├── ocv.h
├── data
    ├── 9.bmp
    ├── cascade.txt.range
    └── cascade.txt
├── Makefile
├── MyStruct.h
├── SimpleClassifier.cpp
├── MatrixRotate.cpp
├── CascadeClassifier.h
├── AdaBoostClassifier.h
├── RotateImage.cpp
├── MyStruct.cpp
├── IntImage.h
├── AdaBoostClassifier.cpp
├── SimpleClassifier.h
├── main.cpp
├── MyCamshift.cpp
├── CascadeClassifier.cpp
└── IntImage.cpp


/ocv.h:
--------------------------------------------------------------------------------
1 | 
2 | #include "opencv/cv.h"
3 | #include "opencv/highgui.h"
4 | 


--------------------------------------------------------------------------------
/data/9.bmp:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/andrewrong/FaceDect/HEAD/data/9.bmp


--------------------------------------------------------------------------------
/data/cascade.txt.range:
--------------------------------------------------------------------------------
1 | 17087.4
2 | 141337
3 | 661507
4 | 3.2258e+007
5 | 14.3214
6 | 89.1736
7 | 


--------------------------------------------------------------------------------
/Makefile:
--------------------------------------------------------------------------------
1 | main:MyCamshift.cpp RotateImage.cpp AdaBoostClassifier.cpp CascadeClassifier.cpp IntImage.cpp MyStruct.cpp SimpleClassifier.cpp MatrixRotate.cpp main.cpp 
2 | 	g++ `pkg-config opencv --libs --cflags opencv`  MyCamshift.cpp RotateImage.cpp AdaBoostClassifier.cpp CascadeClassifier.cpp IntImage.cpp MatrixRotate.cpp MyStruct.cpp SimpleClassifier.cpp main.cpp -o main
3 | 


--------------------------------------------------------------------------------
/MyStruct.h:
--------------------------------------------------------------------------------
 1 | #ifndef MYSTRUCT_H
 2 | #define MYSTRUCT_H
 3 | struct MRect
 4 | {
 5 |     long left;
 6 |     long top;
 7 |     long right;
 8 |     long bottom;
 9 | 
10 |     public:
11 |     long Height() const
12 |     {
13 | 	return bottom - top;
14 |     }
15 |     long Width() const
16 |     {
17 | 	return right - left;
18 |     }
19 |     bool IntersectRect(MRect& source1,MRect& source2);
20 |     void UnionRect(MRect& s1,MRect& s2);
21 | };
22 | 
23 | struct MSize
24 | {
25 |     long cx;
26 |     long cy;
27 | 	MSize(long x,long y)
28 | 	{
29 | 		cx = x;
30 | 		cy = y;
31 | 	}
32 | };
33 | #endif
34 | 


--------------------------------------------------------------------------------
/SimpleClassifier.cpp:
--------------------------------------------------------------------------------
 1 | 
 2 | #include <fstream>
 3 | #include <vector>
 4 | #include <math.h>
 5 | using namespace std;
 6 | #include "IntImage.h"
 7 | #include "SimpleClassifier.h"
 8 | #include "AdaBoostClassifier.h"
 9 | #include "CascadeClassifier.h"
10 | 
11 | 
12 | 
13 | void SimpleClassifier::ReadFromFile(ifstream& f)
14 | {
15 | 	f>>thresh>>parity>>type;
16 | 	f>>x1>>x2>>x3>>x4>>y1>>y2>>y3>>y4;
17 | 	f.ignore(256,'\n');
18 | 	ASSERT(parity == 0 || parity == 1);
19 | 	ASSERT(type>=0 && type<=4);
20 | }
21 | 
22 | void SimpleClassifier::WriteToFile(ofstream& f) const
23 | {
24 | 	f<<thresh<<" ";
25 | 	f<<parity<<" ";
26 | 	f<<type<<" ";
27 | 	f<<x1<<" ";
28 | 	f<<x2<<" ";
29 | 	f<<x3<<" ";
30 | 	f<<x4<<" ";
31 | 	f<<y1<<" ";
32 | 	f<<y2<<" ";
33 | 	f<<y3<<" ";
34 | 	f<<y4<<" ";
35 | 	f<<endl;
36 | }
37 | 


--------------------------------------------------------------------------------
/MatrixRotate.cpp:
--------------------------------------------------------------------------------
 1 | /*
 2 |  * describe:矩阵旋转
 3 |  * author: andrewrong
 4 |  * */
 5 | #include <iostream>
 6 | #include <string>
 7 | #include <fstream>
 8 | #include "opencv/cv.h"
 9 | #include "opencv/highgui.h"
10 | 
11 | using namespace std;
12 | 
13 | void MatrixRotate(int x,int y,float degree,int& rotatedX,int& rotatedY)
14 | {
15 |     float map[2];
16 |     map[0] = x;
17 |     map[1] = y;
18 | 
19 |     CvMat mat = cvMat(2,1,CV_32F,map);
20 | 
21 |     double angle = (degree * CV_PI) / 180.0;
22 |     double sina = sin(angle);
23 |     double cosa = cos(angle);
24 | 
25 |     float mulMap[4];
26 |     CvMat mulMat = cvMat(2,2,CV_32F,mulMap);
27 |     mulMap[0] = cosa;
28 |     mulMap[1] = sina;
29 |     mulMap[2] = -sina;
30 |     mulMap[3] = cosa;
31 | 
32 |     float dst[2] = {0};
33 |     CvMat dstMat = cvMat(2,1,CV_32F,dst);
34 | 
35 |     cvGEMM(&mulMat,&mat,1,NULL,0,&dstMat,0);
36 |     
37 |     rotatedX = dst[0];
38 |     rotatedY = dst[1];
39 | }
40 | 


--------------------------------------------------------------------------------
/CascadeClassifier.h:
--------------------------------------------------------------------------------
 1 | #ifndef CAS_H
 2 | #define CAS_H
 3 | #include <fstream>
 4 | #include <string>
 5 | #include <vector>
 6 | #include "IntImage.h"
 7 | #include "AdaBoostClassifier.h"
 8 | #include "SimpleClassifier.h"
 9 | #include "MyStruct.h"
10 | #include "ocv.h"
11 | 
12 | const int sx = 24;
13 | const int sy = 24;
14 | extern REAL mean_min,mean_max,sq_min,sq_max,var_min,var_max;
15 | 
16 | struct CascadeClassifier
17 | {
18 | 	int count;
19 | 	AdaBoostClassifier* ac;
20 | 
21 | 	CascadeClassifier();
22 | 	~CascadeClassifier();
23 | 	void Clear(void);
24 | 	CascadeClassifier& operator=(const CascadeClassifier& source);
25 | 
26 | 	void WriteToFile(std::ofstream& f) const;
27 | 	void ReadFromFile(std::ifstream& f);
28 | 	void LoadDefaultCascade(std::string& cascade_filename,std::string& cascade_filename_range);
29 | 	virtual void ApplyOriginalSize(IntImage& original,std::vector<MRect>& results) ;
30 | 	void DrawResults(IntImage& image, const std::vector<MRect>& results) const;
31 | };
32 | 
33 | void PostProcess(std::vector<MRect>& result, const int combine_min);
34 | #endif
35 | 


--------------------------------------------------------------------------------
/AdaBoostClassifier.h:
--------------------------------------------------------------------------------
 1 | #ifndef ADA_H
 2 | #define ADA_H
 3 | #include <fstream>
 4 | #include "IntImage.h"
 5 | #include "SimpleClassifier.h"
 6 | #include "MyStruct.h"
 7 | #include "ocv.h"
 8 | 
 9 | 
10 | enum GOAL_METHODS {GOAL_METHOD_MIN_ERROR = 1, GOAL_METHOD_VALID_DR = 2, GOAL_METHOD_FIX_FP = 3};
11 | 
12 | struct AdaBoostClassifier
13 | {
14 | 	int count;
15 | 	SimpleClassifier* scs;
16 | 	REAL* alphas;
17 | 	REAL thresh;
18 | 
19 | 	AdaBoostClassifier();
20 | 	~AdaBoostClassifier();
21 | 	void Clear(void);
22 | 	AdaBoostClassifier& operator=(const AdaBoostClassifier& source);
23 | 	
24 | 	void WriteToFile(std::ofstream& f) const;
25 | 	void ReadFromFile(std::ifstream& f);
26 | 	void InitToGivenSize(const int size);
27 | 
28 | 	inline REAL GetValue(const IntImage& im) const;
29 | 	inline int ApplyImagePatch(const IntImage& im) const;
30 | };
31 | 
32 | REAL AdaBoostClassifier::GetValue(const IntImage& im) const
33 | {
34 | 	int i;
35 | 	REAL value;
36 | 
37 | 	value = 0.0;
38 | 	for(i=0;i<count;i++) value += alphas[i]*scs[i].Apply(im);
39 | 	
40 | 	return value;
41 | }
42 | 
43 | int AdaBoostClassifier::ApplyImagePatch(const IntImage& im) const
44 | {
45 | 	return (GetValue(im)>=thresh)?1:0;
46 | }
47 | #endif
48 | 


--------------------------------------------------------------------------------
/RotateImage.cpp:
--------------------------------------------------------------------------------
 1 | #include <string>
 2 | #include "opencv/cv.h"
 3 | #include "opencv/highgui.h"
 4 | 
 5 | using namespace std;
 6 | 
 7 | void RotateImage(IplImage* img,IplImage* imgRotate,float degree)
 8 | {  
 9 |     double angle = degree  * CV_PI / 180.0; // 弧度    
10 |     double a = sin(angle), b = cos(angle);   
11 |     int width = img->width;    
12 |     int height = img->height;    
13 |     //int width_rotate= int(height * fabs(a) + width * fabs(b));    
14 |     //int height_rotate=int(width * fabs(a) + height * fabs(b));    
15 |     //旋转数组map  
16 |     // [ m0  m1  m2 ] ===>  [ A11  A12   b1 ]  
17 |     // [ m3  m4  m5 ] ===>  [ A21  A22   b2 ]  
18 |     float map[6];  
19 |     CvMat map_matrix = cvMat(2, 3, CV_32F, map);    
20 |     // 旋转中心  
21 |     CvPoint2D32f center = cvPoint2D32f(width / 2, height / 2);    
22 |     cv2DRotationMatrix(center, degree, 1.0, &map_matrix);    
23 |     //map[2] += (width_rotate - width) / 2;    
24 |     //map[5] += (height_rotate - height) / 2;    
25 |     //对图像做仿射变换  
26 |     //CV_WARP_FILL_OUTLIERS - 填充所有输出图像的象素。  
27 |     //如果部分象素落在输入图像的边界外，那么它们的值设定为 fillval.  
28 |     //CV_WARP_INVERSE_MAP - 指定 map_matrix 是输出图像到输入图像的反变换，  
29 |     cvWarpAffine( img,imgRotate, &map_matrix, CV_INTER_LINEAR | CV_WARP_FILL_OUTLIERS, cvScalarAll(0));    
30 | }  
31 | 


--------------------------------------------------------------------------------
/MyStruct.cpp:
--------------------------------------------------------------------------------
 1 | 
 2 | #include "MyStruct.h"
 3 | long max(long left,long right)
 4 | {
 5 |     if(left > right)
 6 |     {
 7 | 	return left;
 8 |     }
 9 |     else
10 |     {
11 | 	return right;
12 |     }
13 | }
14 | 
15 | 
16 | long min(long left,long right)
17 | {
18 |     if(left < right)
19 |     {
20 | 	return left;
21 |     }
22 |     else
23 |     {
24 | 	return right;
25 |     }
26 | }
27 | 
28 | bool MRect::IntersectRect(MRect& source1,MRect& source2)
29 | {
30 |     long maxX = max(source1.left,source2.left); 
31 |     long maxY = max(source1.top,source2.top);
32 |     long minX = min(source1.right,source2.right);
33 |     long minY = min(source1.bottom,source2.bottom);
34 | 
35 |     if(maxX < minX && maxY < minY)
36 |     {
37 | 	this->top = maxY;
38 | 	this->left = maxX;
39 | 	this->bottom = minY;
40 | 	this->right = minX;
41 | 
42 | 	return 1;
43 |     }
44 |     else
45 |     {
46 | 	this->top = this->left = this->bottom = this->right = 0;
47 | 	return 0;
48 |     }
49 | }
50 | 
51 | void MRect::UnionRect(MRect& source1,MRect& source2)
52 | {
53 |     long minX = min(source1.left,source2.left); 
54 |     long minY = min(source1.top,source2.top);
55 |     long maxX = max(source1.right,source2.right);
56 |     long maxY = max(source1.bottom,source2.bottom);
57 | 
58 |     this->top = minY;
59 |     this->left = minX;
60 |     this->bottom = maxY;
61 |     this->right = maxX;
62 | }
63 | 


