OpenCVを使用したビデオの顔認識は未処理の例外を返します

Question

OpenCVで提供されるビデオサンプルで顔認識を使用しようとしています。私が行った変更は、コマンドライン引数を使用してCSVおよびカスケードのクラシファイアパスを提供するのではなく、コード内で直接指定しました。これはコードです：

#include "stdafx.h" 
#include "opencv2/core/core.hpp" 
#include "opencv2/contrib/contrib.hpp" 
#include "opencv2/highgui/highgui.hpp" 
#include "opencv2/imgproc/imgproc.hpp" 
#include "opencv2/objdetect/objdetect.hpp" 

#include <iostream> 
#include <fstream> 
#include <sstream> 

using namespace cv; 
using namespace std; 

static void read_csv(const string& filename, vector<Mat>& images, vector<int>& labels, char separator = ';') { 
    std::ifstream file(filename.c_str(), ifstream::in); 
    if (!file) { 
     string error_message = "No valid input file was given, please check the given filename."; 
     CV_Error(CV_StsBadArg, error_message); 
    } 
    string line, path, classlabel; 
    while (getline(file, line)) { 
     stringstream liness(line); 
     getline(liness, path, separator); 
     getline(liness, classlabel); 
     if(!path.empty() && !classlabel.empty()) { 
      images.push_back(imread(path, 0)); 
      labels.push_back(atoi(classlabel.c_str())); 
     } 
    } 
} 

int main(int argc, const char *argv[]) { 
// Check for valid command line arguments, print usage 
// if no arguments were given. 
if (argc != 4) { 
    cout << "usage: " << argv[0] << " </path/to/haar_cascade> </path/to/csv.ext> </path/to/device id>" << endl; 
    cout << "\t </path/to/haar_cascade> -- Path to the Haar Cascade for face detection." << endl; 
    cout << "\t </path/to/csv.ext> -- Path to the CSV file with the face database." << endl; 
    cout << "\t <device id> -- The webcam device id to grab frames from." << endl; 
    //exit(1); 
} 
// Get the path to your CSV: 
string fn_haar = "C:\\OpenCV-2.4.2\\opencv\\data\\haarcascades\\haarcascade_frontalface_default.xml"; 
string fn_csv = "C:\\Users\\gaspl\\Desktop\\train.txt"; 
int deviceId = 1; 
// These vectors hold the images and corresponding labels: 
vector<Mat> images; 
vector<int> labels; 
// Read in the data (fails if no valid input filename is given, but you'll get an error message): 
try { 
    read_csv(fn_csv, images, labels); 
} catch (cv::Exception& e) { 
    cerr << "Error opening file \"" << fn_csv << "\". Reason: " << e.msg << endl; 
    // nothing more we can do 
    exit(1); 
} 
// 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 haar_cascade; 
haar_cascade.load(fn_haar); 
// Get a handle to the Video device: 
VideoCapture cap(deviceId); 
// Check if we can use this device at all: 
if(!cap.isOpened()) { 
    cerr << "Capture Device ID " << deviceId << "cannot be opened." << endl; 
    return -1; 
} 
// Holds the current frame from the Video device: 
Mat frame; 
for(;;) { 
    cap >> frame; 
    // Clone the current frame: 
    Mat original = frame.clone(); 
    // Convert the current frame to grayscale: 
    Mat gray; 
    cvtColor(original, gray, CV_BGR2GRAY); 
    // Find the faces in the frame: 
    vector< Rect_<int> > faces; 
    haar_cascade.detectMultiScale(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++) { 
     // Process face by face: 
     Rect face_i = faces[i]; 
     // Crop the face from the image. So simple with OpenCV C++: 
     Mat face = 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); 
    } 
    // Show the result: 
    imshow("face_recognizer", original); 
    // And display it: 
    char key = (char) waitKey(20); 
    // Exit this loop on escape: 
    if(key == 27) 
     break; 
    } 
    return 0; 
} 

は、これは私のtrain.txt CSVファイルには、次のようになります。私は（それがうまくビルド）サンプルを実行しようとすると、

C:\\Training\\extract0.jpg;0 
C:\\Training\\extract1.jpg;0 
C:\\Training\\extract2.jpg;0 

しかし、私はこれらのエラーを取得し、それを尋ねます私Breakへ：

First-chance exception at 0x000007FEFE04CAED in facrec.exe: Microsoft C++ exception: cv::Exception at memory location 0x000000000025C530. 
Unhandled exception at at 0x000007FEFE04CAED in facrec.exe: Microsoft C++ exception: cv::Exception at memory location 0x000000000025C530. 

エラーが、私はフィッシャー認識器を初期化する時点で発生：

01私はすでに顔検出と顔抽出を試みたが、彼らは自分のコンピュータ上で正常に動作し

：私は、Visual Studio 2012とOpenCVの2.4.2（x64の-リリースコンフィギュレーションを構築する）とWindows 7の64ビット版を使用しています

Ptr<FaceRecognizer> model = createFisherFaceRecognizer(); 
model->train(images, labels); 

（If anyone wants to check out the code）、私のVisualスタジオのプロジェクト設定（リンカまたはC/C++）には問題はないようです。

There is a similar question hereしかし、まだ何も解決しません。

私は何をしていますか？

Answer 1

すでに郵送で結論しています。唯一のラベルがあなたのCSVファイルで指定されたので、これは、起こる：

 
C:\Training\extract0.jpg;0 
C:\Training\extract1.jpg;0 
C:\Training\extract2.jpg;0 

Fisherfaces方法は、モデルを学習するために、少なくとも2つのクラスを必要とします。このケースは、キャッチされている必要があり、OpenCVの2.4.2は、私のシステム上で次の例外がスローされます：

トレーニングデータに誤りがかなり明確になり

 
OpenCV Error: Bad argument (At least two classes are needed to perform a LDA. Reason: Only one class was given!) in lda, file /home/philipp/github/libfacerec/src/subspace.cpp, line 150 
terminate called after throwing an instance of 'cv::Exception' 
    what(): /home/philipp/github/libfacerec/src/subspace.cpp:150: error: (-5) At least two classes are needed to perform a LDA. Reason: Only one class was given! in function lda 

。あなたのWindows 7インストールでこの例外がスローされない理由はわかりませんが、私はできるだけ早く再現してそれに応じて修正するテストシステムをセットアップします。