C++优先机会例外

Question

我已经用c++写了一个形状检测代码。我正在使用Visual Studio 2013速成版桌面版。

当我运行程序时，它会给出以下错误。

Final.exe: 0xC0000005中0x54EE3C77 (opencv_imgproc244d.dll)处的第一次机会异常:访问冲突读取位置0x05958000。

如果存在针对此异常的处理程序，则程序可以安全地继续运行。

以下是代码示例。

#include "stdafx.h"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
#include <stdlib.h>
#include <thread>  
#include <cv.h>
#include <highgui.h>
#include <windows.h>




void shapeDetectionNew(IplImage* img)
{

try
{

    //converting the original image into grayscale
    IplImage* imgGrayScale = cvCreateImage(cvGetSize(img), 8, 1);
    cvCvtColor(img, imgGrayScale, CV_BGR2GRAY);

    //thresholding the grayscale image to get better results
    cvThreshold(imgGrayScale, imgGrayScale, 128, 255, CV_THRESH_BINARY);

    CvSeq* contour;  //hold the pointer to a contour
    CvSeq* result;   //hold sequence of points of a contour
    CvMemStorage *storage = cvCreateMemStorage(0); //storage area for all contours

    //finding all contours in the image
    cvFindContours(imgGrayScale, storage, &contour, sizeof(CvContour), CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, cvPoint(0, 0));

    //***********************************
    cv::Mat img = cv::imread("F:\\My Works\\Opencv\\Shape_Detection_Images\\shape.jpg");

    //convert IplImage to Mat
    //cv::Mat img(iplImg);

    cv::Mat gray;
    cv::cvtColor(img, gray, CV_BGR2GRAY);

    // Use Canny instead of threshold to catch squares with gradient shading
    cv::Mat bw;
    cv::Canny(gray, bw, 0, 50, 5);

    // Find contours
    std::vector<std::vector<cv::Point> > contours;
    cv::findContours(bw.clone(), contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);

    std::vector<cv::Point> approx;
    cv::Mat dst = img.clone();

    //***********************************

    for (int i = 0; i < contours.size(); i++)
    {
        // Approximate contour with accuracy proportional
        // to the contour perimeter
        cv::approxPolyDP(cv::Mat(contours[i]), approx, cv::arcLength(cv::Mat(contours[i]), true)*0.02, true);

        // Skip small or non-convex objects 
        if (std::fabs(cv::contourArea(contours[i])) < 100 || !cv::isContourConvex(approx))
            continue;

        if (approx.size() == 3)
        {
            setLabel(dst, "TRI", contours[i]);    // Triangles
        }
        else if (approx.size() >= 4 && approx.size() <= 6)
        {
            // Number of vertices of polygonal curve
            int vtc = approx.size();

            // Get the cosines of all corners
            std::vector<double> cos;
            for (int j = 2; j < vtc + 1; j++)
                cos.push_back(angle(approx[j%vtc], approx[j - 2], approx[j - 1]));

            // Sort ascending the cosine values
            std::sort(cos.begin(), cos.end());

            // Get the lowest and the highest cosine
            double mincos = cos.front();
            double maxcos = cos.back();

            // Use the degrees obtained above and the number of vertices
            // to determine the shape of the contour
            if (vtc == 4 && mincos >= -0.1 && maxcos <= 0.3)
                setLabel(dst, "RECT", contours[i]);
            else if (vtc == 5 && mincos >= -0.34 && maxcos <= -0.27)
                setLabel(dst, "PENTA", contours[i]);
            else if (vtc == 6 && mincos >= -0.55 && maxcos <= -0.45)
                setLabel(dst, "HEXA", contours[i]);
        }
        else
        {
            // Detect and label circles
            double area = cv::contourArea(contours[i]);
            cv::Rect r = cv::boundingRect(contours[i]);
            int radius = r.width / 2;

            if (std::abs(1 - ((double)r.width / r.height)) <= 0.2 &&
                std::abs(1 - (area / (CV_PI * std::pow((double)radius, 2)))) <= 0.2)
                setLabel(dst, "CIR", contours[i]);
        }
    }

    cv::imshow("Shape_Detection", dst);


}
catch (int e)
{
    throw e;
}
}

int main()
{
    try
    {

    // Create CvCapture object to grab data from the webcam
    CvCapture* pCapture;

    // Start capturing data from the webcam
    pCapture = cvCaptureFromCAM(1);

    // Define the IplImage pointers we're going to use as globals
    IplImage* pFrame;

    IplImage* pProcessedFrame;
    IplImage* tempFrame;
    pFrame = cvQueryFrame(pCapture);

    //Create the low threshold slider
    // Format: Slider name, window name, reference to variable for slider, max value of slider, callback function
    cvCreateTrackbar("Low Threshold", "Edge_Detection", &lowSliderPosition, maxLowThreshold, onLowThresholdSlide);

    // Create the high threshold slider
    cvCreateTrackbar("High Threshold", "Edge_Detection", &highSliderPosition, maxHighThreshold, onHighThresholdSlide);

    // Create a greyscale image which is the size of our captured image
    pProcessedFrame = cvCreateImage(cvSize(pFrame->width, pFrame->height), IPL_DEPTH_8U, 1);

    // Create a frame to use as our temporary copy of the current frame but in grayscale mode
    tempFrame = cvCreateImage(cvSize(pFrame->width, pFrame->height), IPL_DEPTH_8U, 1);

    char keypress;
    bool quit = false;
    int counterCheck = 1;

    while (quit == false)
    {


        // Make an image from the raw capture data
        // Note: cvQueryFrame is a combination of cvGrabFrame and cvRetrieveFrame
        pFrame = cvQueryFrame(pCapture);

        // Draw the original frame in our window
        cvShowImage("Live_Cam", pFrame);




        shapeDetectionNew(pFrame);



    } // End of while loop

    cvDestroyAllWindows();

}
catch (Exception ex)
{

}

return 1;
}

Answer 1

您不是在检查

 pFrame = cvQueryFrame(pCapture);

不为空。如果是，最终会将其传递给cvCvtColor()，从而引发异常。

完全不同的问题:如果不随后调用waitKey()，imshow()将不会显示任何内容