我试图用c ++中的Bag Of Words来处理,我有一些示例代码,但是这个错误一直在扔它,我不知道为什么。
我对此完全陌生,而且非常失落。
以下是整个代码:
#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;
}
然后它抛出了这个:
OpenCV错误:cv :: kmeans中的断言失败(data.dims&lt; = 2&amp;&amp; type == CV_32F&amp;&amp; K&gt; 0&gt; 0),文件C:\ buildslave64 \ win64_amdoc1 \ 2_4_PackSlave-win32-vc11-shared \ opencv \ modules \ core \ src \ matrix.cpp,第2701行
请帮助。
修改
它打破的行:
dictionary = bowTrainer.cluster(featuresUnclustered); // -- Breaks
编辑2
Ive come across this,但我不确定如何翻译它以帮助我的事业。
答案 0 :(得分:1)
由于我不是OpenCV专家,所以我不能100%确定代码的作用。但是,我可以看到您没有以任何方式初始化input
。这可能会导致您无法获得所需的描述符,从而无法做任何事情。然后代码可能会中断,因为它需要实际数据,但没有。
一般情况下,在处理OpenCV或其他大型“杂乱”库时,我会建议您一步一步地进行,并检查结果是否是您期望的每一步。复制粘贴大量代码并期望它能够正常工作,这绝不是最好的行动方式。
答案 1 :(得分:1)
if (allDescriptors.type() != CV_32F)
{
allDescriptors.convertTo(allDescriptors, CV_32F);
}
答案 2 :(得分:0)
确保第1步中的图像目录正确无误。它应该存在训练图像为0.jpg,50.jpg,...等。在很多情况下,导致图像未加载时会出现此错误。您可以在imread之后添加以下代码进行检查。希望它能起作用。
if(input.empty())
{
cout << "Error: Image cannot be loaded !" << endl;
system("Pause");
return -1;
}