43 #ifndef __OPENCV_OBJDETECT_HPP__
44 #define __OPENCV_OBJDETECT_HPP__
59 #define CV_HAAR_MAGIC_VAL 0x42500000
60 #define CV_TYPE_NAME_HAAR "opencv-haar-classifier"
62 #define CV_IS_HAAR_CLASSIFIER( haar ) \
64 (((const CvHaarClassifierCascade*)(haar))->flags & CV_MAGIC_MASK)==CV_HAAR_MAGIC_VAL)
66 #define CV_HAAR_FEATURE_MAX 3
75 }
rect[CV_HAAR_FEATURE_MAX];
125 #define CV_HAAR_DO_CANNY_PRUNING 1
126 #define CV_HAAR_SCALE_IMAGE 2
127 #define CV_HAAR_FIND_BIGGEST_OBJECT 4
128 #define CV_HAAR_DO_ROUGH_SEARCH 8
142 int min_neighbors CV_DEFAULT(3),
int flags CV_DEFAULT(0),
280 std::vector<int>& rejectLevels, std::vector<double>& levelWeightds,
284 bool outputRejectLevels =
false );
303 ObjectDetection(
const Rect&
rect,
float score,
int classID=-1 );
310 LatentSvmDetector(
const vector<string>& filenames,
const vector<string>& classNames=vector<string>() );
313 virtual void clear();
314 virtual bool empty()
const;
315 bool load(
const vector<string>& filenames,
const vector<string>& classNames=vector<string>() );
317 virtual void detect(
const Mat& image,
318 vector<ObjectDetection>& objectDetections,
319 float overlapThreshold=0.5
f,
322 const vector<string>& getClassNames()
const;
323 size_t getClassCount()
const;
326 vector<CvLatentSvmDetector*> detectors;
327 vector<string> classNames;
347 CV_EXPORTS
void groupRectangles(CV_OUT CV_IN_OUT vector<Rect>& rectList,
int groupThreshold,
double eps=0.2);
348 CV_EXPORTS_W
void groupRectangles(CV_OUT CV_IN_OUT vector<Rect>& rectList, CV_OUT vector<int>&
weights,
int groupThreshold,
double eps=0.2);
349 CV_EXPORTS
void groupRectangles( vector<Rect>& rectList,
int groupThreshold,
double eps, vector<int>*
weights, vector<double>* levelWeights );
350 CV_EXPORTS
void groupRectangles(vector<Rect>& rectList, vector<int>& rejectLevels,
351 vector<double>& levelWeights,
int groupThreshold,
double eps=0.2);
352 CV_EXPORTS
void groupRectangles_meanshift(vector<Rect>& rectList, vector<double>& foundWeights, vector<double>& foundScales,
353 double detectThreshold = 0.0,
Size winDetSize =
Size(64, 128));
359 enum { HAAR = 0, LBP = 1, HOG = 2 };
364 virtual int getFeatureType()
const;
366 virtual bool setImage(
const Mat&
img,
Size origWinSize);
367 virtual bool setWindow(
Point p);
369 virtual double calcOrd(
int featureIdx)
const;
370 virtual int calcCat(
int featureIdx)
const;
389 CV_WRAP CascadeClassifier(
const string&
filename );
390 virtual ~CascadeClassifier();
392 CV_WRAP
virtual bool empty()
const;
393 CV_WRAP
bool load(
const string& filename );
395 CV_WRAP
virtual void detectMultiScale(
const Mat& image,
396 CV_OUT vector<Rect>& objects,
397 double scaleFactor=1.1,
398 int minNeighbors=3,
int flags=0,
402 CV_WRAP
virtual void detectMultiScale(
const Mat& image,
403 CV_OUT vector<Rect>& objects,
404 vector<int>& rejectLevels,
405 vector<double>& levelWeights,
406 double scaleFactor=1.1,
407 int minNeighbors=3,
int flags=0,
410 bool outputRejectLevels=
false );
413 bool isOldFormatCascade()
const;
414 virtual Size getOriginalWindowSize()
const;
415 int getFeatureType()
const;
416 bool setImage(
const Mat& );
422 virtual bool detectSingleScale(
const Mat& image,
int stripCount,
Size processingRectSize,
423 int stripSize,
int yStep,
double factor, vector<Rect>& candidates,
424 vector<int>& rejectLevels, vector<double>& levelWeights,
bool outputRejectLevels=
false);
428 enum { DO_CANNY_PRUNING = 1, SCALE_IMAGE = 2,
429 FIND_BIGGEST_OBJECT = 4, DO_ROUGH_SEARCH = 8 };
431 friend class CascadeClassifierInvoker;
433 template<
class FEval>
434 friend int predictOrdered( CascadeClassifier& cascade,
Ptr<FeatureEvaluator> &featureEvaluator,
double& weight);
436 template<
class FEval>
437 friend int predictCategorical( CascadeClassifier& cascade,
Ptr<FeatureEvaluator> &featureEvaluator,
double& weight);
439 template<
class FEval>
440 friend int predictOrderedStump( CascadeClassifier& cascade,
Ptr<FeatureEvaluator> &featureEvaluator,
double& weight);
442 template<
class FEval>
443 friend int predictCategoricalStump( CascadeClassifier& cascade,
Ptr<FeatureEvaluator> &featureEvaluator,
double& weight);
502 void setFaceDetectionMaskGenerator();
526 enum { DEFAULT_NLEVELS=64 };
528 CV_WRAP
HOGDescriptor() : winSize(64,128), blockSize(16,16), blockStride(8,8),
529 cellSize(8,8), nbins(9), derivAperture(1), winSigma(-1),
531 nlevels(HOGDescriptor::DEFAULT_NLEVELS)
535 Size _cellSize,
int _nbins,
int _derivAperture=1,
double _winSigma=-1,
537 double _L2HysThreshold=0.2,
bool _gammaCorrection=
false,
539 : winSize(_winSize), blockSize(_blockSize), blockStride(_blockStride), cellSize(_cellSize),
540 nbins(_nbins), derivAperture(_derivAperture), winSigma(_winSigma),
541 histogramNormType(_histogramNormType), L2HysThreshold(_L2HysThreshold),
557 CV_WRAP
size_t getDescriptorSize()
const;
558 CV_WRAP
bool checkDetectorSize()
const;
559 CV_WRAP
double getWinSigma()
const;
561 CV_WRAP
virtual void setSVMDetector(
InputArray _svmdetector);
567 CV_WRAP
virtual void save(
const String& filename,
const String& objname=
String())
const;
570 CV_WRAP
virtual void compute(
const Mat&
img,
573 const vector<Point>&
locations=vector<Point>())
const;
575 CV_WRAP
virtual void detect(
const Mat& img, CV_OUT vector<Point>& foundLocations,
576 CV_OUT vector<double>&
weights,
577 double hitThreshold=0,
Size winStride=
Size(),
579 const vector<Point>& searchLocations=vector<Point>())
const;
581 virtual void detect(
const Mat& img, CV_OUT vector<Point>& foundLocations,
582 double hitThreshold=0,
Size winStride=
Size(),
584 const vector<Point>& searchLocations=vector<Point>())
const;
586 CV_WRAP
virtual void detectMultiScale(
const Mat& img, CV_OUT vector<Rect>& foundLocations,
587 CV_OUT vector<double>& foundWeights,
double hitThreshold=0,
589 double finalThreshold=2.0,
bool useMeanshiftGrouping =
false)
const;
591 virtual void detectMultiScale(
const Mat& img, CV_OUT vector<Rect>& foundLocations,
592 double hitThreshold=0,
Size winStride=
Size(),
594 double finalThreshold=2.0,
bool useMeanshiftGrouping =
false)
const;
596 CV_WRAP
virtual void computeGradient(
const Mat& img, CV_OUT
Mat& grad, CV_OUT
Mat& angleOfs,
599 CV_WRAP
static vector<float> getDefaultPeopleDetector();
600 CV_WRAP
static vector<float> getDaimlerPeopleDetector();
618 CV_OUT std::vector<cv::Point>& foundLocations, CV_OUT std::vector<double>& confidences,
623 void detectMultiScaleROI(
const cv::Mat& img,
624 CV_OUT std::vector<cv::Rect>& foundLocations,
625 std::vector<DetectionROI>& locations,
626 double hitThreshold = 0,
627 int groupThreshold = 0)
const;
630 void readALTModel(std::string modelfile);
631 void groupRectangles(vector<cv::Rect>& rectList, vector<double>& weights,
int groupThreshold,
double eps)
const;
636 CV_OUT vector<string>& codes,
640 const vector<string>& codes,
744 return score > rhs.
