Hello, I use the Face Recognition's tutorial with OpenCV in C++ avaible on the official documentation. I have no problem during the compilation but when I run the program I get the following error:
OpenCV Error: Assertion failed (scn == 3 || scn == 4) in cvtColor, file /build/opencv-SviWsf/opencv-2.4.9.1+dfsg/modules/imgproc/src/color.cpp, line 3737 New image readError opening file "data.csv". Reason: /build/opencv-SviWsf/opencv-2.4.9.1+dfsg/modules/imgproc/src/color.cpp:3737: error: (-215) scn == 3 || scn == 4 in function cvtColor
I read a lot of topics about this problem but I don't arrive to solve it. I put some cout in the code to see where the program crash. The problem is in this line :
cvtColor(m,m2,CV_BGR2GRAY);
This is the complete code :
/*
* Copyright (c) 2011. Philipp Wagner <bytefish[at]gmx[dot]de>.
* Released to public domain under terms of the BSD Simplified license.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of the organization nor the names of its contributors
* may be used to endorse or promote products derived from this software
* without specific prior written permission.
*
* See <http://www.opensource.org/licenses/bsd-license>
*/
#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;
int numberImageReaded = 0;
while (getline(file, line)) {
stringstream liness(line);
getline(liness, path, separator);
getline(liness, classlabel);
if(!path.empty() && !classlabel.empty()) {
Mat m = imread(path, 1);
Mat m2;
cout << endl << "New image read";
cvtColor(m,m2,CV_BGR2GRAY);
numberImageReaded++;
cout << endl << "Number of image read = " << numberImageReaded;
images.push_back(m2);
labels.push_back(atoi(classlabel.c_str()));
}
}
cout << endl << "Read finish";
}
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 = string(argv[1]);
string fn_csv = string(argv[2]);
int deviceId = atoi(argv[3]);
// 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;
if(original.empty())
break;
else if(original.channels()>1)
cvtColor(original, gray, CV_BGR2GRAY);
else gray = original;
// 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;
}
I specify that I was obligated to replace this line : images.push_back(imread(path, 0)); by :
Mat m = imread(path, 1);
Mat m2;
cout << endl << "New image read";
cvtColor(m,m2,CV_BGR2GRAY);
numberImageReaded++;
cout << endl << "Number of image read = " << numberImageReaded;
images.push_back(m2);
because I had the error
OpenCV Error: Image step is wrong (The matrix is not continuous, thus its number of rows can not be changed) in reshape, file /build/opencv-SviWsf/opencv-2.4.9.1+dfsg/modules/core/src/matrix.cpp, line 802 terminate called after throwing an instance of 'cv::Exception' what(): /build/opencv-SviWsf/opencv-2.4.9.1+dfsg/modules/core/src/matrix.cpp:802: error: (-13) The matrix is not continuous, thus its number of rows can not be changed in function reshape Abandon (core dumped)
I also tried to put in my file data.csv full paths reference photos but it does not solve the problem (I'm running Ubuntu 16.04). The answers to this problem saying to change array during insertion (what I do) but the problem persists.
I change the code of CSV read to that :
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;
int numberImageReaded = 0;
while (getline(file, line)) {
stringstream liness(line);
getline(liness, path, separator);
getline(liness, classlabel);
if(!path.empty() && !classlabel.empty()) {
Mat m = imread(path, 1);
Mat m2;
cout << endl << "New image read";
if (m.empty()) {
cout << endl << "Image empty";
break;
}
cvtColor(m,m2,CV_BGR2GRAY);
numberImageReaded++;
cout << endl << "Number of image read = " << numberImageReaded;
images.push_back(m2);
labels.push_back(atoi(classlabel.c_str()));
}
}
cout << endl << "Read finish";
}
Now I have this result on the console :
New image read Image empty Erreur de segmentation (core dumped)
I hope you will can help me beacuse I am searching the solution during 4 days and I don't find it... Thanks a lot !