Question

我制作opencv程序，我在搜索中找到了这个这个程序让我找到了矩形的面孔

但我有一个错误这是向量下标超出范围的错误消息我怎样才能解决问题？

#include <stdio.h>
#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/core/core.hpp>
#include <opencv2/contrib/contrib.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/objdetect/objdetect.hpp>
#include <vector>

using namespace cv;
using namespace std;


int main()
{

VideoCapture cap(0); // open the default camera
if(!cap.isOpened())  // check if we succeeded
    return -1;

vector<Mat> images;
vector<int> labels;

// Get the height from the first image. We'll need this
// later in code to reshape the images to their original
// size AND we need to reshape incoming faces to this size:
int im_width = images[0].cols;
int im_height = images[0].rows;
// Create a FaceRecognizer and train it on the given images:
Ptr<FaceRecognizer> model = createFisherFaceRecognizer();
model->train(images, labels);
// That's it for learning the Face Recognition model. You now
// need to create the classifier for the task of Face Detection.
// We are going to use the haar cascade you have specified in the
// command line arguments:
//

CascadeClassifier faceCascade;
faceCascade.load("C:\\opencv\\data\\haarcascade\\haarcascade_frontalface_alt.xml");




Mat image;


namedWindow("edges",1);

for(;;){
    cap >> image; // get a new frame from camera
    Mat original = image.clone();
    Mat frame_gray;
    cvtColor(original, frame_gray, CV_BGR2GRAY);

   // equalizeHist( frame_gray, frame_gray );
   /* GaussianBlur(edges, edges, Size(7,7), 1.5, 1.5);
    Canny(edges, edges, 0, 30, 3);*/

  //DITECT FACE
  // Find the faces in the frame:
    vector< Rect_<int> > faces;
    faceCascade.detectMultiScale(frame_gray, faces);
    // At this point you have the position of the faces in
    // faces. Now we'll get the faces, make a prediction and
    // annotate it in the video. Cool or what?

    for(int i = 0; i < faces.size(); i++) {

    Rect face_i = faces[i];

    //rectangle(image, aRect, CV_RGB(0, 255,0), 1);
    Mat face = frame_gray(face_i);
        // Resizing the face is necessary for Eigenfaces and Fisherfaces. You can easily
        // verify this, by reading through the face recognition tutorial coming with OpenCV.
        // Resizing IS NOT NEEDED for Local Binary Patterns Histograms, so preparing the
        // input data really depends on the algorithm used.
        //
        // I strongly encourage you to play around with the algorithms. See which work best
        // in your scenario, LBPH should always be a contender for robust face recognition.
        //
        // Since I am showing the Fisherfaces algorithm here, I also show how to resize the
        // face you have just found:
        Mat face_resized;
        cv::resize(face, face_resized, Size(im_width, im_height), 1.0, 1.0, INTER_CUBIC);
        // Now perform the prediction, see how easy that is:
        int prediction = model->predict(face_resized);
        // And finally write all we've found out to the original image!
        // First of all draw a green rectangle around the detected face:
        rectangle(original, face_i, CV_RGB(0, 255,0), 1);
        // Create the text we will annotate the box with:
        string box_text = format("Prediction = %d", prediction);
        // Calculate the position for annotated text (make sure we don't
        // put illegal values in there):

        int pos_x = std::max(face_i.tl().x - 10, 0);
        int pos_y = std::max(face_i.tl().y - 10, 0);
        // And now put it into the image:
        putText(original, box_text, Point(pos_x, pos_y), FONT_HERSHEY_PLAIN, 1.0, CV_RGB(0,255,0), 2.0);
   }


    faceCascade.detectMultiScale( frame_gray, faces, 1.1, 3, 0|CV_HAAR_SCALE_IMAGE, Size(30, 30) );


    imshow("frame_gray", frame_gray);

  if(waitKey(1000) >= 0) 
      break;
}
return 0;

}

Answer 1

images 变量为空，因此访问0将具有未定义的行为。这应该被纠正，首先你需要将数据添加到您的图像变量，然后您可以访问它。

vector<Mat> images;
int im_width = images[0].cols;
int im_height = images[0].rows;

这可能会导致某些实现上出现超出范围的错误消息。但是，如果我们从 at

访问无效索引，标准 std::vector 方法会保证此类例外

修改 Herb Shutter在他的Gotw系列中写了很好的文章。

http://www.gotw.ca/gotw/074.htm

Answer 2

向量为空，因为您将它们定义为

vector<Mat> images;
vector<int> labels;

并没有向他们添加元素。

但是，您试图访问向量中尚不存在的向量的第一个元素。

// Get the height from the first image. We'll need this
// later in code to reshape the images to their original
// size AND we need to reshape incoming faces to this size:
int im_width = images[0].cols;
int im_height = images[0].rows;

向量下标超出范围错误message3

2 个答案: