我的跟踪栏有什么问题

What is wrong with my trackbar?

本文关键字：什么 问题 跟踪 我的      更新时间：2023-10-16

我已经使用OpenCV构建了一个成功的边缘检测程序，该程序使用我的Macbook的相机，并具有根据原始图像中的不同通道打印各种边缘的选项，但是当我添加跟踪栏以允许更改Canny的容差时，它既没有响应，又导致我的按键速度变慢。

我

怀疑我使用了这个错误，因为我的代码中的类似错误导致了同样的延迟，但我不确定这里出了什么问题。知道为什么我的跟踪栏没有响应吗？

#include "opencv2/core/core.hpp"
#include "opencv2/flann/miniflann.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/photo/photo.hpp"
#include "opencv2/video/video.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/ml/ml.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/core/core_c.h"
#include "opencv2/highgui/highgui_c.h"
#include "opencv2/imgproc/imgproc_c.h"
#include <cstdlib>
using namespace cv; 
using namespace std;
int showKind = 0;
int waitCount = 1; // wait for this many milliseconds to check for input
Mat channel(Mat A, int ich); // return the image with only this channel non-zero
Mat BW(Mat A); // return the black and white versin of this image
void myWaitKey();
Mat Blur(Mat A, int kernSize);
Mat Edges(Mat A, double tol1, double tol2);
int tol1 = 25; 
int tol2 = 75; 
int tol2Max = 250;
/// trackbar
void on_trackbar(int, void*) {
    cout << "tol2 = " << tol2 << endl;
}
int main() {
    VideoCapture stream1(0);
    namedWindow("cam", CV_WINDOW_NORMAL);
    if( !stream1.isOpened() ) { 
        cout << "Cannot open camera!" << endl;
    }   
    string trackBarName = "tol2";
    createTrackbar( trackBarName.c_str(), "cam",  &tol2, tol2Max, on_trackbar);
    on_trackbar( tol2, 0); 
    Mat cameraFrame; // showKind = 0
    Mat grey; // showkind = 4
    while( true ) { 
        /// read the cameraFrame
        stream1.read(cameraFrame);
        /// show the cameraFrame
        if( showKind == 0 ) imshow("cam", cameraFrame);
        else if( showKind > 0 && showKind < 4 ) imshow("cam", channel(cameraFrame, showKind));
        else if( showKind == 4 ) imshow("cam", BW(cameraFrame) );
        else if( showKind == 5 ) imshow("cam", Edges(channel(cameraFrame,1), tol1, tol2));
        else if( showKind == 6 ) imshow("cam", Edges(channel(cameraFrame,2), tol1, tol2));
        else if( showKind == 7 ) imshow("cam", Edges(channel(cameraFrame,3), tol1, tol2));
        else if( showKind == 8 ) imshow("cam", Edges(cameraFrame, 25, 75));
        else {
            cout << "ERROR: Unknown showKind = " << showKind << endl;
        }

        myWaitKey();
    }

    return 0;
}
Mat channel(Mat A, int ich) {
    Mat Channel[3];
    Mat B;
    split(A, Channel);
    for(int i = 0; i < 3; i++) {
        if( ich-1 != i ) Channel[i].setTo(0);
    }
    merge(Channel, 3, B);
    return B;
}
Mat BW(Mat A) {
    Mat B;
    cvtColor( A, B, CV_BGR2GRAY );
    return B;
}
void myWaitKey() {
    int key = waitKey(waitCount);
    if( key == 27 ) {
        cout << "ESC pressed ... exiting" << endl;
        exit(EXIT_SUCCESS);
    }
    // convert showKind
    else if( key == 48 ){ showKind = 0; }
    else if( key == 49 ){ showKind = 1; }
    else if( key == 50 ){ showKind = 2; }
    else if( key == 51 ){ showKind = 3; }
    else if( key == 52 ){ showKind = 4; }
    else if( key == 53 ){ showKind = 5; }
    else if( key == 54 ){ showKind = 6; }
    else if( key == 55 ){ showKind = 7; }
    else if( key == 56 ){ showKind = 8; }
}
Mat Blur(Mat A, int kernSize) {
    //Mat G = BW(A);
    Mat C;
    // C is now black and white
    blur(A, C, Size(kernSize,kernSize));
    return C;
}
Mat Edges(Mat A, double tol1, double tol2) {
    Mat G = BW(Blur(A,4));
    Mat E;
    Canny(G, E, tol1, tol2);
    A.copyTo(G, E);
    return G;
}

看起来像Mac OS X上跟踪栏实现的问题。

也许这个答案会有所帮助：OSX 中的 OpenCV 跟踪条性能

  • 请参阅下面的示例代码。我已经编写了这个演示代码。希望这对您有所帮助。

    #include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <stdlib.h>
#include <stdio.h>
using namespace cv;
/// Global variables
Mat src, src_gray;
Mat dst, detected_edges;
int edgeThresh = 1;
int lowThreshold;
int const max_lowThreshold = 100;
int ratio = 3;
int kernel_size = 3;
char* window_name = "Edge Map";
void CannyThreshold(int, void*)
{
   /// Reduce noise with a kernel 3x3
   blur( src_gray, detected_edges, Size(3,3) );
   /// Canny detector
   Canny( detected_edges, detected_edges, lowThreshold, lowThreshold*ratio, kernel_size );
   /// Using Canny's output as a mask, we display our result
   dst = Scalar::all(0);
   src.copyTo( dst, detected_edges);
   imshow( window_name, dst );
}
int main( int argc, char** argv )
{
   /// Load an image
   src = imread( argv[1] );
   if( !src.data )
   { return -1; }
   dst.create( src.size(), src.type() );
  cvtColor( src, src_gray, CV_BGR2GRAY );
  namedWindow( window_name, CV_WINDOW_AUTOSIZE );
  createTrackbar( "Min Threshold:", window_name, &lowThreshold, max_lowThreshold, CannyThreshold );
  CannyThreshold(0, 0);
  waitKey(0);
  return 0;
}
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