c++图像检索（coarse to fine）

  //SLAM 相关,需要用到，于是写了一个...这里只实现了course==，不过想达到fine，也是分分钟可以实现的，哈哈
  1 #include <opencv2/core/core.hpp>  
  2 #include <opencv2/imgproc/imgproc.hpp>  
  3 #include <opencv2/highgui/highgui.hpp>  
  4 #include <iostream>  
  5 #include <cassert>
  6 #include <stdlib.h>
  7 #include <vector>
  8 #include <string>
  9 #include <iomanip>
 10 #include <algorithm>
 11 #include <queue>
 12 #include <memory>
 13 
 14 using namespace cv;  
 15 using namespace std; 
 16 
 17 class ColorHistogram  
 18 {  
 19 private:  
 20     int histSize[3];  
 21     float hranges[2];  
 22     const float* ranges[3];  
 23     int channels[3];  
 24      Mat reduce;
 25 public:  
 26   
 27     //构造函数  
 28     ColorHistogram()  
 29     {  
 30         histSize[0]= histSize[1]= histSize[2]= 64;  
 31         hranges[0] = 0.0;  
 32         hranges[1] = 255.0;  
 33         ranges[0] = hranges;  
 34         ranges[1] = hranges;  
 35         ranges[2] = hranges;  
 36         channels[0] = 0;  
 37         channels[1] = 1;  
 38         channels[2] = 2;  
 39     }  
 40   
 41     //计算彩色图像直方图  
 42     Mat getHistogram(const Mat& image)  
 43     {  
 44         Mat hist;  
 45   
 46         //BGR直方图  
 47         hranges[0]= 0.0;      
 48         hranges[1]= 255.0;  
 49         channels[0]= 0;   
 50         channels[1]= 1;   
 51         channels[2]= 2;   
 52   
 53         //计算  
 54         calcHist(&image,1,channels,Mat(),hist,3,histSize,ranges);  
 55         return hist;  
 56     }  
 57   
 58     //计算颜色的直方图  
 59     Mat getHueHistogram(const Mat &image)  
 60     {  
 61         Mat hist;  
 62         Mat hue;  
 63         //转换到HSV空间  
 64         cvtColor(image,hue,CV_BGR2HSV);  
 65   
 66         //设置1维直方图使用的参数  
 67         hranges[0] = 0.0;  
 68         hranges[1] = 180.0;  
 69         channels[0] = 0;  
 70         //计算直方图  
 71         calcHist(&hue,1,channels,Mat(),hist,1,histSize,ranges);  
 72         return hist;  
 73   
 74     }  
 75     
 76     //减少颜色  
 77     Mat colorReduce(const Mat &image,int div = 64)  
 78     {  
 79         int n = static_cast<int>(log(static_cast<double>(div))/log(2.0));  
 80         uchar mask = 0xFF<<n;  
 81         Mat_<Vec3b>::const_iterator it = image.begin<Vec3b>();  
 82         Mat_<Vec3b>::const_iterator itend = image.end<Vec3b>();  
 83         //设置输出图像  
 84         Mat result(image.rows,image.cols,image.type());  
 85         Mat_<Vec3b>::iterator itr = result.begin<Vec3b>();  
 86         for(;it != itend;++it,++itr)  
 87         {  
 88             (*itr)[0] = ((*it)[0]&mask) + div/2;  
 89             (*itr)[1] = ((*it)[1]&mask) + div/2;  
 90             (*itr)[2] = ((*it)[2]&mask) + div/2;  
 91         }  
 92         return result;  
 93     }  
 94     Mat getReduceHistogram(const Mat& image){
 95     
 96       reduce = colorReduce(image,32);  
 97       return getHistogram(reduce); 
 98     }
 99 
100   
101 };  
102 
103   
104 class ImageComparator  
105 {  
106 private:  
107     Mat reference;  
108     Mat input;  
109     Mat refH;  
110     Mat inputH;  
111    
112     ColorHistogram hist;  
113     int div;  
114 public:  
115     ImageComparator():div(32){}  
116   
117     void setColorReducation(int factor)  
118     {  
119         div = factor;  
120     }  
121   
122     int getColorReduction()  
123     {  
124         return div;  
125     }  
126   
127     void setRefrenceImage(const Mat &image)  
128     {  
129         reference = hist.colorReduce(image,div);  
130         refH = hist.getHistogram(reference);  
131     
132     }  
133     void setRefrenceHist(const Mat &hist1)  
134     {  
135         
136         refH = hist1;  
137     
138     }  
139     double compare(const Mat &image)  
140     {  
141         input = hist.colorReduce(image,div);  
142         inputH = hist.getHistogram(input);  
143         return compareHist(refH,inputH,CV_COMP_INTERSECT);  
144     } 
145     double comparehist(const Mat &inputH){
146       
147       return compareHist(refH,inputH,CV_COMP_INTERSECT);  
148     }
149 
150 };  
151 struct Node {
152     double value;
153     int idx;
154     Node (double v, int i): value(v), idx(i) {}
155     friend bool operator > (const struct Node &n1, const struct Node &n2) {
156       return n1.value > n2.value;
157     } 
158 };
159 
160 
161  
162 class Getsimilarsulotin{
163 public:
164   //KF的集合
165   vector<Mat>& _scenebase;
166   //待查询图片
167    Mat _referenceMat;
168    //结果
169   vector<pair<vector<pair<Mat,int>>,double> > res_hist_and_id_of_pic_and_scores;
170   //需要的分数最大的类的个数
171   //int _Nclass;
172   //每个可能图片的分数
173   vector<vector<double> > imgsscores;
174   //图像比较的对像
175   shared_ptr<ImageComparator> imgcompare=make_shared<ImageComparator>();
176 public:
177   Getsimilarsulotin(vector<Mat>& scenebase,Mat & referenceMat):_scenebase(scenebase){
178     _referenceMat=referenceMat.clone();
179     imgcompare->setRefrenceImage(_referenceMat);
180   }
181 
182  /*
183   * 输入：scenebase是一个vector,里面放的是KF的hist
184   *     Ncalss最终几个输出分数最大的类
185   *     referenceMat是带查询的图片
186   * 输出：res_hist_and_id_of_pic_and_scores是输出（分数越小的在越后面）
187   *      其中每个元素是一个pair<类，类的分数>
188   *      类是一个一维的数组，每个元素是一个pair<hist，index>
189   *      这里index的产生是由scenebase的顺序决定的
190   */
191   void getMostsimilar( )
192 { 
193 
194     const int nImages=_scenebase.size();
195     cout<<"start clustering..."<<endl;
196     //存放类的用二维vector存放聚类结果
197     vector<vector<pair<Mat,int>> > resofclu;
198 
199       
200       int startid=0;
201       vector<pair<Mat,int>> clutemp;
202       while(startid<nImages){ 
203       clutemp.clear();
204 
205       Mat referenceM=_scenebase[startid];
206       clutemp.push_back(make_pair(referenceM,startid));
207 
208       int iterid=startid+1;
209       if (iterid>=nImages){
210     break;
211       }
212       ImageComparator* imgcompare=new(ImageComparator);
213       imgcompare->setRefrenceHist(referenceM);
214       for (;iterid<nImages;iterid++){
215     
216     if(imgcompare->comparehist(_scenebase[iterid])>0.7*imgcompare->comparehist(_scenebase[startid])){
217       clutemp.push_back(make_pair(_scenebase[iterid],iterid));    
218     }
219     else{
220       break;
221     }
222       }
223       resofclu.push_back(clutemp);
224       cout<<"the class has "<<clutemp.size()<<" elements"<<endl;
225       startid=iterid;
226       delete imgcompare;
227       }
228       cout<<"Done! we get "<<resofclu.size()<<" classes"<<endl;
229       
230       cout<<"then we average of classes"<<endl;
231       
232 
233       //用于存放类的中心
234       vector<Mat> meanRes;
235       const int nclass=resofclu.size();
236      // meanRes.resize(nclass);
237       //int iii=0;
238       for(auto resclass:resofclu){
239     Mat Matmean=resofclu[0][0].first.clone();
240     Matmean=Matmean*0.0;
241     for(auto sMat:resclass){
242       Matmean=Matmean+sMat.first;
243     }
244     Matmean=Matmean+0.001;
245     Matmean=Matmean*(1.0/double(resclass.size()));
246     meanRes.push_back(Matmean);
247       }
248     
249     cout<<"now we test...."<<endl;
250     
251     vector<double> meanScores;
252     priority_queue<Node, vector<Node>, greater<Node>> minheap;
253     //做一个大小为_Nclass的最小堆,找出分数最大的类
254     const int _Nclass=1;
255     for (int i=0;i<_Nclass;i++){
256       double scores=imgcompare->comparehist(meanRes[i]);
257       meanScores.push_back(scores);
258       Node Notemp(scores,i);
259       minheap.push(Notemp);
260     }
261     for(int i=_Nclass;i<nclass;i++){
262       //当前的node
263       double scores=imgcompare->comparehist(meanRes[i]);
264       meanScores.push_back(scores);
265       Node Noteamp(scores,i);
266      // cout<<Noteamp.value<<endl;
267       if(minheap.top().value<Noteamp.value){
268     //将这个大的数放进去
269     minheap.push(Noteamp);
270     //将堆顶最小的数弹出
271     minheap.pop();
272       }else{
273     continue;
274       }
275     }
276     
277     cout<<"we have get the class with the maxinum score is the "<<minheap.top().idx<<"th class..."<<endl;
278     double maxscore=minheap.top().value;
