1 #ifndef _OPENCV_HAARFEATURES_H_
2 #define _OPENCV_HAARFEATURES_H_
3
4 #include "traincascade_features.h"
5
6 #define CV_HAAR_FEATURE_MAX 3
7
8 #define HFP_NAME "haarFeatureParams"
9 class CvHaarFeatureParams : public CvFeatureParams
10 {
11 public:
12 enum { BASIC = 0, CORE = 1, ALL = 2 };
13 /* 0 - BASIC = Viola
14 * 1 - CORE = All upright
15 * 2 - ALL = All features */
16
17 CvHaarFeatureParams();
18 CvHaarFeatureParams( int _mode );
19
20 virtual void init( const CvFeatureParams& fp );
21 virtual void write( cv::FileStorage &fs ) const;
22 virtual bool read( const cv::FileNode &node );
23
24 virtual void printDefaults() const;
25 virtual void printAttrs() const;
26 virtual bool scanAttr( const std::string prm, const std::string val);
27
28 int mode;
29 };
30
31 class CvHaarEvaluator : public CvFeatureEvaluator
32 {
33 public:
34 virtual void init(const CvFeatureParams *_featureParams,
35 int _maxSampleCount, cv::Size _winSize );
36 virtual void setImage(const cv::Mat& img, uchar clsLabel, int idx);
37 virtual float operator()(int featureIdx, int sampleIdx) const;
38 virtual void writeFeatures( cv::FileStorage &fs, const cv::Mat& featureMap ) const;
39 void writeFeature( cv::FileStorage &fs, int fi ) const; // for old file fornat
40 protected:
41 virtual void generateFeatures();
42
43 class Feature
44 {
45 public:
46 Feature();
47 Feature( int offset, bool _tilted,
48 int x0, int y0, int w0, int h0, float wt0,
49 int x1, int y1, int w1, int h1, float wt1,
50 int x2 = 0, int y2 = 0, int w2 = 0, int h2 = 0, float wt2 = 0.0F );
51 float calc( const cv::Mat &sum, const cv::Mat &tilted, size_t y) const;
52 void write( cv::FileStorage &fs ) const;
53
54 bool tilted;
55 struct
56 {
57 cv::Rect r;
58 float weight;
59 } rect[CV_HAAR_FEATURE_MAX];
60
61 struct
62 {
63 int p0, p1, p2, p3;
64 } fastRect[CV_HAAR_FEATURE_MAX];
65 };
66
67 std::vector<Feature> features;
68 cv::Mat sum; /* sum images (each row represents image) */
69 cv::Mat tilted; /* tilted sum images (each row represents image) */
70 cv::Mat normfactor; /* normalization factor */
71 };
72
operator()73 inline float CvHaarEvaluator::operator()(int featureIdx, int sampleIdx) const
74 {
75 float nf = normfactor.at<float>(0, sampleIdx);
76 return !nf ? 0.0f : (features[featureIdx].calc( sum, tilted, sampleIdx)/nf);
77 }
78
calc(const cv::Mat & _sum,const cv::Mat & _tilted,size_t y)79 inline float CvHaarEvaluator::Feature::calc( const cv::Mat &_sum, const cv::Mat &_tilted, size_t y) const
80 {
81 const int* img = tilted ? _tilted.ptr<int>((int)y) : _sum.ptr<int>((int)y);
82 float ret = rect[0].weight * (img[fastRect[0].p0] - img[fastRect[0].p1] - img[fastRect[0].p2] + img[fastRect[0].p3] ) +
83 rect[1].weight * (img[fastRect[1].p0] - img[fastRect[1].p1] - img[fastRect[1].p2] + img[fastRect[1].p3] );
84 if( rect[2].weight != 0.0f )
85 ret += rect[2].weight * (img[fastRect[2].p0] - img[fastRect[2].p1] - img[fastRect[2].p2] + img[fastRect[2].p3] );
86 return ret;
87 }
88
89 #endif
90