--------------------------------------------------------------------------------
/IntImage.h:
--------------------------------------------------------------------------------
 1 | #ifndef IMAGE_H
 2 | #define IMAGE_H
 3 | #define USE_DOUBLE
 4 | 
 5 | #ifdef USE_DOUBLE
 6 | 	typedef double REAL;
 7 | #else
 8 | 	typedef float REAL;
 9 | #endif
10 | #include <assert.h>
11 | #include <string>
12 | #include "MyStruct.h"
13 | #include "ocv.h"
14 | 
15 | 
16 | #define ASSERT(p) assert(p)
17 | class IntImage
18 | {
19 | public:
20 | 	IntImage();
21 | 	~IntImage();
22 | 
23 | 	void Clear(void); 
24 | 	void SetSize(const MSize size);
25 | 	IntImage& operator=(const IntImage& source);
26 | 	void CalcSquareAndIntegral(IntImage& square,IntImage& image) const;
27 | 	void CalculateVarianceAndIntegralImageInPlace(void);
28 | 	void Resize(IntImage &result,  REAL ratio) const;
29 | 	void Copy(const IntImage& source);
30 | 	void Load(const std::string& filename);
31 | 	void IplImageToIntImage(IplImage* img);
32 | 	void Save(const std::string& filename) const;
33 | 	IplImage* IntImageToIplImage() const;
34 | 
35 | public:
36 | 	int height; // height, or, number of rows of the image
37 | 	int width;  // width, or, number of columns of the image
38 | 	REAL** data;  // auxiliary pointers to accelerate the read/write of the image
39 | 	                // no memory is really allocated, use memory in (buf)
40 | 					// data[i][j] is a pixel's gray value in (i)th row and (j)th column
41 | 	REAL* buf;    // pointer to a block of continuous memory containing the image
42 | 	REAL variance;
43 | 	int label;
44 | };
45 | 
46 | void SwapIntImage(IntImage& i1,IntImage& i2);
47 | #endif
48 | 


--------------------------------------------------------------------------------
/AdaBoostClassifier.cpp:
--------------------------------------------------------------------------------
 1 | #include <fstream>
 2 | #include <vector>
 3 | #include <algorithm>
 4 | #include <math.h>
 5 | #include <float.h>
 6 | using namespace std;
 7 | 
 8 | #include "AdaBoostClassifier.h"
 9 | 
10 | //#include "CascadeClassifier.h"
11 | 
12 | 
13 | AdaBoostClassifier::AdaBoostClassifier():count(0),thresh(0.0),alphas(NULL),scs(NULL)
14 | {
15 | }
16 | 
17 | AdaBoostClassifier::~AdaBoostClassifier()
18 | {
19 | 	Clear();
20 | }
21 | 
22 | void AdaBoostClassifier::Clear()
23 | {
24 | 	delete[] scs; scs=NULL;
25 | 	delete[] alphas; alphas=NULL;
26 | 	count = 0;
27 | 	thresh = 0.0;
28 | }
29 | 
30 | AdaBoostClassifier& AdaBoostClassifier::operator=(const AdaBoostClassifier& source)
31 | {
32 | 	InitToGivenSize(source.count);
33 | 	count = source.count;
34 | 	thresh = source.thresh;
35 | 	memcpy(alphas,source.alphas,sizeof(*alphas)*count);
36 | 	for(int i=0;i<count;i++) scs[i] = source.scs[i];
37 | 	return *this;
38 | }
39 | 
40 | void AdaBoostClassifier::InitToGivenSize(const int size)
41 | {
42 | 	Clear();
43 | 	count = 0;
44 | 	thresh = 0.0;
45 | 	alphas = new REAL[size]; ASSERT(alphas!=NULL);
46 | 	scs = new SimpleClassifier[size]; ASSERT(scs!=NULL);
47 | }
48 | 
49 | void AdaBoostClassifier::WriteToFile(ofstream& f) const
50 | {
51 | 	f<<count<<endl;
52 | 	f<<thresh<<endl;
53 | 	for(int i=0;i<count;i++) f<<alphas[i]<<" ";
54 | 	f<<endl;
55 | 	for(int i=0;i<count;i++) scs[i].WriteToFile(f);
56 | 	f<<endl;
57 | }
58 | 
59 | void AdaBoostClassifier::ReadFromFile(ifstream& f)
60 | {
61 | 	Clear();
62 | 	f>>count; ASSERT(count>0);
63 | 	f.ignore(256,'\n');
64 | 	scs = new SimpleClassifier[count]; ASSERT(scs!=NULL);
65 | 	alphas = new REAL[count]; ASSERT(alphas!=NULL);
66 | 	
67 | 	f>>thresh; f.ignore(256,'\n');
68 | 	for(int i=0;i<count;i++) f>>alphas[i]; f.ignore(256,'\n');
69 | 	for(int i=0;i<count;i++) scs[i].ReadFromFile(f); f.ignore(256,'\n');
70 | }


--------------------------------------------------------------------------------
/SimpleClassifier.h:
--------------------------------------------------------------------------------
  1 | #ifndef SIM_H
  2 | #define SIM_H
  3 | #include "IntImage.h"
  4 | #include <fstream>
  5 | #include "MyStruct.h"
  6 | #include "ocv.h"
  7 | 
  8 | struct SimpleClassifier
  9 | {
 10 | 	REAL thresh;
 11 | 	REAL error;
 12 | 	int parity;
 13 | 	int type; // which type of feature?
 14 | 	int x1,x2,x3,x4,y1,y2,y3,y4;
 15 | 
 16 | 	inline const REAL GetOneFeature(const IntImage& im) const;
 17 | 	inline const REAL GetOneFeatureTranslation(REAL** const data,const int y) const;
 18 | 	inline const int Apply(const REAL value) const;
 19 | 	inline const int Apply(const IntImage& im) const;
 20 | 	void WriteToFile(std::ofstream& f) const;
 21 | 	void ReadFromFile(std::ifstream& f);
 22 | };
 23 | 
 24 | const int SimpleClassifier::Apply(const IntImage& im) const
 25 | {
 26 | 	if(parity == 1)
 27 | 		return (GetOneFeature(im)<thresh)?1:0;
 28 | 	else
 29 | 		return (GetOneFeature(im)>=thresh)?1:0;
 30 | }
 31 | 
 32 | const int SimpleClassifier::Apply(const REAL value) const
 33 | {
 34 | 	if(parity == 1)
 35 | 		return (value<thresh)?1:0;
 36 | 	else
 37 | 		return (value>=thresh)?1:0;
 38 | }
 39 | 
 40 | const REAL SimpleClassifier::GetOneFeature(const IntImage& im) const
 41 | {
 42 | 	REAL f1;
 43 | 	REAL** data = im.data;
 44 | 
 45 | 	switch(type)
 46 | 	{
 47 | 	case 0:
 48 | 		f1 =   data[x1][y3] - data[x1][y1] + data[x3][y3] - data[x3][y1]
 49 | 			 + 2*(data[x2][y1] - data[x2][y3]);
 50 | 		break;
 51 | 	case 1:
 52 | 		f1 =   data[x3][y1] + data[x3][y3] - data[x1][y1] - data[x1][y3]
 53 | 			 + 2*(data[x1][y2] - data[x3][y2]);
 54 | 		break;
 55 | 	case 2:
 56 | 		f1 =   data[x1][y1] -data[x1][y3] + data[x4][y3] - data[x4][y1]
 57 | 			 + 3*(data[x2][y3] - data[x2][y1] + data[x3][y1] - data[x3][y3]);
 58 | 		break;
 59 | 	case 3:
 60 | 		f1 =   data[x1][y1] - data[x1][y4] + data[x3][y4] - data[x3][y1]
 61 | 			 + 3*(data[x3][y2] - data[x3][y3] + data[x1][y3] - data[x1][y2] );
 62 | 		break;
 63 | 	case 4:
 64 | 		f1 =   data[x1][y1] + data[x1][y3] + data[x3][y1] + data[x3][y3]
 65 | 			 - 2*(data[x2][y1] + data[x2][y3] + data[x1][y2] + data[x3][y2])
 66 | 			 + 4*data[x2][y2];
 67 | 		break;
 68 | 	}
 69 | 	return f1/im.variance;
 70 | }
 71 | 
 72 | const REAL SimpleClassifier::GetOneFeatureTranslation(REAL** const data,const int y) const
 73 | {
 74 | 	REAL f1=0;
 75 | 
 76 | 	switch(type)
 77 | 	{
 78 | 	case 0:
 79 | 		f1 =   data[x1][y+y3] - data[x1][y+y1] + data[x3][y+y3] - data[x3][y+y1]
 80 | 			 + 2*(data[x2][y+y1] - data[x2][y+y3]);
 81 | 		break;
 82 | 	case 1:
 83 | 		f1 =   data[x3][y+y1] + data[x3][y+y3] - data[x1][y+y1] - data[x1][y+y3]
 84 | 			 + 2*(data[x1][y+y2] - data[x3][y+y2]);
 85 | 		break;
 86 | 	case 2:
 87 | 		f1 =   data[x1][y+y1] - data[x1][y+y3] + data[x4][y+y3] - data[x4][y+y1]
 88 | 			 + 3*(data[x2][y+y3] - data[x2][y+y1] + data[x3][y+y1]  - data[x3][y+y3]);
 89 | 		break;
 90 | 	case 3:
 91 | 		f1 =   data[x1][y+y1] - data[x1][y+y4] + data[x3][y+y4] - data[x3][y+y1]
 92 | 			 + 3*(data[x3][y+y2] - data[x3][y+y3] + data[x1][y+y3] - data[x1][y+y2]);
 93 | 		break;
 94 | 	case 4:
 95 | 		f1 =   data[x1][y+y1] + data[x1][y+y3] + data[x3][y+y1] + data[x3][y+y3]
 96 | 			 - 2*(data[x2][y+y1] + data[x2][y+y3] + data[x1][y+y2] + data[x3][y+y2])
 97 | 			 + 4*data[x2][y+y2];
 98 | 		break;
 99 | 	default:
100 | 		break;
101 | 	}
102 | 	return f1;
103 | }
104 | #endif
105 | 


--------------------------------------------------------------------------------
/main.cpp:
--------------------------------------------------------------------------------
  1 | #include <string>
  2 | #include <iostream>
  3 | #include <stdio.h>
  4 | #include <vector>
  5 | #include "IntImage.h"
  6 | #include "MyStruct.h"
  7 | #include "CascadeClassifier.h"
  8 | #include "ocv.h"
  9 | 
 10 | using namespace std;
 11 | 
 12 | float CamShift(IplImage* frame,const CvRect& rect,int resetCam);
 13 | void RotateImage(IplImage* frame,IplImage* imgRotate,float degree);
 14 | void MatrixRotate(int x,int y,float degree,int& rotatedX,int& rotatedY);
 15 | 
 16 | int main()
 17 | {
 18 | 	CascadeClassifier face;
 19 | 
 20 | 	string filename = "./data/cascade.txt";
 21 | 	string filenameRange = "./data/cascade.txt.range";
 22 | 
 23 | 	face.LoadDefaultCascade(filename,filenameRange);
 24 | 	cvNamedWindow("face",CV_WINDOW_AUTOSIZE);
 25 | 
 26 | 	IntImage img;
 27 | 
 28 | 	CvCapture* capture = cvCreateCameraCapture(0);
 29 | 	if(capture == NULL)
 30 | 	{
 31 | 		fprintf(stderr,"error capture is null!\n");
 32 | 		return -1;
 33 | 	}
 34 | 
 35 | 	IplImage* frame ;
 36 | 	vector<MRect> results;
 37 | 	CvRect detectedRect;
 38 | 	int detected = 0;
 39 | 	CvPoint** points = new CvPoint*[1];
 40 | 	points[0] = new CvPoint[4];
 41 | 
 42 | 	while(1)
 43 | 	{
 44 | 	    int resetCam = 0;
 45 | 	    frame = cvQueryFrame(capture);
 46 | 	    if(!frame)
 47 | 	    {
 48 | 		    break;
 49 | 	    }
 50 | 	     
 51 | 	    img.IplImageToIntImage(frame);
 52 | 	    face.ApplyOriginalSize(img,results);
 53 | 
 54 | 	    if(results.size() != 0)
 55 | 	    {
 56 | 		detected = 1;
 57 | 		for(int i = 0; i < results.size();i++)
 58 | 		{
 59 | 		    cvRectangle(frame,cvPoint(results[i].left,results[i].top),cvPoint(results[i].right,results[i].bottom),cvScalar(0x00,0x00,0xff),3);
 60 | 		}
 61 | 		printf("rect's num is %d,(%ld,%ld),(%ld,%ld)\n",results.size(),results[0].left,results[0].top,results[0].right,results[0].bottom);
 62 | 		detectedRect.x = results[0].left;
 63 | 		detectedRect.width = results[0].right - results[0].left;
 64 | 		detectedRect.y = results[0].top;
 65 | 		detectedRect.height = results[0].bottom - results[0].top;
 66 | 
 67 | 		resetCam = 1;
 68 | 	    }
 69 | 	    
 70 | 
 71 | 	    if(resetCam == 1)
 72 | 	    {
 73 | 		cout<<"reset Rect"<<endl;
 74 | 		CamShift(frame,detectedRect,resetCam);
 75 | 	    }
 76 | 	    else if(detected == 1 && resetCam == 0)
 77 | 	    {
 78 | 		cout<<"人脸跟踪"<<endl;
 79 | 		float degree = CamShift(frame,detectedRect,resetCam);
 80 | 
 81 | 		if(degree < 0)
 82 | 		{
 83 | 		    cout<<"Head to the right"<<endl;
 84 | 		    degree = fabs(degree) - 100;
 85 | 		    cout<<"Rdegress: "<<degree<<endl;
 86 | 		}
 87 | 		else
 88 | 		{
 89 | 		    cout<<"Head to the left"<<endl;
 90 | 		    degree = 100 - degree;
 91 | 		    cout<<"Ldegress: "<<degree<<endl;
 92 | 		}
 93 | 
 94 | 		IplImage* imgRotate = cvCreateImage(cvGetSize(frame),8,3);
 95 | 		RotateImage(frame,imgRotate,degree);
 96 | 		img.IplImageToIntImage(imgRotate);
 97 | 		face.ApplyOriginalSize(img,results);
 98 | 		cout<<"num:"<<results.size()<<endl;
 99 | 		if(results.size() != 0)
100 | 	    	{
101 | 	    	    for(int i = 0; i < results.size();i++)
102 | 	    	    {
103 | 	    	        cvRectangle(imgRotate,cvPoint(results[i].left,results[i].top),cvPoint(results[i].right,results[i].bottom),cvScalar(0xff,0x00,0x00),3);
104 | 	    	    }
105 | 	    	    printf("rect's num is %d,(%ld,%ld),(%ld,%ld)\n",results.size(),results[0].left,results[0].top,results[0].right,results[0].bottom);
106 | 	    	}
107 | 		
108 | #if 0	
109 | 		if(results.size() > 0)
110 | 		{
111 | 		   int left = results[0].left;
112 | 		   int right = results[0].right;
113 | 		   int top = results[0].top;
114 | 		   int bottom = results[0].bottom;
115 | 
116 | 		   cout<<"("<<left<<","<<top<<"),("<<right<<","<<bottom<<")"<<endl;
117 | 		   MatrixRotate(left,top,-degree,left,top);		
118 | 		   MatrixRotate(right,bottom,-degree,right,bottom);		
119 | 		    
120 | 		   cout<<"("<<left<<","<<top<<"),("<<right<<","<<bottom<<")"<<endl;
121 | 		   points[0][0] = cvPoint(left,top);
122 | 		   points[0][1] = cvPoint(right,top);
123 | 		   points[0][2] = cvPoint(left,bottom);
124 | 		   points[0][3] = cvPoint(right,bottom);
125 | 
126 | 		   cout<<"hello"<<endl;
127 | 		   int pointNum[1] = {1};
128 | 		   cvPolyLine(frame,points,pointNum,1,1,CV_RGB(0,0,0),3);
129 | 		}
130 | #endif
131 | 		cvCopy(imgRotate,frame);
132 | 	    }
133 | 	     
134 | 	    
135 | 	    cvShowImage("face",frame);
136 | 
137 | 	    char c = cvWaitKey(10);
138 | 	    if(c == 27)
139 | 	    {
140 | 		break;
141 | 	    }
142 | 	    
143 | #if 0
144 | 	    if(!detected)
145 | 	    {
146 | 		img.IplImageToIntImage(frame);
147 | 		face.ApplyOriginalSize(img,results);
148 | 		if(results.size() != 0)
149 | 		{
150 | 		    detected = 1;
151 | 		    for(int i = 0; i < results.size();i++)
152 | 		    {
153 | 			cvRectangle(frame,cvPoint(results[i].left,results[i].top),cvPoint(results[i].right,results[i].bottom),cvScalar(0x00,0x00,0xff),3);
154 | 		    }
155 | 		    printf("rect's num is %d,(%ld,%ld),(%ld,%ld)\n",results.size(),results[0].left,results[0].top,results[0].right,results[0].bottom);
156 | 		}
157 | 		cvShowImage("face",frame);
158 | 	    }
159 | 
160 | 	    if(detected)
161 | 	    {
162 | 		tmpImage = CamShift(frame,results[0]);
163 | 		cvShowImage("face",tmpImage);
164 | 	    }
165 | 
166 | 	    char c = cvWaitKey(10);
167 | 	    if(c == 27)
168 | 	    {
169 | 		break;
170 | 	    }
171 | #endif
172 | 	}	
173 | 	delete[] points[0];
174 | 	delete[] points;
175 | 	cvReleaseCapture(&capture);
176 | 	cvDestroyWindow("face");
177 | 	return 0;
178 | }
179 | 


--------------------------------------------------------------------------------
/MyCamshift.cpp:
--------------------------------------------------------------------------------
  1 | #if 0
  2 | #include "ocv.h"
  3 | #include "MyStruct.h"
  4 | #include <stdio.h>
  5 | 
  6 | IplImage *image = 0, *hsv = 0, *hue = 0, *mask = 0, *backproject = 0;
  7 | CvHistogram *hist = 0;
  8 | int i,c;
  9 | int vmin = 10, vmax = 256, smin = 30;
 10 | float hranges_arr[] = {0,180};
 11 | float* hranges = hranges_arr;
 12 | int hdims = 16;
 13 | CvRect selection;
 14 | CvRect track_window;
 15 | CvBox2D track_box;
 16 | CvConnectedComp track_comp;
 17 | int track_object = 1;
 18 | 
 19 | void CamShift(IplImage* frame,const MRect& rect,int resetCam)
 20 | {
 21 |     selection.x = rect.left;
 22 |     selection.y = rect.top;
 23 |     selection.width = rect.right - rect.left; 
 24 |     selection.height = rect.bottom - rect.top; 
 25 | 
 26 |     if(!hsv)
 27 |     {
 28 |         /* allocate all the buffers */
 29 |         //image = cvCreateImage( cvGetSize(frame), 8, 3 );
 30 |         //image->origin = frame->origin;
 31 |         hsv = cvCreateImage( cvGetSize(frame), 8, 3 );
 32 |         hue = cvCreateImage( cvGetSize(frame), 8, 1 );
 33 |         mask = cvCreateImage( cvGetSize(frame), 8, 1 );
 34 |         backproject = cvCreateImage( cvGetSize(frame), 8, 1 );
 35 |         hist = cvCreateHist( 1, &hdims, CV_HIST_ARRAY, &hranges, 1 );
 36 |     }
 37 | 
 38 |     //cvCopy(frame,image,0);
 39 |     cvCvtColor(frame,hsv,CV_BGR2HSV);
 40 | 
 41 |     int _vmin = vmin, _vmax = vmax;
 42 | 
 43 |     cvInRangeS(hsv, cvScalar(0,smin,MIN(_vmin,_vmax),0),
 44 |                         cvScalar(180,256,MAX(_vmin,_vmax),0), mask );
 45 |     cvSplit( hsv, hue, 0, 0, 0 );
 46 | 
 47 | 
 48 |     if(resetCam)
 49 |     {
 50 | 	float max_val = 0.f;
 51 | 	cvSetImageROI(hue, selection);
 52 |     	cvSetImageROI(mask, selection);
 53 |     	cvCalcHist(&hue, hist, 0, mask);
 54 |     	cvGetMinMaxHistValue(hist, 0, &max_val, 0, 0);
 55 |     	//cvConvertScale(hist->bins,hist->bins,max_val ? 255. / max_val : 0., 0 );
 56 |     	cvResetImageROI(hue);
 57 |     	cvResetImageROI(mask);
 58 |     	track_window = selection;
 59 |     }
 60 | 
 61 |     cvCalcBackProject(&hue, backproject, hist);
 62 |     cvAnd( backproject, mask, backproject, 0 );
 63 |     cvCamShift( backproject, track_window,
 64 |                 cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ),
 65 |                 &track_comp, &track_box );
 66 |     track_window = track_comp.rect;
 67 | 
 68 |     cvEllipseBox(frame, track_box, CV_RGB(255,0,0), 3, CV_AA, 0);
 69 |     //cvSaveImage("test.bmp",image);
 70 |     //printf("angle:%f\n",track_box.angle);    
 71 |     //cvRectangle(image,cvPoint(track_window.x,track_window.y),cvPoint(track_window.x + track_window.width,track_window.y +  track_window.height * 3.0 / 4),cvScalar(0x00,0x00,0xff),3);
 72 | }
 73 | #endif
 74 | 
 75 | 
 76 | #include "ocv.h"
 77 | #include "MyStruct.h"
 78 | #include <stdio.h>
 79 | 
 80 | IplImage *hsv = 0, *hue = 0, *mask = 0, *backproject = 0, *histimg = 0;
 81 | CvHistogram *hist = 0;
 82 | 
 83 | int backproject_mode = 0;
 84 | 
 85 | CvRect selection;
 86 | CvRect track_window;
 87 | CvBox2D track_box;
 88 | CvConnectedComp track_comp;
 89 | int hdims = 16;
 90 | float hranges_arr[] = {0,180};
 91 | float* hranges = hranges_arr;
 92 | int vmin = 10, vmax = 256, smin = 30;
 93 | 
 94 | CvScalar hsv2rgb( float hux )
 95 | {
 96 |     int rgb[3], p, sector;
 97 |     static const int sector_data[][3]=
 98 |         {{0,2,1}, {1,2,0}, {1,0,2}, {2,0,1}, {2,1,0}, {0,1,2}};
 99 |     hux *= 0.033333333333333333333333333333333f;
100 |     sector = cvFloor(hux);
101 |     p = cvRound(255*(hux - sector));
102 |     p ^= sector & 1 ? 255 : 0;
103 | 
104 |     rgb[sector_data[sector][0]] = 255;
105 |     rgb[sector_data[sector][1]] = 0;
106 |     rgb[sector_data[sector][2]] = p;
107 | 
108 |     return cvScalar(rgb[2], rgb[1], rgb[0],0);
109 | }
110 | 
111 | float CamShift(IplImage* frame,const CvRect& rect,int resetCam)
112 | {
113 |         int i, bin_w, c;
114 |         if(!hsv)
115 |         {
116 |             hsv = cvCreateImage( cvGetSize(frame), 8, 3 );
117 |             hue = cvCreateImage( cvGetSize(frame), 8, 1 );
118 |             mask = cvCreateImage( cvGetSize(frame), 8, 1 );
119 |             backproject = cvCreateImage( cvGetSize(frame), 8, 1 );
120 |             hist = cvCreateHist( 1, &hdims, CV_HIST_ARRAY, &hranges, 1 );
121 |             histimg = cvCreateImage( cvSize(320,200), 8, 3 );
122 |             cvZero( histimg );
123 |         }
124 | 
125 |         cvCvtColor(frame, hsv, CV_BGR2HSV );
126 | 
127 |         int _vmin = vmin, _vmax = vmax;
128 | 
129 |         cvInRangeS(hsv, cvScalar(0,smin,MIN(_vmin,_vmax),0),cvScalar(180,256,MAX(_vmin,_vmax),0), mask );
130 |         cvSplit(hsv, hue, 0, 0, 0 );
131 | 
132 |         if(resetCam == 1)
133 |         {
134 |             float max_val = 0.f;
135 |             cvSetImageROI(hue, rect);
136 |             cvSetImageROI(mask, rect);
137 |             cvCalcHist(&hue, hist, 0, mask );
138 | 	    cvGetMinMaxHistValue( hist, 0, &max_val, 0, 0 );
139 |             cvConvertScale( hist->bins, hist->bins, max_val ? 255. / max_val : 0., 0 );
140 |             cvResetImageROI( hue );
141 |             cvResetImageROI( mask );
142 |             track_window = rect;
143 |             cvZero( histimg );
144 |             bin_w = histimg->width / hdims;
145 |             for( i = 0; i < hdims; i++ )
146 |             {
147 |                 int val = cvRound( cvGetReal1D(hist->bins,i)*histimg->height/255 );
148 |                 CvScalar color = hsv2rgb(i*180.f/hdims);
149 |                 cvRectangle( histimg, cvPoint(i*bin_w,histimg->height),
150 |                                  cvPoint((i+1)*bin_w,histimg->height - val),
151 |                                  color, -1, 8, 0 );
152 |             }
153 |         }
154 | 
155 |         cvCalcBackProject(&hue, backproject, hist);
156 |         cvAnd(backproject, mask, backproject, 0 );
157 |         cvCamShift( backproject, track_window,cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ),&track_comp, &track_box );
158 |         track_window = track_comp.rect;
159 | 	//printf("track_window:(%d,%d,%d,%d)\n",track_window.x,track_window.y,track_window.width,track_window.height);	
160 | 
161 |         if(!frame->origin )
162 |                 track_box.angle = -track_box.angle;
163 |         cvEllipseBox(frame, track_box, CV_RGB(255,0,0), 3, CV_AA, 0 );
164 | 	
165 | 	//cvRectangle(image,cvPoint(track_window.x,track_window.y),cvPoint(track_window.x + track_window.width,track_window.y +  track_window.height),cvScalar(0x00,0x00,0xff),3);
166 | 
167 |         cvNamedWindow( "Histogram", 1 );
168 |         cvShowImage( "Histogram", histimg );
169 | 
170 | 	return track_box.angle;
171 | }
172 | 
173 | 
174 | 