279     int maxscoreindex=minheap.top().idx;
280     for(int i=0;i<nclass;i++){
281       if(i==maxscoreindex){continue;}
282       if (meanScores[i]>0.9*maxscore){
283     minheap.push(Node(meanScores[i],i));
284       }
285     }
286     int _Sclass=minheap.size();
287     cout<<"we find totally the other classes with scores > 0.9* maxscore,and the number of which is "<<_Sclass<<endl;
288     res_hist_and_id_of_pic_and_scores.resize(_Sclass);
289     for(int  i=0;i<_Sclass;i++){
290       cout<<"the  score is "<< minheap.top().value<<" and the idx is "<<minheap.top().idx<<endl;
291       //最小的放最后
292       res_hist_and_id_of_pic_and_scores[_Sclass-1-i]=(make_pair(resofclu[minheap.top().idx],minheap.top().value));
293       minheap.pop();
294     }
295     
296     
297     
298 
299 }  
300 
301 //求取每个图片与但前reference的score
302 void solvescores(){
303   for(auto lei_and_score:res_hist_and_id_of_pic_and_scores){
304     vector<double> scoretemp;
305     scoretemp.clear();
306     for(auto leitemp:lei_and_score.first){
307       scoretemp.push_back(imgcompare->comparehist(leitemp.first));
308      
309     }
310     imgsscores.push_back(scoretemp);
311   }
312   
313 }
314 
315 vector<vector<double> >& getscores(){
316   return imgsscores;
317     
318   
319 } 
320 vector<pair<vector<pair<Mat,int>>,double> > getres(){
321   return res_hist_and_id_of_pic_and_scores;
322 }
323 
324 
325 };
326 
327 void showtheimage(const string& strPath,const Node& nodett){
328   string strPrefix=strPath+"image_2/";
329       stringstream ss;
330     ss<<setfill(‘0‘)<<setw(6)<<nodett.idx;
331     imshow("my value is"+to_string(nodett.value)+";my index is"+to_string(nodett.idx),imread(strPrefix+ss.str()+".png"));
332   
333 }
334 void LoadImages(const string& strPath,const int n,vector<string>& vstrimage){
335   string strPrefix=strPath+"image_2/";
336   vstrimage.resize(n);
337   for(int i=0;i<n;i++){
338     stringstream ss;
339     ss<<setfill(‘0‘)<<setw(6)<<i;
340     vstrimage[i]=strPrefix+ss.str()+".png";
341   }
342   
343 }
344 int main(int argc,char** argv)  {
345   if(argc!=3){
346       cerr<<endl<<"Usage: ./main pathtoimage numberofimages"<<endl;
347     }
348     
349     
350     //load image
351     
352     vector<string> vstrimage;
353     LoadImages(string(argv[1]),stoi(string(argv[2])),vstrimage);
354     const int nImages=vstrimage.size();
355     
356     cout<<"start creating database...."<<endl;
357     //场景库
358     vector<Mat> scenebase;
359     scenebase.resize(nImages);
360     Mat imtemp;
361     ColorHistogram histsolver;
362     int ii=0;
363     for(auto sPath:vstrimage){
364       imtemp=imread(sPath);
365       Mat histtemp=histsolver.getReduceHistogram(imtemp);
366       scenebase[ii]=histtemp;
367       ii++;
368     }
369     cout<<"the database has been created..."<<"and the size of it is "<<scenebase.size()<<endl;
370    
371     //待查询图片
372     Mat imtest=imread("../image_2/000030.png");
373     imshow("im the reference",imtest);
374     //保存的结果
375     vector<pair<vector<pair<Mat,int>>,double> > res;
376     vector<vector<double> > imagescores;
377     //求解
378     shared_ptr<Getsimilarsulotin> gesolution=make_shared<Getsimilarsulotin>(scenebase,imtest);
379     gesolution->getMostsimilar();
380     res=gesolution->getres();
381     gesolution->solvescores();
382     imagescores=gesolution->getscores();
383     //res[0].first   可以查询类
384     //res[0].second  可以查询该类的分数
385     //(res[0].first)[0].first 可以查询类的一个元素的hist
386     //(res[0].first)[0].second 可以查询hist的index
387     //demo for 输出结果
388     vector<Node> resofpics;
389 
390     int ix=0;
391     for(auto lei_and_score:res){
392       int iy=0;
393       cout<<"类的分数是 ："<<lei_and_score.second<<endl<<"该类中的index有这些"<<endl;
394       for(auto hist_and_index:lei_and_score.first){
395     cout<<"index= "<<hist_and_index.second<<"        "<<"score= "<<imagescores[ix][iy]<<endl;
396     
397     iy++;
398       }
399       ix++;
400     }
401 
402     
403     
404   waitKey(0);
405   return 0;
406 }