c ++ Bag of Words - OpenCV：斷言失敗

Question

我試圖用c ++中的Bag Of Words來處理，我有一些示例代碼，但是這個錯誤一直在拋出它，我不知道為什么。

我對此完全陌生，而且非常失落。

這是完整的代碼：

#include "stdafx.h"
#include <opencv/cv.h>
#include <opencv/highgui.h>
#include <opencv2/nonfree/features2d.hpp>

using namespace cv;
using namespace std;

#define DICTIONARY_BUILD 1 // set DICTIONARY_BUILD 1 to do Step 1, otherwise it goes to step 2

int _tmain(int argc, _TCHAR* argv[])
{   
#if DICTIONARY_BUILD == 1

//Step 1 - Obtain the set of bags of features.

//to store the input file names
char * filename = new char[100];        
//to store the current input image
Mat input;  

//To store the keypoints that will be extracted by SIFT
vector<KeyPoint> keypoints;
//To store the SIFT descriptor of current image
Mat descriptor;
//To store all the descriptors that are extracted from all the images.
Mat featuresUnclustered;
//The SIFT feature extractor and descriptor
SiftDescriptorExtractor detector;   

//I select 20 (1000/50) images from 1000 images to extract feature descriptors and build the vocabulary
for(int f=0;f<999;f+=50){       
    //create the file name of an image
    sprintf(filename,"G:\\testimages\\image\\%i.jpg",f);

    //open the file
    input = imread(filename, CV_LOAD_IMAGE_GRAYSCALE); // -- Forgot to add in

    //detect feature points
    detector.detect(input, keypoints);
    //compute the descriptors for each keypoint
    detector.compute(input, keypoints,descriptor);      
    //put the all feature descriptors in a single Mat object 
    featuresUnclustered.push_back(descriptor);      
    //print the percentage
    printf("%i percent done\n",f/10);
}   


//Construct BOWKMeansTrainer
//the number of bags
int dictionarySize=200;
//define Term Criteria
TermCriteria tc(CV_TERMCRIT_ITER,100,0.001);
//retries number
int retries=1;
//necessary flags
int flags=KMEANS_PP_CENTERS;
//Create the BoW (or BoF) trainer
BOWKMeansTrainer bowTrainer(dictionarySize,tc,retries,flags);
//cluster the feature vectors
Mat dictionary;


dictionary=bowTrainer.cluster(featuresUnclustered); // -- BREAKS


//store the vocabulary
FileStorage fs("dictionary.yml", FileStorage::WRITE);
fs << "vocabulary" << dictionary;
fs.release();

#else
//Step 2 - Obtain the BoF descriptor for given image/video frame. 

//prepare BOW descriptor extractor from the dictionary    
Mat dictionary; 
FileStorage fs("dictionary.yml", FileStorage::READ);
fs["vocabulary"] >> dictionary;
fs.release();   

//create a nearest neighbor matcher
Ptr<DescriptorMatcher> matcher(new FlannBasedMatcher);
//create Sift feature point extracter
Ptr<FeatureDetector> detector(new SiftFeatureDetector());
//create Sift descriptor extractor
Ptr<DescriptorExtractor> extractor(new SiftDescriptorExtractor);    
//create BoF (or BoW) descriptor extractor
BOWImgDescriptorExtractor bowDE(extractor,matcher);
//Set the dictionary with the vocabulary we created in the first step
bowDE.setVocabulary(dictionary);

//To store the image file name
char * filename = new char[100];
//To store the image tag name - only for save the descriptor in a file
char * imageTag = new char[10];

//open the file to write the resultant descriptor
FileStorage fs1("descriptor.yml", FileStorage::WRITE);  

//the image file with the location. change it according to your image file location
sprintf(filename,"G:\\testimages\\image\\1.jpg");       
//read the image
Mat img=imread(filename,CV_LOAD_IMAGE_GRAYSCALE);       
//To store the keypoints that will be extracted by SIFT
vector<KeyPoint> keypoints;     
//Detect SIFT keypoints (or feature points)
detector->detect(img,keypoints);
//To store the BoW (or BoF) representation of the image
Mat bowDescriptor;      
//extract BoW (or BoF) descriptor from given image
bowDE.compute(img,keypoints,bowDescriptor);

//prepare the yml (some what similar to xml) file
sprintf(imageTag,"img1");           
//write the new BoF descriptor to the file
fs1 << imageTag << bowDescriptor;       

//You may use this descriptor for classifying the image.

//release the file storage
fs1.release();
#endif
printf("\ndone\n"); 
return 0;
}

但后來它拋出了這個：

OpenCV錯誤：cv :: kmeans中的斷言失敗（data.dims <= 2 && type == CV_32F && K> 0），文件C：\\ buildslave64 \\ win64_amdoc1 \\ 2_4_PackSlave-win32-vc11-shared \\ opencv \\ modules \\ core \\ src \\ matrix.cpp，第2701行

請幫助。

編輯

它打破的線：

dictionary = bowTrainer.cluster(featuresUnclustered); // -- Breaks

編輯2

我遇到過這個 ，但我不確定如何翻譯它以幫助我的事業。

Answer 1

因為我不是OpenCV專家，所以我不能100％確定代碼在做什么。 但是我可以看到你沒有以任何方式初始化input 。 這可能會導致您無法獲得所需的描述符，從而無法做任何事情。 然后代碼可能會中斷，因為它期望實際數據，但沒有。

一般來說，在處理OpenCV或其他大型“雜亂”庫時，我建議你一步一步地進行，並檢查結果是你期望的每一步。 復制粘貼大量代碼並期望它能夠正常工作，這絕不是最好的行動方案。

Answer 2

if (allDescriptors.type() != CV_32F)
{
    allDescriptors.convertTo(allDescriptors, CV_32F);
}

Answer 3

確保第1步中的圖像目錄正確無誤。 它應該存在訓練圖像為0.jpg，50.jpg，...等。在很多情況下，導致圖像未加載時會出現此錯誤。 您可以在imread之后添加以下代碼進行檢查。 希望它能奏效。

    if(input.empty())
    {
        cout << "Error: Image cannot be loaded !" << endl;
        system("Pause");
        return -1;
    }