Question

我试图在 macOS Sierria 版本10.12.5下使用OpenCV3.0示例c ++代码运行面部检测。但是，我没有加载＆＃34; .xml＆＃34;文件。我尝试使用相对路径以及＆＃34; haarcascade_frontalface_alt.xml＆＃34; 和＆＃34; haarcascade_eye_tree_eyeglasses.xml＆＃34; 运行它的绝对路径，但是它并没有为我解决问题。我成功编译了代码，但收到了错误消息：

--(!)Error loading face cascade

我认为 CascadeClassifier 的加载方法存在一些问题。我读了一些线程。但没有人给出解决这个问题的具体指示。我求求解决这个问题的具体指示。非常感谢你们！

以下是示例代码：

#include "opencv2/objdetect.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"

#include <iostream>
#include <stdio.h>

using namespace std;
using namespace cv;

/** Function Headers */
void detectAndDisplay( Mat frame );

/** Global variables */
String face_cascade_name = "/my/path/to/haarcascade_frontalface_alt.xml";
String eyes_cascade_name = "/my/path/to/haarcascade_eye_tree_eyeglasses.xml";
CascadeClassifier face_cascade;
CascadeClassifier eyes_cascade;
String window_name = "Capture - Face detection";

/** @function main */
int main( int argc, const char** argv )
{
    // CommandLineParser parser(argc, argv,
    //     "{help h||}"
    //     "{face_cascade|../../data/haarcascades/haarcascade_frontalface_alt.xml|}"
    //     "{eyes_cascade|../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml|}");

    // cout << "\nThis program demonstrates using the cv::CascadeClassifier class to detect objects (Face + eyes) in a video stream.\n"
    //         "You can use Haar or LBP features.\n\n";
    // parser.printMessage();

    // face_cascade_name = parser.get<string>("face_cascade");
    // eyes_cascade_name = parser.get<string>("eyes_cascade");
    VideoCapture capture;
    Mat frame;

    //-- 1. Load the cascades
    if( !face_cascade.load( face_cascade_name ) ){ printf("--(!)Error loading face cascade\n"); return -1; };
    if( !eyes_cascade.load( eyes_cascade_name ) ){ printf("--(!)Error loading eyes cascade\n"); return -1; };

    //-- 2. Read the video stream
    capture.open( 0 );
    if ( ! capture.isOpened() ) { printf("--(!)Error opening video capture\n"); return -1; }

    while ( capture.read(frame) )
    {
        if( frame.empty() )
        {
            printf(" --(!) No captured frame -- Break!");
            break;
        }

        //-- 3. Apply the classifier to the frame
        detectAndDisplay( frame );

        char c = (char)waitKey(10);
        if( c == 27 ) { break; } // escape
    }
    return 0;
}

/** @function detectAndDisplay */
void detectAndDisplay( Mat frame )
{
    std::vector<Rect> faces;
    Mat frame_gray;

    cvtColor( frame, frame_gray, COLOR_BGR2GRAY );
    equalizeHist( frame_gray, frame_gray );

    //-- Detect faces
    face_cascade.detectMultiScale( frame_gray, faces, 1.1, 2, 0|CASCADE_SCALE_IMAGE, Size(30, 30) );

    for ( size_t i = 0; i < faces.size(); i++ )
    {
        Point center( faces[i].x + faces[i].width/2, faces[i].y + faces[i].height/2 );
        ellipse( frame, center, Size( faces[i].width/2, faces[i].height/2 ), 0, 0, 360, Scalar( 255, 0, 255 ), 4, 8, 0 );

        Mat faceROI = frame_gray( faces[i] );
        std::vector<Rect> eyes;

        //-- In each face, detect eyes
        eyes_cascade.detectMultiScale( faceROI, eyes, 1.1, 2, 0 |CASCADE_SCALE_IMAGE, Size(30, 30) );

        for ( size_t j = 0; j < eyes.size(); j++ )
        {
            Point eye_center( faces[i].x + eyes[j].x + eyes[j].width/2, faces[i].y + eyes[j].y + eyes[j].height/2 );
            int radius = cvRound( (eyes[j].width + eyes[j].height)*0.25 );
            circle( frame, eye_center, radius, Scalar( 255, 0, 0 ), 4, 8, 0 );
        }
    }
    //-- Show what you got
    imshow( window_name, frame );
}

尝试运行OpenCv objectDetection

0 个答案: