDEFINED_DICTIONARY_NAME(dictionaryId));
Mat camMatrix, distCoeffs;
if(estimatePose) {
bool readOk = readCameraParameters(parser.get<string>("c"), camMatrix, distCoeffs);
if(!readOk) {
cerr << "Invalid camera file" << endl;
return 0;
}
}
VideoCapture inputVideo;
int waitTime;
if(!video.empty()) {
inputVideo.open(video);
waitTime = 0;
} else {
inputVideo.open(camId);
waitTime = 10;
}
double totalTime = 0;
int totalIterations = 0;
while(inputVideo.grab()) {
Mat image, imageCopy;
inputVideo.retrieve(image);
double tick = (double)getTickCount();
vector<int> ids;
vector< vector<Point2f> > corners, rejected;
vector<Vec3d> rvecs, tvecs;
// detect markers and estimate pose
aruco::detectMarkers(image, dictionary, corners, ids, detectorParams, rejected);
if(estimatePose && ids.size() > 0)
aruco::estimatePoseSingleMarkers(corners, markerLength, camMatrix, distCoeffs, rvecs,
tvecs);
double currentTime = ((double)getTickCount() - tick)/getTickFrequency();
totalTime += currentTime;
totalIterations++;
if(totalIterations % 30 == 0) {
cout << "Detection Time = " << currentTime * 1000 << " ms "
<< "(Mean = " << 1000 * totalTime/double(totalIterations) << " ms)" << endl;
}
// draw results
image.copyTo(imageCopy);
if(ids.size() > 0) {
aruco::drawDetectedMarkers(imageCopy, corners, ids);
if(estimatePose) {
for(unsigned int i = 0; i < ids.size(); i++)
aruco::drawAxis(imageCopy, camMatrix, distCoeffs, rvecs[i], tvecs[i],
markerLength * 0.5f);
}
}
if(showRejected && rejected.size() > 0)
aruco::drawDetectedMarkers(imageCopy, rejected, noArray(), Scalar(100, 0, 255));
imshow("out", imageCopy);
char key = (char)waitKey(waitTime);
if(key == 27) break;
}
return 0;
}
这是我得到的消息： 基本标记检测 用法：detecttest [PARAMS]
-c
Camera intrinsic parameters. Needed for camera pose
--ci (value:0)
Camera id if input doesnt come from video (-v)
-d
dictionary: DICT_4X4_50=0, DICT_4X4_100=1, DICT_4X4_250=2,DICT_4X4_1000=3, DICT_5X5_50=4, DICT_5X5_100=5, DICT_5X5_250=6, DICT_5X5_1000=7, DICT_6X6_50=8, DICT_6X6_100=9, DICT_6X6_250=10, DICT_6X6_1000=11, DICT_7X7_50=12,DICT_7X7_100=13, DICT_7X7_250=14, DICT_7X7_1000=15, DICT_ARUCO_ORIGINAL = 16
--dp
File of marker detector parameters
-l (value:0.1)
Marker side lenght (in meters). Needed for correct scale in camera pose
-r
show rejected candidates too
-v
Input from video file, if ommited, input comes from camera