ошибка предсказания распознавания лиц в opencv

Я наткнулся на исключение в моем заявлении, от которого я не могу избавиться …

Я пытаюсь написать простую программу распознавания лиц со всеми тремя алгоритмами распознавания лиц (Eigen, Fisher и LBPH).

Необработанное исключение вызывается строкой:

Fisher_prediction = Fisher_model->predict(crop);

и сообщение об ошибке говорит: Unhandled exception at at 0x000007FEFDB3A49D in FaceRecognition.exe: Microsoft C++ exception: cv::Exception at memory location 0x00000000002782B0.

и вызвано: msvcr110d.dll!_CxxThrowException(void * pExceptionObject, const _s__ThrowInfo * pThrowInfo) Line 152 C++

Любые предложения, где я иду не так?

вот остальная часть кода:

Mat frame = imread("1.jpg");

// Apply the classifier to the frame
if (!frame.empty()) {

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));

// Set Region of Interest
cv::Rect roi_b;
cv::Rect roi_c;

size_t ic = 0; // ic is index of current element
int ac = 0; // ac is area of current element

size_t ib = 0; // ib is index of biggest element
int ab = 0; // ab is area of biggest element

// Iterate through all current elements (detected faces)
for (ic = 0; ic < faces.size(); ic++) {

roi_c.x = faces[ic].x;
roi_c.y = faces[ic].y;
roi_c.width = (faces[ic].width);
roi_c.height = (faces[ic].height);

ac = roi_c.width * roi_c.height; // Get the area of current element (detected face)

roi_b.x = faces[ib].x;
roi_b.y = faces[ib].y;
roi_b.width = (faces[ib].width);
roi_b.height = (faces[ib].height);

ab = roi_b.width * roi_b.height; // Get the area of biggest element, at beginning it is same as "current" element

if (ac > ab) {

ib = ic;
roi_b.x = faces[ib].x;
roi_b.y = faces[ib].y;
roi_b.width = (faces[ib].width);
roi_b.height = (faces[ib].height);
}

crop = frame(roi_b);
cv::resize(crop, res, Size(img_width, img_height), 0, 0, INTER_LINEAR); // This will be needed later while saving images
cvtColor(crop, gray, CV_BGR2GRAY); // Convert cropped image to Grayscale

Point pt1(faces[ic].x, faces[ic].y); // Display detected faces on main window - live stream from camera
Point pt2((faces[ic].x + faces[ic].height), (faces[ic].y + faces[ic].width));
//rectangle(frame, pt1, pt2, Scalar(0, 255, 0), 2, 8, 0);

/* Calculate the position for annotated text */
int pos_x = std::max(roi_b.tl().x - 10, 0);
int pos_y = std::max(roi_b.tl().y - 10, 0);

if(createdFisher) {
Fisher_prediction = Fisher_model->predict(crop);
QString Fisher_qs = QString::number(Fisher_prediction);
/* Create the text we will annotate the box with */
string Fisher_text = format("Prediction Fisherfaces = %d", Fisher_prediction);
putText(frame, Fisher_text, Point(pos_x, pos_y), FONT_HERSHEY_PLAIN, 1.0, CV_RGB(0,255,0), 2.0);
/* Draw a green rectangle around the detected face */
rectangle(frame, pt1, pt2, MATCH_COLOR, 1);
ui.txtConsole->appendPlainText(QString("Fisherfaces - " + Fisher_qs));
}
if(createdEigen) {
Eigen_prediction = Eigen_model->predict(crop);
QString Eigen_qs = QString::number(Eigen_prediction);
/* Create the text we will annotate the box with */
string Eigen_text = format("Prediction Eigenfaces = %d", Eigen_prediction);
putText(frame, Eigen_text, Point(pos_x, pos_y), FONT_HERSHEY_PLAIN, 1.0, CV_RGB(0,255,0), 2.0);
/* Draw a green rectangle around the detected face */
rectangle(frame, pt1, pt2, MATCH_COLOR, 1);
ui.txtConsole->appendPlainText(QString("Eigenfaces - " + Eigen_qs));
}
if(createdLBPH) {
LBPH_prediction = LBPH_model->predict(crop);
QString LBPH_qs = QString::number(LBPH_prediction);
/* Create the text we will annotate the box with */
string LBPH_text = format("Prediction LBPH = %d", LBPH_prediction);
putText(frame, LBPH_text, Point(pos_x, pos_y), FONT_HERSHEY_PLAIN, 1.0, CV_RGB(0,255,0), 2.0);
/* Draw a green rectangle around the detected face */
rectangle(frame, pt1, pt2, MATCH_COLOR, 1);
ui.txtConsole->appendPlainText(QString("Linear Binary Patern Histogram - " + LBPH_qs));
}
}

putText(frame, text, cvPoint(30, 30), FONT_HERSHEY_COMPLEX_SMALL, 0.8, cvScalar(0, 0, 255), 1, CV_AA);
imshow("original", frame);

if (!crop.empty()) {
imshow("detected", crop);
}
else
destroyWindow("detected");
}

int c = waitKey(0);

Все необходимые #include и переменные вместе с классификатором инициализируются в начале программы.