opencv的未處理異常contour.exe

Question

我在OpenCV的代碼工作得很好，直到當我想找到輪廓：

findContours(src, contours,hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE); 

然後我不斷收到以下錯誤：

"Unhandled exception at 0x773e3e28 in Contour.exe: Microsoft C++ exception: cv::Exception at memory location 0x002ff3ac.."

你對這個錯誤有什麼想法嗎？

我的完整代碼如下。

感謝

Mat src=Mat(100,200,CV_64F),newimg; 
vector<vector<Point>> contours; 
vector<Vec4i> hierarchy; 

for (int i=25;i<80;i++) 
    for(int j=25;j<80;j++) 
     src.at<double>(i,j)=1; 
imshow("img",src); 
waitKey(0); 

findContours(src, contours,hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE); 

Answer 1

來自OpenCV的文件引述有關findContours

image – Source, an 8-bit single-channel image. Non-zero pixels are treated as 1’s. Zero pixels remain 0’s, so the image is treated as binary . You can use compare() , inRange() , threshold() , adaptiveThreshold() , Canny() , and others to create a binary image out of a grayscale or color one. The function modifies the image while extracting the contours. If mode equals to CV_RETR_CCOMP or CV_RETR_FLOODFILL, the input can also be a 32-bit integer image of labels (CV_32SC1).

你可以調整你的代碼，你CV_64FC1圖像轉換爲CV_8UC1，如：

... 
Mat1b img8u; 
src.convertTo(img8u, CV_8U); 

vector<vector<Point>> contours; 
vector<Vec4i> hierarchy; 

findContours(img8u, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE); 
... 

---

另外，從評論中可以看出，您使用的是Visual Studio 2010，但將使用msvc11（Visual Studio 2012）構建的OpenCV鏈接起來。

您需要使用Visual Studio 2012或使用msvc10（Visual Studio 2010）重新編譯OpenCV。如果您決定升級VS，則可以直接轉到VS2013（並鏈接到vc12）或VS2015（但您需要重新編譯OpenCV）。

Answer 2

你的問題是當你需要一個CV_8UC1圖像時，你會給「findContours」一個CV_64F圖像。您通常會將findContours傳遞給邊緣檢測器的輸出。 （E.G. Canny）。

如果將代碼修改爲以下代碼，可以通過Canny進行過濾後在圖像中找到輪廓。

Mat src=Mat(100,200,CV_64F),newimg; 
Mat tCannyMat; 
vector<vector<Point>> contours; 
vector<Vec4i> hierarchy; 

for (int i=25;i<80;i++) 
    for(int j=25;j<80;j++) 
     src.at<double>(i,j)=1; 
imshow("img",src); 
waitKey(0); 

int lowThreshold = 0x3f;//This is the single value threshold 
int ratio = 3;//This is the ratio to apply for the entire pixel 
int kernel_size = 3;//This is the canny kernel size 

//You can use your own edge detector/a different one here if you wish. 
//Canny merely serves to give a working example. 
cv::Canny(src, tCannyMat, lowThreshold, lowThreshold*ratio, kernel_size); 

findContours(tCannyMat, contours,hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE);