Чтение нарушения доступа в FeatureDetector OpenCV 2.4.5
Я попробовал примеры кодов о соответствии многих изображений в OpenCV 2.4.5 и я изменил этот код. Я нашел код ошибки:
Unhandled exception at 0x585a7090 in testing.exe:
0xC0000005: Access violation reading location 0x00000000.
Его вина в featureDetector->detect(queryImage, queryKeypoints),
Я не могу найти решение этой проблемы.
Пожалуйста, помогите мне.
#include <opencv2\highgui\highgui.hpp>
#include <opencv2\features2d\features2d.hpp>
#include <opencv2\contrib\contrib.hpp>
#include <iostream>
#include <fstream>
#include <conio.h>
#include <string>
using namespace std;
using namespace cv;
static void readTrainFilenames(const string& filename, string& dirName, vector<string>& trainFilenames);
static bool readImages(const string& queryImageName, Mat& queryImage);
static bool readTrainImages(const string& trainFilename, vector<Mat>& trainImages, vector<string>& trainImageNames);
static void detectKeypoints(const Mat& queryImage, vector<KeyPoint>& queryKeypoints,
const vector<Mat>& trainImages, vector<vector<KeyPoint>>& trainKeypoints, Ptr<FeatureDetector>& featureDetector);static void readTrainFilenames(const string& filename, string& dirName, vector<string>& trainFilenames)
{
trainFilenames.clear();
ifstream file(filename.c_str());
if(!file.is_open())
{
cout << "File can't open" << endl;
return;
}
size_t pos = filename.rfind("\\");
char dlmtr = '\\';
if(pos == String::npos)
{
pos = filename.rfind('/');
dlmtr = '/';
}
dirName = pos == string::npos ? "" : filename.substr(0, pos) + dlmtr;
while(!file.eof())
{
string str; getline(file, str);
if(str.empty()) break;
trainFilenames.push_back(str);
} // end while
file.close();
} // end void readTrainFilenamesstatic bool readImages(const string& queryImageName, Mat& queryImage)
{
cout << "reading images..." << endl;
queryImage = imread(queryImageName, CV_LOAD_IMAGE_GRAYSCALE);
if(queryImage.empty())
{
cout << "query image can not be read. \n";
return false;
} // end ifreturn true;
}
static bool readTrainImages(const string& trainFilename, vector<Mat>& trainImages, vector<string>& trainImageNames)
{
cout << "reading training images..." << endl;
string trainDirName = "D:/matching_to_many_images/";
readTrainFilenames(trainFilename, trainDirName, trainImageNames);
if(trainImageNames.empty())
{
cout << "Train image filenames can not be read." << endl;
return false;
} // end if
int readImageCount = 0;
for(size_t i = 0; i < trainImageNames.size(); i++)
{
string filename = trainDirName + trainImageNames[i];
Mat img = imread(filename, CV_LOAD_IMAGE_GRAYSCALE);
if(img.empty())
{
cout << "Train image " << filename << " can not be read." << endl;
}
else
{
readImageCount++;
}// end if
trainImages.push_back(img);
} // end for
if(!readImageCount)
{
cout << "All train images can not be read." << endl;
return false;
}
else
{
cout << readImageCount << " train images were read." << endl;
}
cout << endl;
return true;
}
static void detectKeypoints(const Mat& queryImage, vector<KeyPoint>& queryKeypoints,
const vector<Mat>& trainImages,
vector<vector<KeyPoint>>& trainKeypoints,
Ptr<FeatureDetector>& featureDetector){
cout << endl << "Extracting keypoints from images..." << endl;
try{
featureDetector->detect(queryImage, queryKeypoints);
}
catch(Ptr<FeatureDetector> a)
{
cout << "hmm" << endl;
}
cout << endl;
} // end void detectKeypoints
int main()
{
const string defaultDetectorType = "SURF";
const string defaultDescriptorType = "SURF";
const string defaultMatcherType = "FlannBased";
const string defaultQueryImageName = "D:/matching_to_many_images/query.png";
const string defaultFileWithTrainImages = "D:/matching_to_many_images/train/trainImages.txt";
const string defaultDirToSaveResImages = "D:/matching_to_many_images/results";
Ptr<FeatureDetector> featureDetector;
Ptr<DescriptorExtractor> descriptorExtractor;
Ptr<DescriptorMatcher> descriptorMatcher;
Mat queryImages;
vector<Mat> trainImages;
vector<string> trainImagesNames;
vector<KeyPoint> queryKeypoints;
vector<vector<KeyPoint>> trainKeypoints;
if(!readImages(defaultQueryImageName, queryImages))
{
_getch();
return -1;
} // end if
if(!readTrainImages(defaultFileWithTrainImages, trainImages, trainImagesNames))
{
_getch();
return -1;
}
detectKeypoints(queryImages, queryKeypoints, trainImages, trainKeypoints, featureDetector);
cout << "\n done \n";
_getch();
return 0;
} // end main method
Обновить:
#include <opencv2\highgui\highgui.hpp>
#include <opencv2\features2d\features2d.hpp>
#include <opencv2\contrib\contrib.hpp>
#include <iostream>
#include <fstream>
#include <conio.h>
#include <string>
using namespace std;
using namespace cv;
static void readTrainFilenames(const string& filename, string& dirName, vector<string>& trainFilenames);
static bool readImages(const string& queryImageName, Mat& queryImage);
static bool readTrainImages(const string& trainFilename, vector<Mat>& trainImages, vector<string>& trainImageNames);
static void detectKeypoints(const Mat& queryImage, vector<KeyPoint>& queryKeypoints, Ptr<FeatureDetector>& featureDetector);static void readTrainFilenames(const string& filename, string& dirName, vector<string>& trainFilenames)
{
trainFilenames.clear();
ifstream file(filename.c_str());
if(!file.is_open())
{
cout << "File can't open" << endl;
return;
}
size_t pos = filename.rfind("\\");
char dlmtr = '\\';
if(pos == String::npos)
{
pos = filename.rfind('/');
dlmtr = '/';
}
dirName = pos == string::npos ? "" : filename.substr(0, pos) + dlmtr;
while(!file.eof())
{
string str; getline(file, str);
if(str.empty()) break;
trainFilenames.push_back(str);
} // end while
file.close();
} // end void readTrainFilenamesstatic bool readImages(const string& queryImageName, Mat& queryImage)
{
cout << "reading images..." << endl;
queryImage = imread(queryImageName, CV_LOAD_IMAGE_GRAYSCALE);
if(queryImage.empty())
{
cout << "query image can not be read. \n";
return false;
} // end ifreturn true;
}
static bool readTrainImages(const string& trainFilename, vector<Mat>& trainImages, vector<string>& trainImageNames)
{
cout << "reading training images..." << endl;
string trainDirName = "D:/matching_to_many_images/";
readTrainFilenames(trainFilename, trainDirName, trainImageNames);
if(trainImageNames.empty())
{
cout << "Train image filenames can not be read." << endl;
return false;
} // end if
int readImageCount = 0;
for(size_t i = 0; i < trainImageNames.size(); i++)
{
string filename = trainDirName + trainImageNames[i];
Mat img = imread(filename, CV_LOAD_IMAGE_GRAYSCALE);
if(img.empty())
{
cout << "Train image " << filename << " can not be read." << endl;
}
else
{
readImageCount++;
}// end if
trainImages.push_back(img);
} // end for
if(!readImageCount)
{
cout << "All train images can not be read." << endl;
return false;
}
else
{
cout << readImageCount << " train images were read." << endl;
}
cout << endl;
return true;
}
static void detectKeypoints(const Mat& queryImage, vector<KeyPoint>& queryKeypoints, Ptr<FeatureDetector>& featureDetector){
cout << endl << "Extracting keypoints from images..." << endl;
featureDetector->detect(queryImage, queryKeypoints);cout << endl;
} // end void detectKeypoints
int main()
{
const string defaultDetectorType = "SURF";
const string defaultDescriptorType = "SURF";
const string defaultMatcherType = "FlannBased";
const string defaultQueryImageName = "D:/matching_to_many_images/query.png";
const string defaultFileWithTrainImages = "D:/matching_to_many_images/train/trainImages.txt";
const string defaultDirToSaveResImages = "D:/matching_to_many_images/results";
Ptr<FeatureDetector> featureDetector;
Ptr<DescriptorExtractor> descriptorExtractor;
Ptr<DescriptorMatcher> descriptorMatcher;
Mat queryImages;
vector<Mat> trainImages;
vector<string> trainImagesNames;
vector<KeyPoint> queryKeypoints;
vector<vector<KeyPoint>> trainKeypoints;
if(!readImages(defaultQueryImageName, queryImages))
{
_getch();
return -1;
} // end if
if(!readTrainImages(defaultFileWithTrainImages, trainImages, trainImagesNames))
{
_getch();
return -1;
}
detectKeypoints(queryImages, queryKeypoints, featureDetector);
cout << "\n done \n";
_getch();
return 0;
} // end main method
РЕШЕННЫЕ ПРОБЛЕМЫ:
#include <opencv2\highgui\highgui.hpp>
#include <opencv2\features2d\features2d.hpp>
#include <opencv2\contrib\contrib.hpp>
#include <opencv2\nonfree\nonfree.hpp>
#include <iostream>
#include <fstream>
#include <conio.h>
#include <string>
using namespace std;
using namespace cv;
const string defaultDetectorType = "SURF";
const string defaultDescriptorType = "SURF";
const string defaultMatcherType = "FlannBased";
const string defaultQueryImageName = "D:/matching_to_many_images/query.png";
const string defaultFileWithTrainImages = "D:/matching_to_many_images/train/trainImages.txt";
const string defaultDirToSaveResImages = "D:/matching_to_many_images/results";
static void readTrainFilenames(const string& filename, string& dirName, vector<string>& trainFilenames);
static bool readImages(const string& queryImageName, Mat& queryImage);
static bool readTrainImages(const string& trainFilename, vector<Mat>& trainImages, vector<string>& trainImageNames);
static void detectKeypoints(const Mat& queryImage, vector<KeyPoint>& queryKeypoints, Ptr<FeatureDetector>& featureDetector);
static bool createDetectorDescriptorMatcher(const string& detectorType,
const string& descriptorType,
const string& matcherType,
Ptr<FeatureDetector>& featureDetector,
Ptr<DescriptorExtractor>& descriptorExtractor,
Ptr<DescriptorMatcher>& descriptorMatcher);
static void readTrainFilenames(const string& filename, string& dirName, vector<string>& trainFilenames)
{
trainFilenames.clear();
ifstream file(filename.c_str());
if(!file.is_open())
{
cout << "File can't open" << endl;
return;
}
size_t pos = filename.rfind("\\");
char dlmtr = '\\';
if(pos == String::npos)
{
pos = filename.rfind('/');
dlmtr = '/';
}
dirName = pos == string::npos ? "" : filename.substr(0, pos) + dlmtr;
while(!file.eof())
{
string str; getline(file, str);
if(str.empty()) break;
trainFilenames.push_back(str);
} // end while
file.close();
} // end void readTrainFilenamesstatic bool readImages(const string& queryImageName, Mat& queryImage)
{
cout << "reading images..." << endl;
queryImage = imread(queryImageName, CV_LOAD_IMAGE_GRAYSCALE);
if(queryImage.empty())
{
cout << "query image can not be read. \n";
return false;
} // end ifreturn true;
}
static bool readTrainImages(const string& trainFilename, vector<Mat>& trainImages, vector<string>& trainImageNames)
{
cout << "reading training images..." << endl;
string trainDirName = "D:/matching_to_many_images/";
readTrainFilenames(trainFilename, trainDirName, trainImageNames);
if(trainImageNames.empty())
{
cout << "Train image filenames can not be read." << endl;
return false;
} // end if
int readImageCount = 0;
for(size_t i = 0; i < trainImageNames.size(); i++)
{
string filename = trainDirName + trainImageNames[i];
Mat img = imread(filename, CV_LOAD_IMAGE_GRAYSCALE);
if(img.empty())
{
cout << "Train image " << filename << " can not be read." << endl;
}
else
{
readImageCount++;
}// end if
trainImages.push_back(img);
} // end for
if(!readImageCount)
{
cout << "All train images can not be read." << endl;
return false;
}
else
{
cout << readImageCount << " train images were read." << endl;
}
cout << endl;
return true;
}
static void detectKeypoints(const Mat& queryImage, vector<KeyPoint>& queryKeypoints, Ptr<FeatureDetector>& featureDetector){
cout << endl << "Extracting keypoints from images..." << endl;
if(queryImage.empty())
{
cout << "Query Image EMPTY" << endl;
}
else{
cout << "Query Image FILLED" << endl;
}
featureDetector->detect(queryImage, queryKeypoints);cout << endl;
} // end void detectKeypoints
static bool createDetectorDescriptorMatcher(const string& detectorType,
const string& descriptorType,
const string& matcherType,
Ptr<FeatureDetector>& featureDetector,
Ptr<DescriptorExtractor>& descriptorExtractor,
Ptr<DescriptorMatcher>& descriptorMatcher)
{
cout << "Creating feature detector, descriptor extractor and descriptor matcher ... " << endl;
featureDetector = FeatureDetector::create(detectorType);
descriptorExtractor = DescriptorExtractor::create(descriptorType);
descriptorMatcher = DescriptorMatcher::create(matcherType);
cout << endl;
if(featureDetector.empty())
{
cout << "feature detector empty" << endl;
}
if(descriptorExtractor.empty())
{
cout << "descriptor extractor empty" << endl;
}
if(descriptorMatcher.empty())
{
cout << "descriptor matcher empty" << endl;
}
bool isCreated = !(featureDetector.empty() || descriptorExtractor.empty() || descriptorMatcher.empty());
if(!isCreated)
{
cout << "can not create feature detector or descriptor extractor or descriptor matcher of given types." << endl;
} // end if
return isCreated;
} // end void createDetectorDescriptorMatcher
int main()
{
initModule_nonfree();
string detectorType = defaultDetectorType;
string descriptorType = defaultDetectorType;
string matcherType = defaultMatcherType;
string queryImageName = defaultQueryImageName;
string fileWithTrainImages = defaultFileWithTrainImages;
string dirToSaveResImages = defaultDirToSaveResImages;
Ptr<FeatureDetector> featureDetector = FeatureDetector::create("SURF");
Ptr<DescriptorExtractor> descriptorExtractor = DescriptorExtractor::create("SURF");
Ptr<DescriptorMatcher> descriptorMatcher;
if(!createDetectorDescriptorMatcher(detectorType, descriptorType, matcherType, featureDetector, descriptorExtractor, descriptorMatcher))
{
_getch();
return -1;
}Mat queryImages;
vector<Mat> trainImages;
vector<string> trainImagesNames;
vector<KeyPoint> queryKeypoints;
vector<vector<KeyPoint>> trainKeypoints;
if(!readImages(defaultQueryImageName, queryImages))
{
_getch();
return -1;
} // end if
if(!readTrainImages(defaultFileWithTrainImages, trainImages, trainImagesNames))
{
_getch();
return -1;
}
detectKeypoints(queryImages, queryKeypoints, featureDetector);
cout << "\n done \n";
_getch();
return 0;
} // end main method
ПОЛНЫЙ ОБРАЗЕЦ КОДОВ, ПОДХОДЯЩИХ К МНОГИМ ИЗОБРАЖЕНИЯМ
#include <opencv2\highgui\highgui.hpp>
#include <opencv2\features2d\features2d.hpp>
#include <opencv2\contrib\contrib.hpp>
#include <opencv2\nonfree\nonfree.hpp>
#include <iostream>
#include <fstream>
#include <conio.h>
#include <string>
using namespace std;
using namespace cv;
const string defaultDetectorType = "SURF";
const string defaultDescriptorType = "SURF";
const string defaultMatcherType = "FlannBased";
const string defaultQueryImageName = "D:/matching_to_many_images/query.png";
const string defaultFileWithTrainImages = "D:/matching_to_many_images/train/trainImages.txt";
const string defaultDirToSaveResImages = "D:/matching_to_many_images/results";
static void readTrainFilenames(const string& filename, string& dirName, vector<string>& trainFilenames);
static bool readImages(const string& queryImageName, Mat& queryImage);
static bool readTrainImages(const string& trainFilename, vector<Mat>& trainImages, vector<string>& trainImageNames);
static void detectKeypoints(const Mat& queryImage, vector<KeyPoint>& queryKeypoints, const vector<Mat>& trainImages, vector<vector<KeyPoint>>& trainKeypoints, Ptr<FeatureDetector>& featureDetector);
static bool createDetectorDescriptorMatcher(const string& detectorType,
const string& descriptorType,
const string& matcherType,
Ptr<FeatureDetector>& featureDetector,
Ptr<DescriptorExtractor>& descriptorExtractor,
Ptr<DescriptorMatcher>& descriptorMatcher);
static void computeDescriptors(const Mat& queryImage, vector<KeyPoint>& queryKeypoints, Mat& queryDescriptors,
const vector<Mat>& trainImages, vector<vector<KeyPoint>>& trainKeypoints, vector<Mat>& trainDescriptors,
Ptr<DescriptorExtractor>& descriptorExtractor);
static void matchDescriptors(const Mat& queryDescriptors, const vector<Mat>& trainDescriptors, vector<DMatch>& matches, Ptr<DescriptorMatcher>& descriptorMatcher);
static void maskMatchesByTrainImgIdx(const vector<DMatch>& matches, int trainImgIdx, vector<char>& mask);
static void readTrainFilenames(const string& filename, string& dirName, vector<string>& trainFilenames)
{
trainFilenames.clear();
ifstream file(filename.c_str());
if(!file.is_open())
{
cout << "File can't open" << endl;
return;
}
size_t pos = filename.rfind("\\");
char dlmtr = '\\';
if(pos == String::npos)
{
pos = filename.rfind('/');
dlmtr = '/';
}
dirName = pos == string::npos ? "" : filename.substr(0, pos) + dlmtr;
while(!file.eof())
{
string str; getline(file, str);
if(str.empty()) break;
trainFilenames.push_back(str);
} // end while
file.close();
} // end void readTrainFilenamesstatic bool readImages(const string& queryImageName, Mat& queryImage)
{
cout << "reading images..." << endl;
queryImage = imread(queryImageName, CV_LOAD_IMAGE_GRAYSCALE);
if(queryImage.empty())
{
cout << "query image can not be read. \n";
return false;
} // end ifreturn true;
}
static bool readTrainImages(const string& trainFilename, vector<Mat>& trainImages, vector<string>& trainImageNames)
{
cout << "reading training images..." << endl;
string trainDirName = "D:/matching_to_many_images/";
readTrainFilenames(trainFilename, trainDirName, trainImageNames);
if(trainImageNames.empty())
{
cout << "Train image filenames can not be read." << endl;
return false;
} // end if
int readImageCount = 0;
for(size_t i = 0; i < trainImageNames.size(); i++)
{
string filename = trainDirName + trainImageNames[i];
Mat img = imread(filename, CV_LOAD_IMAGE_GRAYSCALE);
if(img.empty())
{
cout << "Train image " << filename << " can not be read." << endl;
}
else
{
readImageCount++;
}// end if
trainImages.push_back(img);
} // end for
if(!readImageCount)
{
cout << "All train images can not be read." << endl;
return false;
}
else
{
cout << readImageCount << " train images were read." << endl;
}
cout << endl;
return true;
}
static void detectKeypoints(const Mat& queryImage, vector<KeyPoint>& queryKeypoints, const vector<Mat>& trainImages, vector<vector<KeyPoint>>& trainKeypoints, Ptr<FeatureDetector>& featureDetector){
cout << endl << "Extracting keypoints from images..." << endl;
if(queryImage.empty())
{
cout << "Query Image EMPTY" << endl;
}
else{
cout << "Query Image FILLED" << endl;
}
featureDetector->detect(queryImage, queryKeypoints);
featureDetector->detect(trainImages, trainKeypoints);
cout << endl;
} // end void detectKeypoints
static bool createDetectorDescriptorMatcher(const string& detectorType,
const string& descriptorType,
const string& matcherType,
Ptr<FeatureDetector>& featureDetector,
Ptr<DescriptorExtractor>& descriptorExtractor,
Ptr<DescriptorMatcher>& descriptorMatcher)
{
cout << "Creating feature detector, descriptor extractor and descriptor matcher ... " << endl;
featureDetector = FeatureDetector::create(detectorType);
descriptorExtractor = DescriptorExtractor::create(descriptorType);
descriptorMatcher = DescriptorMatcher::create(matcherType);
cout << endl;
if(featureDetector.empty())
{
cout << "feature detector empty" << endl;
}
if(descriptorExtractor.empty())
{
cout << "descriptor extractor empty" << endl;
}
if(descriptorMatcher.empty())
{
cout << "descriptor matcher empty" << endl;
}
bool isCreated = !(featureDetector.empty() || descriptorExtractor.empty() || descriptorMatcher.empty());
if(!isCreated)
{
cout << "can not create feature detector or descriptor extractor or descriptor matcher of given types." << endl;
} // end if
return isCreated;
} // end void createDetectorDescriptorMatcher
static void computeDescriptors(const Mat& queryImage, vector<KeyPoint>& queryKeypoints, Mat& queryDescriptors,
const vector<Mat>& trainImages, vector<vector<KeyPoint>>& trainKeypoints, vector<Mat>& trainDescriptors,
Ptr<DescriptorExtractor>& descriptorExtractor)
{
cout << "computing descriptors for keypoints..." << endl;
descriptorExtractor->compute(queryImage, queryKeypoints, queryDescriptors);
descriptorExtractor->compute(trainImages, trainKeypoints, trainDescriptors);
int totalTrainDesc = 0;
for(vector<Mat>::const_iterator tdIter = trainDescriptors.begin(); tdIter != trainDescriptors.end(); tdIter++)
totalTrainDesc += tdIter->rows;
cout << "Query descriptors count : " << queryDescriptors.rows << "; Total train descriptors count : " << totalTrainDesc << endl;
cout << endl;
} // end void computeDescriptors
static void matchDescriptors(const Mat& queryDescriptors, const vector<Mat>& trainDescriptors, vector<DMatch>& matches, Ptr<DescriptorMatcher>& descriptorMatcher)
{
cout << "Set train descriptors collection in the matcher and match query descriptors to them..." << endl;
TickMeter tm;
tm.start();
descriptorMatcher->add(trainDescriptors);
descriptorMatcher->train();
tm.stop();
double buildTime = tm.getTimeMilli();
tm.start();
descriptorMatcher->match(queryDescriptors, matches);
tm.stop();
double matchTime = tm.getTimeMilli();
CV_Assert(queryDescriptors.rows == (int)matches.size() || matches.empty());
cout << "Number of matches: " << matches.size() << endl;
cout << "Build time: " << buildTime << " ms; Match time: " << matchTime << " ms" << endl;
cout << endl;
} // end void matchDescriptors
static void saveResultImages(const Mat& queryImage, const vector<KeyPoint>& queryKeypoints,
const vector<Mat>& trainImages, const vector<vector<KeyPoint>> &trainKeypoints, const vector<DMatch>& matches,
const vector<string>& trainImageNames, const string& resultDir)
{
cout << "Save results..." << endl;
Mat drawImg;
vector<char> mask;
for(size_t i = 0; i < trainImages.size(); i++)
{
if(!trainImages[i].empty())
{
maskMatchesByTrainImgIdx(matches, (int)i, mask);
drawMatches(queryImage, queryKeypoints, trainImages[i], trainKeypoints[i], matches, drawImg, Scalar(255, 0, 0), Scalar(0, 255, 255), mask);
string filename = resultDir + "/res_" + trainImageNames[i];
if(!imwrite(filename, drawImg))
{
cout << "Image " << filename << " can not be saved (may be because directory " << resultDir << " does not exist" << endl;
} // end if
} // end if
}
} // end void saveResultImages
static void maskMatchesByTrainImgIdx(const vector<DMatch>& matches, int trainImgIdx, vector<char>& mask)
{
mask.resize(matches.size());
fill(mask.begin(), mask.end(), 0);
for(size_t i = 0; i < matches.size(); i++)
{
if(matches[i].imgIdx == trainImgIdx)
{
mask[i] = 1;
}
}
} // end void maskMatchesByTrainImgIdx
int main()
{
initModule_nonfree();
string detectorType = defaultDetectorType;
string descriptorType = defaultDetectorType;
string matcherType = defaultMatcherType;
string queryImageName = defaultQueryImageName;
string fileWithTrainImages = defaultFileWithTrainImages;
string dirToSaveResImages = defaultDirToSaveResImages;
Ptr<FeatureDetector> featureDetector = FeatureDetector::create("SURF");
Ptr<DescriptorExtractor> descriptorExtractor = DescriptorExtractor::create("SURF");
Ptr<DescriptorMatcher> descriptorMatcher;
if(!createDetectorDescriptorMatcher(detectorType, descriptorType, matcherType, featureDetector, descriptorExtractor, descriptorMatcher))
{
_getch();
return -1;
}
Mat queryImages;
vector<Mat> trainImages;
vector<string> trainImagesNames;
vector<KeyPoint> queryKeypoints;
vector<vector<KeyPoint>> trainKeypoints;
if(!readImages(defaultQueryImageName, queryImages))
{
_getch();
return -1;
} // end if
if(!readTrainImages(defaultFileWithTrainImages, trainImages, trainImagesNames))
{
_getch();
return -1;
}
detectKeypoints(queryImages, queryKeypoints, trainImages, trainKeypoints, featureDetector);
Mat queryDescriptors;
vector<Mat> trainDescriptors;
computeDescriptors(queryImages, queryKeypoints, queryDescriptors, trainImages, trainKeypoints, trainDescriptors, descriptorExtractor);
vector<DMatch> matches;
matchDescriptors(queryDescriptors, trainDescriptors, matches, descriptorMatcher);
saveResultImages(queryImages, queryKeypoints, trainImages, trainKeypoints, matches, trainImagesNames, dirToSaveResImages);
cout << "\n done \n";
_getch();
return 0;
} // end main method
Решение
документация для класса FeatureDetector говорит, что это абстрактный базовый класс, что означает, что вы не должны иметь возможность создавать экземпляр этого класса. Это вина OpenCV, что компилятор не жалуется!
Попробуйте добавить:
Ptr<FeatureDetector> featureDetector = FeatureDetector::create(defaultDetectorType);
Обновить:
Моим следующим предложением было бы уменьшить сложность. Упростите основную программу до минимальной рабочей версии:
int main()
{
cv::initModule_nonfree(); // to load SURF/SIFT etc.
std::vector<cv::KeyPoint> queryKeypoints;
cv::Mat queryImage = cv::imread(FILENAME, CV_LOAD_IMAGE_GRAYSCALE);
cv::Ptr<FeatureDetector> featureDetector = cv::FeatureDetector::create("SURF");
featureDetector->detect(queryImage, queryKeypoints);
}
Если вышеприведенная версия работает, начните добавлять больше функций (медленно), пока не получите текущую версию. В тот момент, когда ошибка возвращается, вы знаете, что последняя добавленная часть является виновником, и вы можете сосредоточиться на этом.
Если вышеуказанная версия не работает, вы, по крайней мере, создали SSCCE, которую вы можете попытаться исправить (с помощью других).
Кстати: сообщение об ошибке говорит вам, что ваша программа пытается прочитать расположение памяти 0x00000000 Это показатель того, что вы используете неинициализированную структуру данных, но я не уверен, где проблема в вашей программе.
Другие решения
Кажется, вы не инициализировали Ptr<FeatureDetector> featureDetector; где угодно, это абстрактный класс