score;
760 std::vector<Feature>& features,
787 return processImpl(src,
mask);
790 virtual std::string
name()
const =0;
802 static Ptr<Modality> create(
const std::string& modality_type);
836 virtual std::string
name()
const;
872 int extract_threshold);
874 virtual std::string
name()
const;
903 Match(
int x,
int y,
float similarity,
const std::string& class_id,
int template_id);
927 inline Match::Match(
int _x,
int _y,
float _similarity,
const std::string& _class_id,
int _template_id)
928 :
x(_x),
y(_y), similarity(_similarity), class_id(_class_id), template_id(_template_id)
968 void match(
const std::vector<Mat>& sources,
float threshold, std::vector<Match>& matches,
969 const std::vector<std::string>& class_ids = std::vector<std::string>(),
971 const std::vector<Mat>& masks = std::vector<Mat>())
const;
983 int addTemplate(
const std::vector<Mat>& sources,
const std::string& class_id,
984 const Mat& object_mask,
Rect* bounding_box = NULL);
989 int addSyntheticTemplate(
const std::vector<Template>& templates,
const std::string& class_id);
997 const std::vector< Ptr<Modality> >&
getModalities()
const {
return modalities; }
1002 int getT(
int pyramid_level)
const {
return T_at_level[pyramid_level]; }
1015 const std::vector<Template>& getTemplates(
const std::string& class_id,
int template_id)
const;
1017 int numTemplates()
const;
1018 int numTemplates(
const std::string& class_id)
const;
1019 int numClasses()
const {
return static_cast<int>(class_templates.size()); }
1021 std::vector<std::string> classIds()
const;
1026 std::string readClass(
const FileNode& fn,
const std::string &class_id_override =
"");
1027 void writeClass(
const std::string& class_id,
FileStorage& fs)
const;
1029 void readClasses(
const std::vector<std::string>& class_ids,
1030 const std::string&
format =
"templates_%s.yml.gz");
1031 void writeClasses(
const std::string&
format =
"templates_%s.yml.gz")
const;
1047 const std::vector<Size>&
sizes,
1048 float threshold, std::vector<Match>& matches,
1049 const std::string& class_id,
1050 const std::vector<TemplatePyramid>& template_pyramids)
const;
int width
Definition: objdetect.hpp:695
struct CvHaarFeature::@352 rect[CV_HAAR_FEATURE_MAX]
int child
Definition: objdetect.hpp:95
Point2i Point
Definition: core.hpp:893
CvPoint pt
Definition: objdetect.hpp:152
Definition: objdetect.hpp:385
bool operator<(const Match &rhs) const
Sort matches with high similarity to the front.
Definition: objdetect.hpp:906
float score
Definition: objdetect.hpp:219
size_t num_features
Definition: objdetect.hpp:881
SimilarRects(double _eps)
Definition: objdetect.hpp:335
Represents a modality operating over an image pyramid.
Definition: objdetect.hpp:707
int height
Definition: objdetect.hpp:696
std::vector< int > T_at_level
Definition: objdetect.hpp:1036
GLenum GLint GLint y
Definition: core_c.h:613
CvFileNode * node
Definition: core_c.h:1638
const int * sizes
Definition: core_c.h:212
int neighbors
Definition: objdetect.hpp:115
Definition: types_c.h:1021
Match()
Definition: objdetect.hpp:899
int difference_threshold
Definition: objdetect.hpp:880
Definition: objdetect.hpp:525
Ptr< QuantizedPyramid > process(const Mat &src, const Mat &mask=Mat()) const
Form a quantized image pyramid from a source image.
Definition: objdetect.hpp:784
float threshold
Definition: objdetect.hpp:454
const char const char ** filename
Definition: core_c.h:1750
int pyramid_levels
Definition: objdetect.hpp:1035
virtual ~Modality()
Definition: objdetect.hpp:775
Definition: objdetect.hpp:78
virtual bool extractTemplate(Template &templ) const =0
Extract most discriminant features at current pyramid level to form a new template.
int ntrees
Definition: objdetect.hpp:467
CvHidHaarClassifierCascade * hid_cascade
Definition: objdetect.hpp:109
int classID
Definition: objdetect.hpp:306
vector< DTree > classifiers
Definition: objdetect.hpp:481
bool isStumpBased
Definition: objdetect.hpp:473
void delete_obj()
deletes the object. Override if needed
Definition: operations.hpp:2612
File Storage Node class.
Definition: core.hpp:4119
CvSize real_window_size
Definition: objdetect.hpp:106
Size2i Size
Definition: core.hpp:896
CvHaarClassifierCascade CvMemStorage * storage
Definition: objdetect.hpp:140
int stageType
Definition: objdetect.hpp:475
Definition: objdetect.hpp:512
Definition: types_c.h:951
CV_PROP double winSigma
Definition: objdetect.hpp:608
Definition: types_c.h:1138
int pyramidLevels() const
Get number of pyramid levels used by this detector.
Definition: objdetect.hpp:1007
int y
y offset
Definition: objdetect.hpp:681
Definition: objdetect.hpp:464
Feature()
Definition: objdetect.hpp:684
int right
Definition: objdetect.hpp:456
Modality that computes quantized surface normals from a dense depth map.
Definition: objdetect.hpp:853
CV_PROP double L2HysThreshold
Definition: objdetect.hpp:610
std::vector< Feature > features
Definition: objdetect.hpp:698
int sizeX
Definition: objdetect.hpp:187
Definition: objdetect.hpp:448
Definition: objdetect.hpp:332
int * right
Definition: objdetect.hpp:84
CVAPI(CvHaarClassifierCascade *) cvLoadHaarClassifierCascade(const char *directory
GLuint src
Definition: core_c.h:1650
Modality that computes quantized gradient orientations from a color image.
Definition: objdetect.hpp:818
int int int flags
Definition: highgui_c.h:186
struct CvLSVMFilterPosition CvLSVMFilterPosition
int numFeatures
Definition: objdetect.hpp:189
CvMat int int num_features
Definition: ml.hpp:1999
CV_EXPORTS Ptr< Detector > getDefaultLINEMOD()
Factory function for detector using LINE-MOD algorithm with color gradients and depth normals...
int d
Definition: legacy.hpp:3064
CV_WRAP HOGDescriptor(Size _winSize, Size _blockSize, Size _blockStride, Size _cellSize, int _nbins, int _derivAperture=1, double _winSigma=-1, int _histogramNormType=HOGDescriptor::L2Hys, double _L2HysThreshold=0.2, bool _gammaCorrection=false, int _nlevels=HOGDescriptor::DEFAULT_NLEVELS)
Definition: objdetect.hpp:534
virtual void pyrDown()=0
Go to the next pyramid level.
float strong_threshold
Definition: objdetect.hpp:843
int nodeCount
Definition: objdetect.hpp:461
bool operator<(const Candidate &rhs) const
Sort candidates with high score to the front.