--------------------------------------------------------------------------------
/CascadeClassifier.cpp:
--------------------------------------------------------------------------------
  1 | 
  2 | #include <fstream>
  3 | #include <vector>
  4 | #include <math.h>
  5 | #include <algorithm>
  6 | #include <string>
  7 | using namespace std;
  8 | #include "CascadeClassifier.h"
  9 | 
 10 | REAL mean_min,mean_max,sq_min,sq_max,var_min,var_max;
 11 | 
 12 | CascadeClassifier::CascadeClassifier():count(0),ac(NULL)
 13 | {
 14 | }
 15 | 
 16 | CascadeClassifier::~CascadeClassifier()
 17 | {
 18 | 	Clear();	
 19 | }
 20 | 
 21 | void CascadeClassifier::Clear()
 22 | {
 23 | 	count = 0;
 24 | 	delete[] ac; ac=NULL;
 25 | }
 26 | 
 27 | CascadeClassifier& CascadeClassifier::operator=(const CascadeClassifier& source)
 28 | {
 29 | 	Clear();
 30 | 	count = source.count;
 31 | 	int max_nodes = 50;
 32 | 	ac = new AdaBoostClassifier[max_nodes]; ASSERT(ac!=NULL);
 33 | 	for(int i=0;i<count;i++) ac[i] = source.ac[i];
 34 | 	return *this;
 35 | }
 36 | 
 37 | void CascadeClassifier::ReadFromFile(ifstream& f)
 38 | {
 39 | 	Clear();
 40 | 	f>>count; f.ignore(256,'\n');
 41 | 	int max_nodes = 50;
 42 | 	ac = new AdaBoostClassifier[max_nodes]; ASSERT(ac!=NULL);
 43 | 	for(int i=0;i<count;i++) ac[i].ReadFromFile(f);
 44 | }
 45 | 
 46 | void CascadeClassifier::WriteToFile(ofstream& f) const
 47 | {
 48 | 	f<<count<<endl;
 49 | 	for(int i=0;i<count;i++) ac[i].WriteToFile(f);
 50 | }
 51 | 
 52 | void CascadeClassifier::LoadDefaultCascade(string& cascade_filename,string& cascade_filename_range)
 53 | {
 54 | 	ifstream f;
 55 | 	ifstream frange;
 56 | 	f.open(cascade_filename.c_str());
 57 | 	frange.open(cascade_filename_range.c_str());
 58 | 	frange>>mean_min>>mean_max>>sq_min>>sq_max>>var_min>>var_max;
 59 | 	ReadFromFile(f);
 60 | 	f.close();
 61 | 	frange.close();
 62 | }
 63 | 
 64 | void CascadeClassifier::DrawResults(IntImage& image,const vector<MRect>& results) const
 65 | {
 66 | 	int i;
 67 | 	unsigned int k;
 68 | 	int x1,x2,y1,y2;
 69 | 
 70 | 	for(k=0;k<results.size();k++)
 71 | 	{
 72 | 		y1 = (results[k].top>=0)?results[k].top:0; 
 73 | 		y1 = (results[k].top<image.height)?results[k].top:(image.height-1);
 74 | 		y2 = (results[k].bottom>=0)?results[k].bottom:0;
 75 | 		y2 = (results[k].bottom<image.height)?results[k].bottom:(image.height-1);
 76 | 		x1 = (results[k].left>=0)?results[k].left:0;
 77 | 		x1 = (results[k].left<image.width)?results[k].left:(image.width-1);
 78 | 		x2 = (results[k].right>=0)?results[k].right:0;
 79 | 		x2 = (results[k].right<image.width)?results[k].right:(image.width-1);	
 80 | 		for(i=y1;i<=y2;i++) 
 81 | 		{
 82 | 			image.data[i][x1] = 255;
 83 | 			image.data[i][x2] = 255;
 84 | 		}
 85 | 		for(i=x1;i<=x2;i++)
 86 | 		{
 87 | 			image.data[y1][i] = 255;
 88 | 			image.data[y2][i] = 255;
 89 | 		}
 90 | 	}
 91 | }
 92 | 
 93 | void CascadeClassifier::ApplyOriginalSize(IntImage& original,vector<MRect>& results) 
 94 | {
 95 | 	IntImage procface;
 96 | 	IntImage image,square;
 97 | 	REAL sq,ex,value;
 98 | 	int result;
 99 | 	MRect rect;
100 | 	REAL ratio;
101 | 
102 | 	procface.Copy(original);
103 | 	ratio = 1.0;
104 | 	results.clear();
105 | 	REAL paddedsize = REAL(1)/REAL((sx+1)*(sy+1));
106 | 	while((procface.height>sx+1) && (procface.width>sy+1))
107 | 	{
108 | 		procface.CalcSquareAndIntegral(square,image);
109 | 		for(int i=0,size_x=image.height-sx;i<size_x;i+=1)
110 | 			for(int j=0,size_y=image.width-sy;j<size_y;j+=1)
111 | 			{
112 | 				ex = image.data[i+sx][j+sy]+image.data[i][j]-image.data[i+sx][j]-image.data[i][j+sy];
113 | 				if(ex<mean_min || ex>mean_max) continue;
114 | 				sq = square.data[i+sx][j+sy]+square.data[i][j]-square.data[i+sx][j]-square.data[i][j+sy];
115 | 				if(sq<sq_min) continue;
116 | 				ex *= paddedsize;
117 | 				ex = ex * ex;
118 | 				sq *= paddedsize;
119 | 				sq = sq - ex;
120 | 				ASSERT(sq>=0);
121 | 				if(sq>0) sq = sqrt(sq); else sq = 1.0;
122 | 				if(sq<var_min) continue;
123 | 				result = 1;
124 | 				for(int k=0;k<count;k++)
125 | 				{
126 | 					value = 0.0;
127 | 					for(int t=0,size=ac[k].count;t<size;t++)
128 | 					{
129 | 						REAL f1 = 0;
130 | 						REAL** p = image.data + i;
131 | 						SimpleClassifier& s = ac[k].scs[t];
132 | 
133 | 						switch(s.type)
134 | 						{
135 | 							case 0:
136 | 								f1 =   p[s.x1][j+s.y3] - p[s.x1][j+s.y1] + p[s.x3][j+s.y3] - p[s.x3][j+s.y1]
137 | 									+ REAL(2)*(p[s.x2][j+s.y1] - p[s.x2][j+s.y3]);
138 | 								break;
139 | 							case 1:
140 | 								f1 =   p[s.x3][j+s.y1] + p[s.x3][j+s.y3] - p[s.x1][j+s.y1] - p[s.x1][j+s.y3]
141 | 									+ REAL(2)*(p[s.x1][j+s.y2] - p[s.x3][j+s.y2]);
142 | 								break;
143 | 							case 2:
144 | 								f1 =   p[s.x1][j+s.y1] - p[s.x1][j+s.y3] + p[s.x4][j+s.y3] - p[s.x4][j+s.y1]
145 | 									+ REAL(3)*(p[s.x2][j+s.y3] - p[s.x2][j+s.y1] + p[s.x3][j+s.y1]  - p[s.x3][j+s.y3]);
146 | 								break;
147 | 							case 3:
148 | 								f1 =   p[s.x1][j+s.y1] - p[s.x1][j+s.y4] + p[s.x3][j+s.y4] - p[s.x3][j+s.y1]
149 | 									+ REAL(3)*(p[s.x3][j+s.y2] - p[s.x3][j+s.y3] + p[s.x1][j+s.y3] - p[s.x1][j+s.y2]);
150 | 								break;
151 | 							case 4:
152 | 								f1 =   p[s.x1][j+s.y1] + p[s.x1][j+s.y3] + p[s.x3][j+s.y1] + p[s.x3][j+s.y3]
153 | 									- REAL(2)*(p[s.x2][j+s.y1] + p[s.x2][j+s.y3] + p[s.x1][j+s.y2] + p[s.x3][j+s.y2])
154 | 									+ REAL(4)*p[s.x2][j+s.y2];
155 | 								break;
156 | 							default:
157 | 								;
158 | 						}
159 | 						if(s.parity!=0)
160 | 							if(f1<sq*s.thresh)
161 | 								value += ac[k].alphas[t];
162 | 							else ;
163 | 						else
164 | 							if(f1>=sq*s.thresh)
165 | 								value += ac[k].alphas[t];
166 | 							else ;
167 | 					}
168 | 					if(value<ac[k].thresh) 
169 | 					{
170 | 						result = 0;
171 | 						break;
172 | 					}
173 | 				}
174 | 				if(result!=0) 
175 | 				{
176 | 					const REAL r = 1.0/ratio;
177 | 					rect.left = (long)(j*r);rect.top = (long)(i*r);
178 | 					rect.right = (long)((j+sy)*r);rect.bottom = (long)((i+sx)*r);
179 | 					results.push_back(rect);
180 | 				}
181 | 			}
182 | 		ratio = ratio * REAL(0.8);
183 | 		procface.Resize(image,REAL(0.8));
184 | 		SwapIntImage(procface,image);
185 | 	}
186 | 
187 | 	//total_fp += results.size();
188 | 
189 | 	PostProcess(results,2);
190 | 	PostProcess(results,0);
191 | 	DrawResults(original,results);
192 | //	original.Save(filename+"_result.JPG");
193 | }
194 | 
195 | inline int SizeOfRect(const MRect& rect)
196 | {
197 | 	return rect.Height()*rect.Width();
198 | }
199 | 
200 | void PostProcess(vector<MRect>& result,const int combine_min)
201 | {
202 | 	vector<MRect> res1;
203 | 	vector<MRect> resmax;
204 | 	vector<int> res2;
205 | 	bool yet;
206 | 	MRect rectInter;
207 | 	
208 | 	for(unsigned int i=0,size_i=result.size();i<size_i;i++)
209 | 	{
210 | 		yet = false;
211 | 		MRect& result_i = result[i];
212 | 		for(unsigned int j=0,size_r=res1.size();j<size_r;j++)
213 | 		{
214 | 			MRect& resmax_j = resmax[j];
215 | 			if(rectInter.IntersectRect(result_i,resmax_j))
216 | 			{
217 | 				if(
218 | 					SizeOfRect(rectInter)>0.6*SizeOfRect(result_i) 
219 | 				 && SizeOfRect(rectInter)>0.6*SizeOfRect(resmax_j)
220 | 				  )
221 | 				{
222 | 					MRect& res1_j = res1[j];
223 | 					resmax_j.UnionRect(resmax_j,result_i);
224 | 					res1_j.bottom += result_i.bottom;
225 | 					res1_j.top += result_i.top;
226 | 					res1_j.left += result_i.left;
227 | 					res1_j.right += result_i.right;
228 | 					res2[j]++;
229 | 					yet = true;
230 | 					break;
231 | 				}
232 | 			}
233 | 		}
234 | 		if(yet==false)
235 | 		{
236 | 			res1.push_back(result_i);
237 | 			resmax.push_back(result_i);
238 | 			res2.push_back(1);
239 | 		}
240 | 	}
241 | 
242 | 	for(unsigned int i=0,size=res1.size();i<size;i++)
243 | 	{
244 | 		const int count = res2[i];
245 | 		MRect& res1_i = res1[i];
246 | 		res1_i.top /= count;
247 | 		res1_i.bottom /= count;
248 | 		res1_i.left /= count;
249 | 		res1_i.right /= count;
250 | 	}
251 | 
252 | 	result.clear();
253 | 	for(unsigned int i=0,size=res1.size();i<size;i++) 
254 | 		if(res2[i]>combine_min)
255 | 			result.push_back(res1[i]);
256 | }
257 | 


--------------------------------------------------------------------------------
/IntImage.cpp:
--------------------------------------------------------------------------------
  1 | #include <stdio.h>
  2 | #include <algorithm>
  3 | #include "IntImage.h"
  4 | using namespace std;
  5 | 
  6 | 
  7 | IntImage::IntImage():height(0),width(0),data(NULL),buf(NULL),variance(0.0),label(-1)
  8 | {
  9 | }
 10 | 
 11 | IntImage::~IntImage()
 12 | {
 13 |     Clear();
 14 | }
 15 | 
 16 | void IntImage::Clear(void)
 17 | {
 18 |     if(data == NULL)
 19 |         ASSERT(buf == NULL);
 20 |     else
 21 |     {
 22 |         ASSERT(buf != NULL);
 23 |         for(int i=0; i<height; i++)	data[i] = NULL;
 24 |         delete[] data;
 25 |         data = NULL;
 26 |         delete[] buf;
 27 |         buf = NULL;
 28 |         height = width = 0;
 29 |         variance = 0.0;
 30 |         label = -1;
 31 |     }
 32 | }
 33 | 
 34 | void IntImage::Copy(const IntImage& source)
 35 | // the ONLY way to make a copy of 'source' to this image
 36 | {
 37 |     ASSERT(source.height > 0);
 38 |     ASSERT(source.width > 0);
 39 |     if(&source == this)	return;
 40 |     SetSize(MSize(source.height,source.width));
 41 |     memcpy(buf,source.buf,sizeof(REAL)*height*width);
 42 | }
 43 | 
 44 | void IntImage::Load(const string& filename)
 45 | {
 46 |     IplImage* img;
 47 | 
 48 |     img = cvLoadImage(filename.c_str(),0);
 49 |     SetSize(MSize(img->height,img->width));
 50 |     for(int i=0,ih=img->height,iw=img->width; i<ih; i++)
 51 |     {
 52 |         REAL* pdata = data[i];
 53 |         unsigned char* pimg = reinterpret_cast<unsigned char*>(img->imageData+img->widthStep*i);
 54 |         for(int j=0; j<iw; j++) pdata[j] = pimg[j];
 55 |     }
 56 |     cvReleaseImage(&img);
 57 | }
 58 | 
 59 | void IntImage::IplImageToIntImage(IplImage* img)
 60 | {
 61 |     IplImage* changedImage = cvCreateImage(cvSize(img->width,img->height),IPL_DEPTH_8U,1);
 62 |     switch(img->nChannels)
 63 |     {
 64 | 	case 1:
 65 |     	    break;
 66 |     	case 2:
 67 |     	{
 68 |     	    cvCvtColor(img,changedImage,CV_BGR5652GRAY);
 69 |     	    break;
 70 |     	}
 71 |     	case 3:
 72 |     	{
 73 |     	    cvCvtColor(img,changedImage,CV_BGR2GRAY);
 74 |     	    break;
 75 |     	}
 76 |     	case 4:
 77 |     	{
 78 |     	    cvCvtColor(img,changedImage,CV_BGRA2GRAY);
 79 |     	    break;
 80 |     	}
 81 |     }
 82 | 
 83 |     SetSize(MSize(img->height,img->width));
 84 |     for(int i=0,ih=img->height,iw=img->width; i<ih; i++)
 85 |     {
 86 |         REAL* pdata = data[i];
 87 |         unsigned char* pimg = reinterpret_cast<unsigned char*>(changedImage->imageData+changedImage->widthStep*i);
 88 |         for(int j=0; j<iw; j++) pdata[j] = pimg[j];
 89 |     }
 90 |     cvReleaseImage(&changedImage);
 91 | }
 92 | 
 93 | void IntImage::Save(const string& filename) const
 94 | {
 95 |     IplImage* img;
 96 | 
 97 |     img = cvCreateImage(cvSize(width,height),IPL_DEPTH_8U,1);
 98 |     for(int i=0,ih=img->height,iw=img->width; i<ih; i++)
 99 |     {
100 |         REAL* pdata = data[i];
101 |         unsigned char* pimg = reinterpret_cast<unsigned char*>(img->imageData+img->widthStep*i);
102 |         for(int j=0; j<iw; j++) pimg[j] = (unsigned char)pdata[j];
103 |     }
104 |     cvSaveImage(filename.c_str(),img);
105 |     cvReleaseImage(&img);
106 | }
107 | 
108 | IplImage* IntImage::IntImageToIplImage() const
109 | {
110 |     IplImage* img;
111 |     img = cvCreateImage(cvSize(width,height),IPL_DEPTH_8U,1);
112 |     for(int i=0,ih=img->height,iw=img->width; i<ih; i++)
113 |     {
114 |         REAL* pdata = data[i];
115 |         unsigned char* pimg = reinterpret_cast<unsigned char*>(img->imageData+img->widthStep*i);
116 |         for(int j=0; j<iw; j++) pimg[j] = (unsigned char)pdata[j];
117 |     }
118 |     return img;
119 | }
120 | 
121 | void IntImage::SetSize(const MSize size)
122 | // 'size' is the new size of the image, if necessary, memory is reallocated
123 | // size.cx is the new height and size.cy is the new width
124 | {
125 |     if((size.cx == height) && (size.cy == width) && (buf != NULL) && (data != NULL) ) return;
126 |     ASSERT(size.cx >= 0);
127 |     ASSERT(size.cy >= 0);
128 |     Clear();
129 | 
130 |     height = size.cx;
131 |     width = size.cy;
132 | 
133 |     buf = new REAL[height*width];
134 |     ASSERT(buf != NULL);
135 |     data = new REAL*[height];
136 |     ASSERT(data != NULL);
137 |     for(int i=0; i<height; i++)	data[i] = &buf[i*width];
138 | }
139 | 
140 | IntImage& IntImage::operator=(const IntImage& source)
141 | {
142 |     SetSize(MSize(source.height,source.width));
143 |     memcpy(buf,source.buf,sizeof(*buf)*height*width);
144 |     label = source.label;
145 |     variance = source.variance;
146 | 
147 |     return *this;
148 | }
149 | 
150 | void IntImage::Resize(IntImage &result, REAL ratio) const
151 | {
152 |     result.SetSize(MSize(int(height*ratio),int(width*ratio)));
153 |     ratio = 1/ratio;
154 |     for(int i=0,rh=result.height,rw=result.width; i<rh; i++)
155 |         for(int j=0; j<rw; j++)
156 |         {
157 |             int x0,y0;
158 |             REAL x,y,fx0,fx1;
159 |             x = j*ratio;
160 |             y = i*ratio;
161 |             x0 = (int)(x);
162 |             y0 = (int)(y);
163 | 
164 |             //by Jianxin Wu
165 |             //1. The conversion of float to int in C is towards to 0 point, i.e. the floor function for positive numbers, and ceiling function for negative numbers.
166 |             //2. We only make use of ratio<1 in this applicaiton, and all numbers involved are positive.
167 |             //Using these, we have 0<=x<=height-1 and 0<=y<=width-1. Thus, boundary conditions check is not necessary.
168 |             //In languages other than C/C++ or ratio>=1, take care.
169 |             if (x0 == width-1) x0--;
170 |             if (y0 == height-1) y0--;
171 | 
172 |             x = x - x0;
173 |             y = y - y0;
174 | 
175 |             fx0 = data[y0][x0] + x*(data[y0][x0+1]-data[y0][x0]);
176 |             fx1 = data[y0+1][x0] + x*(data[y0+1][x0+1]-data[y0+1][x0]);
177 | 
178 |             result.data[i][j] = fx0 + y*(fx1-fx0);
179 |         }
180 | }
181 | 
182 | void IntImage::CalculateVarianceAndIntegralImageInPlace(void)
183 | // We pad a zero column and a zero row, so 24*24 image will be 25*25 in size
184 | {
185 |     REAL partialsum;
186 |     REAL ex,ex2;
187 |     REAL size,var;
188 | 
189 |     ex = 0;
190 |     ex2 = 0;
191 |     for(int i=0,size=height*width; i<size; i++)
192 |     {
193 |         ex += buf[i];
194 |         ex2 += (buf[i]*buf[i]);
195 |     }
196 |     size = REAL(height*width);
197 |     var = ex2/size - (ex/size)*(ex/size);
198 |     ASSERT(var >= 0);
199 |     if(var>0)
200 |         variance = sqrt(var);
201 |     else
202 |         variance = 1.0;
203 | 
204 | 
205 |     for(int i=1; i<width; i++)
206 |     {
207 |         data[0][i] = data[0][i-1] + data[0][i];
208 |     }
209 |     for(int i=1; i<height; i++)
210 |     {
211 |         partialsum = 0;
212 |         for(int j=0; j<width; j++)
213 |         {
214 |             partialsum += data[i][j];
215 |             data[i][j] = data[i-1][j] + partialsum;
216 |         }
217 |     }
218 | }
219 | 
220 | void IntImage::CalcSquareAndIntegral(IntImage& square, IntImage& image) const
221 | {
222 |     REAL partialsum,partialsum2;
223 | 
224 |     square.SetSize(MSize(height+1,width+1));
225 |     image.SetSize(MSize(height+1,width+1));
226 | 
227 |     for(int i=0; i<=width+1; i++) square.buf[i]=image.buf[i]=0;
228 |     for(int i=1; i<=height; i++)
229 |     {
230 |         partialsum = partialsum2 = 0;
231 |         square.data[i][0] = 0;
232 |         image.data[i][0] = 0;
233 |         for(int j=1; j<=width; j++)
234 |         {
235 |             partialsum += (data[i-1][j-1]*data[i-1][j-1]);
236 |             partialsum2 += data[i-1][j-1];
237 |             square.data[i][j] = square.data[i-1][j] + partialsum;
238 |             image.data[i][j] = image.data[i-1][j] + partialsum2;
239 |         }
240 |     }
241 | }
242 | 
243 | void SwapIntImage(IntImage& i1,IntImage& i2)
244 | {
245 |     std::swap(i1.height,i2.height);
246 |     std::swap(i1.width,i2.width);
247 |     std::swap(i1.buf,i2.buf);
248 |     std::swap(i1.data,i2.data);
249 |     std::swap(i1.variance,i2.variance);
250 |     std::swap(i1.label,i2.label);
251 | }
252 | 


