c ++ Bag of Words - OpenCV：断言失败

Question

I'm trying to get to grips with Bag Of Words in c++ and I have some sample code, but this Error keeps on throwing it and I don't know why.

I'm completely new to this and am very much lost.

Here's the entirety of the code:

#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;
}

But then it throws this up:

OpenCV Error: Assertion failed (data.dims <= 2 && type == CV_32F && K > 0) in cv::kmeans, file C:\\buildslave64\\win64_amdoc1\\2_4_PackSlave-win32-vc11-shared\\opencv\\modules\\core\\src\\matrix.cpp, line 2701

Help, please.

EDIT

Line that it breaks on:

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

EDIT 2

Ive come across this , but i am unsure how to translate it to help with my cause.

Answer 1

I'm not 100% sure of what the code is doing since I'm not an OpenCV expert. However I can see that you are not initializing input in any way. This probably results in you not getting the descriptors you want, and thus not really doing anything. The code then probably breaks since it expects actual data in, but there is none.

In general, when dealing with OpenCV or other big "kind of messy" libraries I would advise you to proceed step by step, and checking that results are what you expect every step of the way. Copy-pasting a big blob of code and expecting it to work is never the best course of action.

Answer 2

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

Answer 3

Make sure that your image directory in 1st step is correct. It should exist training images as 0.jpg, 50.jpg, ... etc. Cause in a lot of situations, this error occurs when image is not loaded. You can add following codes after imread to check. Hope it can work.

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