Definition: objdetect.hpp:742
double scale
Definition: objdetect.hpp:107
CvSize orig_window_size
Definition: objdetect.hpp:105
float fineFunction[4]
Definition: objdetect.hpp:186
GLXDrawable GLXDrawable read
int CvMemStorage int double eps
Definition: imgproc_c.h:353
CV_PROP int histogramNormType
Definition: objdetect.hpp:609
int template_id
Definition: objdetect.hpp:924
GLenum GLsizei GLenum GLenum const GLvoid * image
Definition: highgui_c.h:230
CV_PROP Size winSize
Definition: objdetect.hpp:602
CV_INLINE CvSize cvSize(int width, int height)
Definition: types_c.h:1145
_Tp height
Definition: core.hpp:883
int label
Quantization.
Definition: objdetect.hpp:682
struct CvHaarStageClassifier CvHaarStageClassifier
CV_EXPORTS_W void write(FileStorage &fs, const string &name, int value)
double eps
Definition: objdetect.hpp:344
CvRect rect
Definition: objdetect.hpp:114
CvHaarClassifier * classifier
Definition: objdetect.hpp:92
const std::vector< Ptr< Modality > > & getModalities() const
Get the modalities used by this detector.
Definition: objdetect.hpp:997
Definition: objdetect.hpp:297
vector< double > confidences
Definition: objdetect.hpp:519
CvRect rect
Definition: core_c.h:100
void clear(const ColorA &color=ColorA::black(), bool clearDepthBuffer=true)
virtual void initializeMask(const cv::Mat &)
Definition: objdetect.hpp:497
float weight
Definition: objdetect.hpp:74
vector< Stage > stages
Definition: objdetect.hpp:480
The 2D size class.
Definition: core.hpp:81
int featureType
Definition: objdetect.hpp:476
Definition: objdetect.hpp:648
int y
Definition: objdetect.hpp:921
float score
Definition: objdetect.hpp:305
CvMat * original
Definition: objdetect.hpp:650
const char * name
Definition: core_c.h:1538
Definition: objdetect.hpp:526
vector< float > leaves
Definition: objdetect.hpp:483
GLint GLvoid * img
Definition: legacy.hpp:1150
struct CvHidHaarClassifierCascade CvHidHaarClassifierCascade
Definition: objdetect.hpp:99
Definition: objdetect.hpp:356
HOGDescriptor(const HOGDescriptor &d)
Definition: objdetect.hpp:550
Ptr< MaskGenerator > maskGenerator
Definition: objdetect.hpp:505
SourceFileRef load(const DataSourceRef &dataSource, size_t sampleRate=0)
int x
Definition: objdetect.hpp:920
int * left
Definition: objdetect.hpp:83
Discriminant feature described by its location and label.
Definition: objdetect.hpp:678
CV_PROP int derivAperture
Definition: objdetect.hpp:607
CV_PROP int nbins
Definition: objdetect.hpp:606
std::vector< Ptr< Modality > > modalities
Definition: objdetect.hpp:1034
int num_components
Definition: objdetect.hpp:204
struct CvHaarFeature CvHaarFeature
struct CvHaarClassifierCascade CvHaarClassifierCascade
CV_EXPORTS void gammaCorrection(const GpuMat &src, GpuMat &dst, bool forward=true, Stream &stream=Stream::Null())
Routines for correcting image color gamma.
int * num_part_filters
Definition: objdetect.hpp:205
int tilted
Definition: objdetect.hpp:70
int getT(int pyramid_level) const
Get sampling step T at pyramid_level.