--------------------------------------------------------------------------------
/data/cascade.txt:
--------------------------------------------------------------------------------
  1 | 12
  2 | 7
  3 | 1.49525
  4 | 0.716859 0.611201 0.541917 0.510268 0.490544 0.462789 0.555611 
  5 | -0.476127 1 1 23 -1 24 -1 17 20 23 -1 
  6 | 2.7167 0 4 5 9 13 -1 0 3 6 -1 
  7 | -37.1614 1 3 3 -1 10 -1 7 11 15 19 
  8 | -0.511015 1 1 0 -1 1 -1 16 19 22 -1 
  9 | 2.25347 0 4 20 22 24 -1 3 6 9 -1 
 10 | 2.15467 0 0 0 7 14 -1 0 -1 1 -1 
 11 | -22.7724 1 0 9 15 21 -1 11 -1 13 -1 
 12 | 
 13 | 15
 14 | 3.095
 15 | 1.14242 0.792674 0.691926 0.605297 0.601735 0.521567 0.527394 0.505073 0.49907 0.459109 0.559147 0.580994 0.43217 0.480875 0.486123 
 16 | -39.3655 1 2 3 9 15 21 16 -1 23 -1 
 17 | -18.1351 1 3 1 -1 14 -1 9 11 13 15 
 18 | -41.3307 1 0 0 3 6 -1 7 -1 21 -1 
 19 | 1.255 0 1 0 -1 5 -1 6 8 10 -1 
 20 | 0.785691 0 1 22 -1 23 -1 0 3 6 -1 
 21 | 1.19344 0 0 6 7 8 -1 2 -1 6 -1 
 22 | -2.49354 1 3 0 -1 22 -1 18 20 22 24 
 23 | 3.34934 0 1 0 -1 3 -1 0 3 6 -1 
 24 | 0.179026 0 1 15 -1 16 -1 14 16 18 -1 
 25 | 0 0 0 9 10 11 -1 11 -1 13 -1 
 26 | -2.0945 1 1 21 -1 23 -1 0 1 2 -1 
 27 | -1.25891 1 1 9 -1 16 -1 3 6 9 -1 
 28 | -0.0573044 1 0 12 13 14 -1 7 -1 11 -1 
 29 | -24.5845 1 0 13 16 19 -1 8 -1 15 -1 
 30 | -0.0266904 1 1 11 -1 12 -1 13 14 15 -1 
 31 | 
 32 | 30
 33 | 5.84944
 34 | 1.0838 0.852051 0.627409 0.528806 0.546801 0.509162 0.501287 0.570873 0.548523 0.474681 0.559069 0.457394 0.496085 0.457078 0.466796 0.542106 0.464617 0.411842 0.417023 0.531267 0.422077 0.423033 0.410993 0.417241 0.497113 0.41556 0.494026 0.414514 0.526819 0.401588 
 35 | 41.0919 0 2 1 4 7 10 0 -1 21 -1 
 36 | -30.8134 1 3 0 -1 14 -1 8 11 14 17 
 37 | 30.5444 0 4 0 8 16 -1 12 17 22 -1 
 38 | 0.337045 0 1 11 -1 15 -1 1 2 3 -1 
 39 | -4.61118 1 2 0 1 2 3 0 -1 21 -1 
 40 | 0.276982 0 0 0 3 6 -1 0 -1 1 -1 
 41 | 0 0 0 9 10 11 -1 0 -1 1 -1 
 42 | -6.18059 1 0 0 1 2 -1 6 -1 18 -1 
 43 | -0.0852404 1 2 10 11 12 13 11 -1 23 -1 
 44 | 24.9599 0 0 0 4 8 -1 0 -1 21 -1 
 45 | 0 1 0 14 15 16 -1 20 -1 21 -1 
 46 | 1.10601 0 3 6 -1 17 -1 8 9 10 11 
 47 | 2.51321 0 1 23 -1 24 -1 0 5 10 -1 
 48 | 0 0 1 4 -1 5 -1 20 21 22 -1 
 49 | 119.053 0 2 0 4 8 12 6 -1 18 -1 
 50 | -0.0254071 1 3 0 -1 5 -1 10 11 12 13 
 51 | 0.344633 0 1 18 -1 22 -1 17 18 19 -1 
 52 | -2.37588 1 2 10 12 14 16 8 -1 15 -1 
 53 | 65.5175 0 1 7 -1 23 -1 4 13 22 -1 
 54 | -0.19671 1 1 7 -1 9 -1 12 13 14 -1 
 55 | -2.02884 1 0 16 18 20 -1 15 -1 21 -1 
 56 | 0 1 0 12 13 14 -1 20 -1 21 -1 
 57 | -0.0957553 1 1 22 -1 23 -1 21 22 23 -1 
 58 | -70.6412 1 1 6 -1 23 -1 0 11 22 -1 
 59 | 0.0767329 1 3 10 -1 16 -1 20 21 22 23 
 60 | -25.2238 1 2 2 6 10 14 16 -1 23 -1 
 61 | 0.894963 1 3 0 -1 5 -1 8 9 10 11 
 62 | 14.2519 0 0 6 15 24 -1 0 -1 1 -1 
 63 | 0.335199 1 2 9 10 11 12 7 -1 11 -1 
 64 | -0.602465 1 3 0 -1 2 -1 18 20 22 24 
 65 | 
 66 | 30
 67 | 6.23521
 68 | 0.980876 0.838809 0.722299 0.662937 0.534916 0.526418 0.606632 0.493153 0.489254 0.489449 0.610735 0.472891 0.475425 0.489731 0.524369 0.573863 0.444844 0.484885 0.524751 0.51049 0.42348 0.536803 0.525153 0.440759 0.467877 0.443876 0.446806 0.424305 0.460255 0.487942 
 69 | -29.5672 1 3 0 -1 9 -1 6 10 14 18 
 70 | -7.50465 1 0 2 3 4 -1 0 -1 21 -1 
 71 | 0 0 1 10 -1 11 -1 0 1 2 -1 
 72 | 2.14081 0 0 6 7 8 -1 16 -1 23 -1 
 73 | 10.4553 0 1 0 -1 2 -1 0 7 14 -1 
 74 | -10.1483 1 0 12 14 16 -1 8 -1 15 -1 
 75 | -1.00471 1 1 11 -1 14 -1 2 6 10 -1 
 76 | -1.9124 1 4 20 22 24 -1 15 18 21 -1 
 77 | -2.08895 1 0 13 17 21 -1 6 -1 8 -1 
 78 | -5.5409 1 1 16 -1 23 -1 0 1 2 -1 
 79 | 0 0 0 8 9 10 -1 0 -1 1 -1 
 80 | -0.396832 1 1 8 -1 12 -1 7 8 9 -1 
 81 | 0.115618 0 0 0 1 2 -1 0 -1 1 -1 
 82 | 0 0 0 8 9 10 -1 9 -1 10 -1 
 83 | -173.891 1 1 2 -1 23 -1 1 12 23 -1 
 84 | 0.65156 0 1 11 -1 14 -1 15 18 21 -1 
 85 | 0.208781 0 4 0 3 6 -1 21 22 23 -1 
 86 | 61.8353 0 1 10 -1 23 -1 4 13 22 -1 
 87 | -0.988665 0 0 5 9 13 -1 11 -1 13 -1 
 88 | 0.495513 0 1 20 -1 23 -1 1 2 3 -1 
 89 | 0.52997 1 2 7 8 9 10 8 -1 15 -1 
 90 | 5.53283 0 0 18 19 20 -1 6 -1 18 -1 
 91 | 0 1 0 14 15 16 -1 4 -1 5 -1 
 92 | -1.84906 1 2 17 18 19 20 6 -1 18 -1 
 93 | 0.220224 0 3 7 -1 14 -1 13 14 15 16 
 94 | 11.5152 0 2 16 18 20 22 6 -1 18 -1 
 95 | 0 1 0 22 23 24 -1 0 -1 1 -1 
 96 | -0.855639 0 2 7 8 9 10 10 -1 16 -1 
 97 | -104.109 1 0 0 4 8 -1 0 -1 21 -1 
 98 | -0.89601 0 2 6 7 8 9 10 -1 16 -1 
 99 | 
100 | 50
101 | 9.57097
102 | 1.03743 0.75517 0.625919 0.602472 0.524701 0.578895 0.518272 0.511817 0.488142 0.455629 0.539198 0.592351 0.476754 0.500618 0.455755 0.463239 0.494794 0.512853 0.489522 0.48305 0.434861 0.571466 0.421003 0.506724 0.452305 0.507275 0.419503 0.439205 0.437469 0.460826 0.407081 0.538887 0.410228 0.409562 0.426301 0.442916 0.414881 0.369688 0.383423 0.392576 0.450149 0.429396 0.400542 0.385871 0.414131 0.381844 0.439508 0.428256 0.464437 0.39741 
103 | 49.1149 0 0 4 8 12 -1 0 -1 21 -1 
104 | -1.71662 1 3 4 -1 12 -1 11 12 13 14 
105 | 0.723904 0 1 0 -1 3 -1 1 2 3 -1 
106 | 9.65294 0 1 0 -1 2 -1 0 7 14 -1 
107 | -3.09959 1 0 2 3 4 -1 16 -1 23 -1 
108 | -0.612108 1 3 6 -1 12 -1 10 11 12 13 
109 | 0.631603 0 0 5 6 7 -1 18 -1 20 -1 
110 | -0.176042 1 3 19 -1 21 -1 9 11 13 15 
111 | 26.0266 0 0 5 9 13 -1 16 -1 23 -1 
112 | 0.139068 0 1 2 -1 4 -1 9 10 11 -1 
113 | -176.136 1 1 0 -1 23 -1 1 12 23 -1 
114 | 0 0 1 12 -1 13 -1 1 2 3 -1 
115 | 3.70569 0 2 18 19 20 21 6 -1 18 -1 
116 | -3.68682 1 2 9 11 13 15 4 -1 15 -1 
117 | -3.93517 1 0 12 18 24 -1 0 -1 1 -1 
118 | 0.461223 0 1 10 -1 12 -1 15 18 21 -1 
119 | 58.6491 0 1 1 -1 24 -1 7 12 17 -1 
120 | 0.229344 1 2 7 8 9 10 9 -1 10 -1 
121 | 7.29451 0 2 14 16 18 20 10 -1 16 -1 
122 | -0.45581 1 4 21 22 23 -1 14 18 22 -1 
123 | 3.9695 0 0 13 15 17 -1 10 -1 16 -1 
124 | -0.995272 0 2 7 8 9 10 8 -1 15 -1 
125 | -1.37066 1 2 3 4 5 6 16 -1 23 -1 
126 | 0.346885 1 2 8 9 10 11 7 -1 11 -1 
127 | 7.08503 0 2 17 18 19 20 6 -1 18 -1 
128 | -2.19141 0 2 8 9 10 11 5 -1 16 -1 
129 | -1.14883 1 2 17 18 19 20 10 -1 16 -1 
130 | 0 1 0 14 15 16 -1 0 -1 1 -1 
131 | 2.3735 0 2 17 18 19 20 8 -1 15 -1 
132 | -0.0865088 1 1 0 -1 5 -1 15 16 17 -1 
133 | -11.2174 1 1 20 -1 23 -1 0 3 6 -1 
134 | -0.891049 0 3 18 -1 22 -1 11 12 13 14 
135 | -2.03264 1 2 1 2 3 4 1 -1 8 -1 
136 | -0.331916 1 3 13 -1 16 -1 18 20 22 24 
137 | 2.89446 0 2 1 2 3 4 2 -1 16 -1 
138 | 0.534142 1 4 18 21 24 -1 11 12 13 -1 
139 | 0.165529 0 1 0 -1 1 -1 0 1 2 -1 
140 | 0 1 0 12 13 14 -1 0 -1 1 -1 
141 | -1.17609 1 4 0 2 4 -1 3 6 9 -1 
142 | 19.7205 0 0 0 4 8 -1 0 -1 21 -1 
143 | 0.166715 1 2 14 15 16 17 0 -1 1 -1 
144 | -2.62091 1 2 0 1 2 3 1 -1 8 -1 
145 | 0.27402 0 1 10 -1 14 -1 9 10 11 -1 
146 | -0.163263 1 2 2 3 4 5 5 -1 6 -1 
147 | -0.0849459 1 1 3 -1 4 -1 13 14 15 -1 
148 | 2.45574 0 0 0 1 2 -1 16 -1 23 -1 
149 | -0.718668 0 4 8 9 10 -1 9 12 15 -1 
150 | -4.97052 1 1 12 -1 23 -1 1 2 3 -1 
151 | 0.0268839 0 0 8 9 10 -1 20 -1 21 -1 
152 | -0.476198 1 3 11 -1 19 -1 1 2 3 4 
153 | 
154 | 50
155 | 9.95788
156 | 0.870915 0.712598 0.62074 0.519939 0.521166 0.520748 0.629626 0.53419 0.51321 0.594843 0.47984 0.559568 0.576 0.449704 0.475909 0.434287 0.558501 0.518993 0.437263 0.435915 0.438284 0.426288 0.429024 0.438977 0.426229 0.510603 0.401346 0.488421 0.381635 0.419014 0.427554 0.46558 0.489837 0.444901 0.450848 0.465151 0.452758 0.447424 0.427016 0.424526 0.39222 0.45798 0.466561 0.458045 0.493229 0.39846 0.390829 0.441644 0.380402 0.422936 
157 | 26.8316 0 2 0 3 6 9 7 -1 21 -1 
158 | -1.74749 1 1 0 -1 10 -1 13 14 15 -1 
159 | 7.94104 0 0 6 8 10 -1 1 -1 8 -1 
160 | 12.6534 0 2 17 19 21 23 6 -1 18 -1 
161 | 0 0 0 1 2 3 -1 0 -1 1 -1 
162 | 132.551 0 1 0 -1 23 -1 2 12 22 -1 
163 | -5.29098 1 3 7 -1 22 -1 9 11 13 15 
164 | 8.55974 0 4 5 9 13 -1 12 17 22 -1 
165 | 121.375 0 2 1 5 9 13 0 -1 21 -1 
166 | 0 0 1 14 -1 15 -1 0 1 2 -1 
167 | 0 0 0 6 7 8 -1 9 -1 10 -1 
168 | 10.1712 0 0 8 16 24 -1 0 -1 1 -1 
169 | -0.0863557 1 0 12 13 14 -1 13 -1 20 -1 
170 | 0.911399 0 3 19 -1 22 -1 5 7 9 11 
171 | -1.79618 1 0 14 19 24 -1 0 -1 1 -1 
172 | -0.839507 0 4 7 8 9 -1 4 13 22 -1 
173 | -11.4329 1 0 0 1 2 -1 0 -1 21 -1 
174 | -0.319914 1 0 14 16 18 -1 18 -1 20 -1 
175 | 1.96056 0 4 11 14 17 -1 11 14 17 -1 
176 | 0 0 3 14 -1 15 -1 0 1 2 3 
177 | 0.956429 0 1 0 -1 8 -1 1 2 3 -1 
178 | 1.46486 0 1 3 -1 6 -1 5 8 11 -1 
179 | 2.55085 0 2 3 4 5 6 16 -1 23 -1 
180 | -0.323783 1 2 10 11 12 13 2 -1 16 -1 
181 | 8.60563 0 0 0 2 4 -1 1 -1 8 -1 
182 | -0.137492 0 2 15 16 17 18 0 -1 1 -1 
183 | -9.78859 1 0 14 16 18 -1 10 -1 16 -1 
184 | -0.151184 1 1 10 -1 12 -1 1 6 11 -1 
185 | 0 0 1 16 -1 17 -1 15 16 17 -1 
186 | -2.88987 1 2 0 1 2 3 16 -1 23 -1 
187 | 0.37851 1 2 9 10 11 12 6 -1 18 -1 
188 | 2.17228 0 0 2 3 4 -1 16 -1 23 -1 
189 | -1.20721 0 2 7 9 11 13 0 -1 1 -1 
190 | 3.50014 0 2 17 18 19 20 6 -1 18 -1 
191 | 0.127488 1 2 8 9 10 11 0 -1 1 -1 
192 | 9.0971 0 2 13 15 17 19 10 -1 16 -1 
193 | -0.755048 0 2 13 14 15 16 1 -1 8 -1 
194 | 0.34943 0 0 4 5 6 -1 4 -1 5 -1 
195 | 0.381436 1 4 9 10 11 -1 6 12 18 -1 
196 | -4.56311 1 3 16 -1 24 -1 18 20 22 24 
197 | 0.940836 1 3 15 -1 24 -1 13 14 15 16 
198 | -123.219 1 1 0 -1 23 -1 1 12 23 -1 
199 | 0.616647 1 2 8 9 10 11 7 -1 11 -1 
200 | 130.295 0 2 1 6 11 16 0 -1 21 -1 
201 | 0 0 1 2 -1 4 -1 9 10 11 -1 
202 | -0.421945 1 1 0 -1 3 -1 21 22 23 -1 
203 | 7.53758 0 0 4 6 8 -1 16 -1 23 -1 
204 | 0 1 3 12 -1 16 -1 20 21 22 23 
205 | 0.897182 0 1 4 -1 22 -1 21 22 23 -1 
206 | 0.584389 1 3 0 -1 4 -1 13 14 15 16 
207 | 
208 | 50
209 | 9.66727
210 | 0.835861 0.645112 0.650024 0.546711 0.564288 0.497329 0.516814 0.507643 0.470219 0.437719 0.525847 0.502931 0.427437 0.430353 0.522228 0.50187 0.445043 0.500491 0.507047 0.556275 0.457654 0.440852 0.483661 0.512272 0.42278 0.488306 0.413365 0.506911 0.407426 0.411204 0.441402 0.532538 0.384194 0.408673 0.415507 0.429334 0.517578 0.379272 0.390837 0.397494 0.398964 0.472385 0.489387 0.410389 0.421406 0.397383 0.472957 0.407524 0.500031 0.391129 
211 | 1.92163 0 0 7 8 9 -1 0 -1 11 -1 
212 | 13.7861 0 2 0 4 8 12 18 -1 20 -1 
213 | -1.15481 1 3 2 -1 8 -1 11 12 13 14 
214 | -2.69451 1 2 0 1 2 3 1 -1 8 -1 
215 | -19.349 1 3 0 -1 3 -1 0 7 14 21 
216 | 0.267438 0 3 7 -1 10 -1 8 9 10 11 
217 | -1.50723 1 0 3 4 5 -1 2 -1 6 -1 
218 | 0.0274809 0 1 12 -1 13 -1 17 18 19 -1 
219 | -1.31906 1 3 18 -1 21 -1 18 20 22 24 
220 | -0.543511 1 2 11 12 13 14 1 -1 18 -1 
221 | 0.959427 0 0 4 5 6 -1 18 -1 20 -1 
222 | 1.15161 0 0 6 7 8 -1 6 -1 18 -1 
223 | -6.0027 1 1 12 -1 22 -1 3 6 9 -1 
224 | 0 0 1 23 -1 24 -1 5 6 7 -1 
225 | -4.37009 1 0 18 19 20 -1 6 -1 18 -1 
226 | 0 1 0 15 16 17 -1 0 -1 1 -1 
227 | 2.53332 0 0 19 20 21 -1 6 -1 18 -1 
228 | -0.218515 0 2 14 15 16 17 0 -1 1 -1 
229 | -2.18141 1 1 21 -1 23 -1 0 1 2 -1 
230 | -0.164049 1 2 10 11 12 13 5 -1 16 -1 
231 | -0.465858 1 3 23 -1 24 -1 0 3 6 9 
232 | -0.209804 1 0 0 2 4 -1 11 -1 13 -1 
233 | 13.9501 0 0 0 4 8 -1 1 -1 18 -1 
234 | -0.393388 1 3 1 -1 7 -1 10 11 12 13 
235 | -1.74843 1 2 18 19 20 21 6 -1 18 -1 
236 | 0.212205 1 2 15 16 17 18 0 -1 1 -1 
237 | 88.8284 0 1 7 -1 23 -1 4 13 22 -1 
238 | 0 1 3 9 -1 15 -1 20 21 22 23 
239 | 0.139565 0 1 0 -1 1 -1 0 1 2 -1 
240 | 0 0 4 9 10 11 -1 16 17 18 -1 
241 | 18.6843 0 0 4 14 24 -1 0 -1 1 -1 
242 | -0.0484746 1 0 15 16 17 -1 1 -1 8 -1 
243 | -0.669204 1 0 16 18 20 -1 6 -1 8 -1 
244 | -1.60313 1 2 17 18 19 20 5 -1 16 -1 
245 | 10.547 1 4 12 17 22 -1 3 12 21 -1 
246 | -25.9797 1 0 13 16 19 -1 8 -1 15 -1 
247 | 0.231852 1 0 22 23 24 -1 18 -1 20 -1 
248 | 0.276455 0 0 5 6 7 -1 5 -1 6 -1 
249 | -0.344426 1 1 7 -1 10 -1 13 14 15 -1 
250 | -0.523137 1 4 18 19 20 -1 12 15 18 -1 
251 | 0.549245 1 3 0 -1 2 -1 7 9 11 13 
252 | 9.87959 0 0 0 2 4 -1 1 -1 8 -1 
253 | -0.593619 0 3 13 -1 15 -1 20 21 22 23 
254 | 1.2979 0 0 15 16 17 -1 8 -1 15 -1 
255 | -0.552887 1 0 13 15 17 -1 2 -1 6 -1 
256 | 2.18684 0 0 4 5 6 -1 2 -1 6 -1 
257 | -0.971051 0 2 6 7 8 9 8 -1 15 -1 
258 | -35.176 1 1 12 -1 23 -1 0 3 6 -1 
259 | 0.840446 1 2 6 7 8 9 10 -1 16 -1 
260 | 7.81001 0 2 13 15 17 19 8 -1 15 -1 
261 | 
262 | 100
263 | 18.1392
264 | 0.745595 0.714433 0.594324 0.620613 0.638556 0.524678 0.529876 0.508898 0.474004 0.501073 0.475461 0.498564 0.48881 0.420471 0.455712 0.431462 0.507705 0.518341 0.410566 0.460292 0.40215 0.41128 0.474677 0.41423 0.420274 0.434837 0.393714 0.429241 0.42978 0.394542 0.378158 0.430141 0.458114 0.403137 0.387266 0.436312 0.488213 0.381603 0.476348 0.409592 0.385929 0.382473 0.378688 0.412372 0.496854 0.402126 0.462042 0.362344 0.44962 0.379106 0.386061 0.374572 0.372574 0.440227 0.355094 0.362498 0.439267 0.409491 0.359451 0.358013 0.44535 0.458295 0.351878 0.343382 0.390023 0.36343 0.419763 0.410878 0.411463 0.338594 0.366155 0.409061 0.396475 0.369164 0.44613 0.45627 0.38235 0.373596 0.418531 0.433422 0.396156 0.388696 0.34289 0.384086 0.360233 0.335308 0.389506 0.419185 0.36293 0.44416 0.372464 0.34827 0.371739 0.339166 0.42561 0.359156 0.421092 0.351416 0.346123 0.339954 
265 | -44.7649 1 3 0 -1 9 -1 4 10 16 22 
266 | -13.7241 1 0 0 2 4 -1 6 -1 18 -1 
267 | 0 0 0 6 7 8 -1 0 -1 1 -1 
268 | 148.701 0 2 1 5 9 13 0 -1 21 -1 
269 | -1.88683 1 3 3 -1 22 -1 11 12 13 14 
270 | 0.547277 0 0 6 7 8 -1 18 -1 20 -1 
271 | -0.977397 1 2 1 2 3 4 2 -1 6 -1 
272 | -0.378759 1 3 10 -1 15 -1 10 11 12 13 
273 | -2.17842 1 2 0 1 2 3 16 -1 23 -1 
274 | 0 0 4 7 8 9 -1 1 2 3 -1 
275 | 1.43127 0 0 1 2 3 -1 16 -1 23 -1 
276 | -0.830777 1 0 16 20 24 -1 0 -1 1 -1 
277 | 0.374977 0 0 19 21 23 -1 6 -1 8 -1 
278 | -51.9395 1 2 0 8 16 24 16 -1 23 -1 
279 | 3.86769 0 1 0 -1 23 -1 1 2 3 -1 
280 | -12.7683 0 4 8 16 24 -1 3 12 21 -1 
281 | -1.4361 1 1 20 -1 23 -1 1 2 3 -1 
282 | 10.6162 1 4 8 14 20 -1 0 11 22 -1 
283 | 95.2921 0 1 0 -1 23 -1 1 12 23 -1 
284 | -0.328692 0 2 15 17 19 21 0 -1 1 -1 
285 | -0.835966 1 3 4 -1 9 -1 10 11 12 13 
286 | -13.4859 1 2 13 15 17 19 6 -1 18 -1 
287 | -0.127347 0 0 8 9 10 -1 10 -1 16 -1 
288 | -0.6463 1 4 16 18 20 -1 11 14 17 -1 
289 | -20.5105 1 1 11 -1 23 -1 2 10 18 -1 
290 | 0 0 0 10 11 12 -1 11 -1 13 -1 
291 | -4.48076 1 4 14 16 18 -1 10 16 22 -1 
292 | -0.293131 1 0 13 14 15 -1 1 -1 8 -1 
293 | 5.86091 0 2 14 16 18 20 10 -1 16 -1 
294 | 1.95843 0 3 3 -1 8 -1 16 18 20 22 
295 | 0 0 1 11 -1 12 -1 3 4 5 -1 
296 | -4.31099 1 0 18 19 20 -1 6 -1 18 -1 
297 | 0.4584 1 2 7 8 9 10 10 -1 16 -1 
298 | 0.413332 0 0 0 2 4 -1 0 -1 1 -1 
299 | 1.51056 0 3 9 -1 11 -1 11 14 17 20 
300 | 3.88356 0 2 17 18 19 20 8 -1 15 -1 
301 | 0.190479 1 2 9 10 11 12 11 -1 23 -1 
302 | -4.17704 1 0 0 1 2 -1 15 -1 21 -1 
303 | 0.0283327 0 1 0 -1 3 -1 7 8 9 -1 
304 | -0.469041 1 2 0 1 2 3 3 -1 5 -1 
305 | 0 0 1 1 -1 2 -1 4 5 6 -1 
306 | -0.422702 1 4 8 16 24 -1 21 22 23 -1 
307 | -0.137888 1 3 12 -1 13 -1 17 19 21 23 
308 | -5.13991 1 0 19 20 21 -1 6 -1 18 -1 
309 | -0.61323 0 2 16 17 18 19 2 -1 6 -1 
310 | 3.93315 0 2 0 1 2 3 1 -1 8 -1 
311 | 0.127136 1 3 0 -1 1 -1 12 13 14 15 
312 | 50.2604 0 1 10 -1 24 -1 6 12 18 -1 
313 | 0.925257 1 2 14 16 18 20 0 -1 1 -1 
314 | 11.413 0 2 13 15 17 19 8 -1 15 -1 
315 | -0.310605 0 2 12 13 14 15 6 -1 8 -1 
316 | 2.2124 0 2 3 4 5 6 16 -1 23 -1 
317 | -0.450798 1 0 4 5 6 -1 18 -1 20 -1 
318 | 0.74337 1 4 8 9 10 -1 5 12 19 -1 
319 | -0.44759 1 0 20 22 24 -1 0 -1 1 -1 
320 | -0.410599 0 4 5 10 15 -1 12 13 14 -1 
321 | 0.609321 0 0 3 4 5 -1 18 -1 20 -1 
322 | 0 0 0 9 10 11 -1 11 -1 13 -1 
323 | 0 1 3 0 -1 1 -1 20 21 22 23 
324 | -0.0827149 1 2 8 9 10 11 11 -1 23 -1 
325 | 8.85817 0 0 8 16 24 -1 0 -1 1 -1 
326 | -0.144517 0 2 19 20 21 22 0 -1 1 -1 
327 | 1.0221 0 1 14 -1 16 -1 15 18 21 -1 
328 | 3.1492 0 2 18 19 20 21 6 -1 18 -1 
329 | -1.39385 1 1 0 -1 6 -1 14 16 18 -1 
330 | 3.00888 0 2 20 21 22 23 5 -1 16 -1 
331 | 0.859479 1 4 14 18 22 -1 11 12 13 -1 
332 | -90.4048 1 1 6 -1 23 -1 0 11 22 -1 
333 | -0.0977053 1 1 12 -1 15 -1 5 6 7 -1 
334 | 0 1 2 10 11 12 13 20 -1 21 -1 
335 | 1.43158 0 2 3 4 5 6 3 -1 5 -1 
336 | -1.1336 0 3 8 -1 14 -1 3 4 5 6 
337 | -0.711314 1 2 3 4 5 6 2 -1 6 -1 
338 | -1.37604 0 2 13 14 15 16 16 -1 23 -1 
339 | 69.44 0 2 0 5 10 15 15 -1 21 -1 
340 | 1.06588 1 2 6 7 8 9 8 -1 15 -1 
341 | 4.53087 0 1 0 -1 8 -1 0 3 6 -1 
342 | 0.278119 1 2 8 9 10 11 11 -1 13 -1 
343 | 6.38673 0 2 16 17 18 19 6 -1 18 -1 
344 | -1.00928 0 2 6 7 8 9 10 -1 16 -1 
345 | 2.79753 0 2 17 18 19 20 4 -1 15 -1 
346 | 0.145104 0 3 11 -1 12 -1 6 8 10 12 
347 | 17.4395 0 0 3 6 9 -1 16 -1 23 -1 
348 | -0.671733 1 1 4 -1 9 -1 13 14 15 -1 
349 | -0.0878517 1 1 0 -1 1 -1 20 21 22 -1 
350 | 0 0 1 16 -1 17 -1 15 16 17 -1 
351 | 2.24904 0 2 21 22 23 24 8 -1 15 -1 
352 | -0.558347 0 2 14 15 16 17 2 -1 6 -1 
353 | -7.62145 1 1 3 -1 22 -1 1 2 3 -1 
354 | 0.18912 1 4 11 12 13 -1 21 22 23 -1 
355 | 0.488553 0 1 16 -1 23 -1 0 1 2 -1 
356 | 1.30216 0 2 19 20 21 22 10 -1 16 -1 
357 | -0.0128294 0 0 10 11 12 -1 8 -1 15 -1 
358 | 0.936465 0 0 14 15 16 -1 8 -1 15 -1 
359 | 0.365563 1 2 20 21 22 23 3 -1 5 -1 
360 | -3.25713 1 1 6 -1 15 -1 11 12 13 -1 
361 | -0.217075 0 2 16 17 18 19 0 -1 1 -1 
362 | 0.242923 0 0 0 1 2 -1 0 -1 1 -1 
363 | -0.172333 1 2 9 10 11 12 6 -1 8 -1 
364 | 0 0 0 5 6 7 -1 0 -1 1 -1 
365 | 
366 | 120
367 | 21.9194
368 | 0.779959 0.720165 0.595705 0.571563 0.535582 0.499606 0.536523 0.483826 0.515874 0.570531 0.551142 0.466204 0.42923 0.506733 0.503379 0.451665 0.49209 0.415058 0.443282 0.479461 0.420627 0.475341 0.414676 0.405262 0.413364 0.46933 0.406816 0.408378 0.414279 0.448013 0.454565 0.424883 0.419012 0.478915 0.41848 0.443756 0.443811 0.431987 0.414228 0.400828 0.401658 0.456897 0.479042 0.50187 0.397137 0.459162 0.400631 0.419816 0.439176 0.435985 0.444534 0.438451 0.459688 0.369441 0.419631 0.439997 0.380187 0.401343 0.44231 0.475715 0.376709 0.368235 0.373505 0.435899 0.369234 0.390893 0.36423 0.390352 0.458391 0.373204 0.39257 0.416839 0.43303 0.39127 0.43763 0.42395 0.375924 0.38847 0.362274 0.36805 0.384531 0.411479 0.372115 0.429915 0.381254 0.414892 0.387337 0.417853 0.383723 0.385063 0.441203 0.359474 0.434693 0.427192 0.3698 0.384652 0.35987 0.358252 0.408865 0.386653 0.360915 0.35885 0.433105 0.393084 0.41835 0.354252 0.321257 0.455951 0.351955 0.411855 0.388474 0.341135 0.407976 0.373252 0.358251 0.425806 0.399395 0.397866 0.376751 0.358186 
369 | 40.6203 0 0 5 8 11 -1 0 -1 21 -1 
370 | -0.479347 1 3 4 -1 7 -1 11 12 13 14 
371 | -3.7907 1 0 0 2 4 -1 6 -1 8 -1 
372 | 5.14466 0 1 0 -1 7 -1 5 8 11 -1 
373 | -1.88205 1 4 19 21 23 -1 17 20 23 -1 
374 | 1.51915 0 1 13 -1 22 -1 1 2 3 -1 
375 | -1.46128 1 3 9 -1 11 -1 9 11 13 15 
376 | 2.04993 0 2 3 4 5 6 1 -1 8 -1 
377 | -4.47527 1 2 3 9 15 21 20 -1 21 -1 
378 | -2.64088 1 1 20 -1 23 -1 1 2 3 -1 
379 | -0.744537 1 0 13 17 21 -1 6 -1 8 -1 
380 | 0.351834 0 1 0 -1 3 -1 1 2 3 -1 
381 | 12.0844 1 4 8 16 24 -1 3 12 21 -1 
382 | -5.48802 1 0 18 19 20 -1 6 -1 18 -1 
383 | -13.6583 0 4 11 17 23 -1 3 12 21 -1 
384 | 42.4019 0 1 8 -1 24 -1 8 13 18 -1 
385 | -0.0349497 1 1 10 -1 20 -1 4 5 6 -1 
386 | -0.808442 1 2 10 12 14 16 11 -1 13 -1 
387 | 8.03783 0 2 11 13 15 17 10 -1 16 -1 
388 | 0.218022 0 0 7 8 9 -1 18 -1 20 -1 
389 | 1.93141 0 0 0 1 2 -1 16 -1 23 -1 
390 | -1.60543 1 4 0 11 22 -1 4 11 18 -1 
391 | 0.228031 0 4 21 22 23 -1 0 3 6 -1 
392 | -1.12346 1 1 15 -1 23 -1 21 22 23 -1 
393 | -1.01353 0 4 9 10 11 -1 6 12 18 -1 
394 | 7.63059 0 2 14 16 18 20 10 -1 16 -1 
395 | -0.315042 1 0 0 1 2 -1 10 -1 16 -1 
396 | 0.104164 0 4 8 10 12 -1 15 18 21 -1 
397 | 2.02904 0 2 20 21 22 23 10 -1 16 -1 
398 | 0 0 0 7 8 9 -1 0 -1 1 -1 
399 | -2.39692 1 2 20 21 22 23 0 -1 21 -1 
400 | 1.1524 0 1 0 -1 9 -1 9 10 11 -1 
401 | 1.50194 0 2 3 4 5 6 18 -1 20 -1 
402 | -1.0678 0 2 6 8 10 12 0 -1 1 -1 
403 | 3.15434 0 2 2 3 4 5 16 -1 23 -1 
404 | 0.122849 1 2 12 13 14 15 0 -1 1 -1 
405 | -0.981893 1 1 17 -1 23 -1 1 2 3 -1 
406 | -4.67467 0 4 10 13 16 -1 3 12 21 -1 
407 | -1.60482 1 3 4 -1 21 -1 1 2 3 4 
408 | 2.21751 0 0 6 7 8 -1 11 -1 23 -1 
409 | -1.06821 1 2 16 17 18 19 10 -1 16 -1 
410 | 0.18404 1 2 13 14 15 16 0 -1 1 -1 
411 | -156.642 1 1 2 -1 23 -1 1 12 23 -1 
412 | 0.949116 1 3 16 -1 23 -1 12 13 14 15 
413 | 1.58224 0 0 2 3 4 -1 16 -1 23 -1 
414 | 0 1 0 13 14 15 -1 20 -1 21 -1 
415 | -0.311215 1 3 14 -1 16 -1 18 20 22 24 
416 | 10.221 0 3 7 -1 20 -1 15 18 21 24 
417 | -1.26935 0 2 8 9 10 11 10 -1 16 -1 
418 | -7.13112 1 2 13 15 17 19 5 -1 16 -1 
419 | -0.146188 0 0 8 9 10 -1 11 -1 13 -1 
420 | -37.1859 1 0 0 4 8 -1 15 -1 21 -1 
421 | 0.0639265 1 0 22 23 24 -1 20 -1 21 -1 
422 | -0.431605 1 3 20 -1 22 -1 9 11 13 15 
423 | 31.6382 0 1 15 -1 24 -1 7 14 21 -1 
424 | 20.7156 1 4 5 14 23 -1 1 12 23 -1 
425 | 3.12175 0 2 19 20 21 22 7 -1 21 -1 
426 | 0.505999 1 3 7 -1 10 -1 3 4 5 6 
427 | -2.83573 1 0 20 21 22 -1 10 -1 16 -1 
428 | 1.22026 1 0 6 15 24 -1 7 -1 11 -1 
429 | 2.01097 0 1 23 -1 24 -1 0 5 10 -1 
430 | 2.66994 0 1 0 -1 2 -1 1 6 11 -1 
431 | -7.90093 1 0 0 1 2 -1 7 -1 21 -1 
432 | -0.850259 0 4 14 19 24 -1 12 13 14 -1 
433 | -1.24094 1 2 0 1 2 3 2 -1 6 -1 
434 | 3.65721 1 4 13 17 21 -1 5 14 23 -1 
435 | -0.242117 1 1 6 -1 7 -1 13 14 15 -1 
436 | -2.82717 1 1 22 -1 23 -1 0 3 6 -1 
437 | -1.68081 1 0 12 16 20 -1 2 -1 6 -1 
438 | -2.1984 1 3 21 -1 24 -1 18 20 22 24 
439 | 0.13567 0 1 8 -1 13 -1 9 10 11 -1 
440 | -43.7032 1 1 16 -1 23 -1 0 11 22 -1 
441 | -0.210054 0 1 9 -1 12 -1 17 18 19 -1 
442 | 60.8438 0 0 0 5 10 -1 0 -1 21 -1 
443 | 1.04087 1 1 8 -1 12 -1 17 18 19 -1 
444 | -0.514917 1 0 5 6 7 -1 2 -1 6 -1 
445 | 0 0 1 10 -1 11 -1 16 19 22 -1 
446 | 0.240034 0 0 5 6 7 -1 5 -1 6 -1 
447 | 0.113349 0 1 22 -1 23 -1 1 2 3 -1 
448 | 0.930893 0 3 6 -1 17 -1 8 9 10 11 
449 | 12.5404 0 3 5 -1 21 -1 1 4 7 10 
450 | 0.0906575 1 2 7 9 11 13 7 -1 11 -1 
451 | 5.00702 0 2 17 18 19 20 6 -1 18 -1 
452 | 0.166723 1 2 14 15 16 17 0 -1 1 -1 
453 | 2.34952 0 2 18 19 20 21 10 -1 16 -1 
454 | -1.06265 0 4 8 9 10 -1 5 12 19 -1 
455 | -2.79981 1 2 1 2 3 4 16 -1 23 -1 
456 | -0.0303672 1 3 3 -1 4 -1 10 11 12 13 
457 | 0.392773 0 0 8 9 10 -1 3 -1 5 -1 
458 | -4.73676 1 0 1 2 3 -1 16 -1 23 -1 
459 | -6.27278 0 4 12 18 24 -1 6 12 18 -1 
460 | 6.31679 1 4 13 18 23 -1 6 12 18 -1 
461 | -154.253 1 1 5 -1 23 -1 1 12 23 -1 
462 | -0.336013 0 2 9 10 11 12 20 -1 21 -1 
463 | 0.547614 0 0 17 18 19 -1 11 -1 13 -1 
464 | -0.0776641 0 3 13 -1 15 -1 0 1 2 3 
465 | -0.265544 1 0 3 4 5 -1 5 -1 6 -1 
466 | 0.408633 1 4 10 11 12 -1 9 12 15 -1 
467 | -1.48814 1 1 5 -1 6 -1 16 19 22 -1 
468 | 0.976571 0 3 3 -1 8 -1 16 18 20 22 
469 | -0.495544 1 3 10 -1 13 -1 11 12 13 14 
470 | 0.647363 0 0 4 5 6 -1 18 -1 20 -1 
471 | -2.1414 0 3 12 -1 23 -1 11 12 13 14 
472 | 4.44447 0 2 4 5 6 7 16 -1 23 -1 
473 | 0.397388 1 0 0 1 2 -1 11 -1 13 -1 
474 | 0.668901 0 2 5 6 7 8 2 -1 6 -1 
475 | 0.695693 0 0 4 5 6 -1 4 -1 5 -1 
476 | -0.408145 0 4 7 9 11 -1 19 20 21 -1 
477 | 19.2036 0 0 7 10 13 -1 16 -1 23 -1 
478 | 1.58139 1 2 14 15 16 17 16 -1 23 -1 
479 | -1.3567 1 2 12 13 14 15 10 -1 16 -1 
480 | -0.155689 0 2 14 15 16 17 20 -1 21 -1 
481 | -11.075 1 3 13 -1 19 -1 15 18 21 24 
482 | 4.72331 0 1 2 -1 20 -1 17 20 23 -1 
483 | -1.79109 0 3 9 -1 11 -1 18 20 22 24 
484 | -3.139 1 0 20 21 22 -1 9 -1 20 -1 
485 | 0.80261 1 2 21 22 23 24 2 -1 6 -1 
486 | -1.18557 1 2 15 16 17 18 8 -1 15 -1 
487 | -0.106927 1 1 3 -1 4 -1 13 14 15 -1 
488 | 0 0 0 5 6 7 -1 11 -1 13 -1 
489 | 
490 | 140
491 | 24.1307
492 | 0.732284 0.583687 0.589416 0.552838 0.511431 0.527594 0.587893 0.459888 0.506251 0.498639 0.395016 0.383105 0.394083 0.375467 0.392988 0.546997 0.406255 0.425023 0.439123 0.508883 0.413488 0.406878 0.39797 0.368173 0.471158 0.392655 0.427868 0.424439 0.427478 0.411831 0.382458 0.375596 0.448213 0.419873 0.454779 0.395141 0.417439 0.379852 0.378888 0.420545 0.385719 0.380857 0.491116 0.387919 0.44873 0.366886 0.3834 0.362402 0.470507 0.377015 0.472044 0.373527 0.411479 0.456479 0.360291 0.336536 0.374836 0.440133 0.369 0.342165 0.394013 0.41041 0.349954 0.354622 0.340636 0.360871 0.366328 0.385569 0.373524 0.397882 0.411507 0.346601 0.389195 0.366718 0.380885 0.328847 0.330004 0.388664 0.394366 0.416906 0.400793 0.370661 0.382188 0.323682 0.424898 0.373172 0.364455 0.414546 0.352426 0.411283 0.335104 0.442887 0.430614 0.344932 0.338547 0.411167 0.3902 0.354141 0.373207 0.343519 0.382004 0.362522 0.350084 0.354736 0.327316 0.323384 0.383672 0.367875 0.353243 0.340931 0.342745 0.311719 0.396393 0.409418 0.363095 0.343141 0.356684 0.339246 0.369198 0.338536 0.346519 0.348024 0.350237 0.338316 0.332951 0.311186 0.329245 0.416274 0.419031 0.363052 0.420746 0.344616 0.373497 0.324671 0.358394 0.35753 0.399411 0.325601 0.374817 0.338598 
493 | 2.60768 0 0 7 8 9 -1 11 -1 23 -1 
494 | -19.027 1 3 2 -1 22 -1 9 11 13 15 
495 | 5.09389 0 0 3 8 13 -1 5 -1 6 -1 
496 | -4.96317 1 2 0 1 2 3 0 -1 21 -1 
497 | -4.10927 1 0 0 10 20 -1 11 -1 13 -1 
498 | 4.31427 0 2 0 1 2 3 1 -1 18 -1 
499 | 0 1 0 13 14 15 -1 0 -1 1 -1 
500 | -0.145475 0 0 8 10 12 -1 11 -1 13 -1 
501 | 4.78342 0 2 18 19 20 21 9 -1 20 -1 
502 | -0.304401 1 3 11 -1 14 -1 18 20 22 24 
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798 | 180
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982 | 


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