Definition: objdetect.hpp:1002
_Tp y
Definition: core.hpp:883
vector< DTreeNode > nodes
Definition: objdetect.hpp:482
Definition: objdetect.hpp:451
CV_PROP Size blockSize
Definition: objdetect.hpp:603
int count
Definition: objdetect.hpp:80
virtual ~MaskGenerator()
Definition: objdetect.hpp:495
std::string String
Definition: core.hpp:85
float threshold
Definition: objdetect.hpp:91
CvRect rect
Definition: objdetect.hpp:218
Definition: types_c.h:1272
Definition: objdetect.hpp:382
vector< cv::Point > locations
Definition: objdetect.hpp:517
std::vector< Template > TemplatePyramid
Definition: objdetect.hpp:1038
CV_EXPORTS_W void findDataMatrix(InputArray image, CV_OUT vector< string > &codes, OutputArray corners=noArray(), OutputArrayOfArrays dmtx=noArray())
CV_EXPORTS_W void min(InputArray src1, InputArray src2, OutputArray dst)
computes per-element minimum of two arrays (dst = min(src1, src2))
CvSize int int int CvPoint int delta
Definition: core_c.h:1427
CV_EXPORTS std::deque< CvDataMatrixCode > cvFindDataMatrix(CvMat *im)
Definition: objdetect.hpp:380
struct CvHaarClassifier CvHaarClassifier
virtual ~HOGDescriptor()
Definition: objdetect.hpp:555
Definition: objdetect.hpp:459
const CvArr const CvArr const CvArr * tilted_sum
Definition: objdetect.hpp:147
GLenum GLint x
Definition: core_c.h:632
Definition: objdetect.hpp:381
void CvArr
Definition: types_c.h:196
CV_EXPORTS MatExpr abs(const Mat &m)
vector< int > subsets
Definition: objdetect.hpp:484
int distance_threshold
Definition: objdetect.hpp:879
Definition: objdetect.hpp:68
void colormap(const Mat &quantized, Mat &dst)
Debug function to colormap a quantized image for viewing.
_Tp x
Definition: core.hpp:883
CV_PROP Size blockStride
Definition: objdetect.hpp:604
CvLSVMFilterObject ** filters
Definition: objdetect.hpp:206
std::vector< Mat > LinearMemories
Definition: objdetect.hpp:1042
std::string class_id
Definition: objdetect.hpp:923
Interface for modalities that plug into the LINE template matching representation.
Definition: objdetect.hpp:771
virtual ~QuantizedPyramid()
Definition: objdetect.hpp:711
int x
Definition: objdetect.hpp:165
Definition: objdetect.hpp:300
int featureIdx
Definition: objdetect.hpp:453
Object detector using the LINE template matching algorithm with any set of modalities.
Definition: objdetect.hpp:936
OutputArray OutputArrayOfArrays
Definition: core.hpp:1450
Definition: types_c.h:645
CV_EXPORTS_W double threshold(InputArray src, OutputArray dst, double thresh, double maxval, int type)
applies fixed threshold to the image
XML/YAML File Storage Class.
Definition: core.hpp:4040
Definition: objdetect.hpp:693
float * threshold
Definition: objdetect.hpp:82
int parent
Definition: objdetect.hpp:96
double scale
Definition: objdetect.hpp:515
Feature f
Definition: objdetect.hpp:747
Definition: objdetect.hpp:88
The n-dimensional matrix class.
Definition: core.hpp:1688
int first
Definition: objdetect.hpp:466
CV_PROP Size cellSize
Definition: objdetect.hpp:605
int left
Definition: objdetect.hpp:455
Data data
Definition: objdetect.hpp:487
float score
Definition: objdetect.hpp:748
Definition: types_c.h:465
Definition: objdetect.hpp:522
Definition: objdetect.hpp:492
float threshold
Definition: objdetect.hpp:468
float * H
Definition: objdetect.hpp:190
const CvArr CvSeq CvSeq ** descriptors
Definition: compat.hpp:647
CvSize CvPoint2D32f * corners
Definition: calib3d.hpp:215
float score_threshold
Definition: objdetect.hpp:208
Rect rect
Definition: objdetect.hpp:304
int l
Definition: objdetect.hpp:167
int y
Definition: objdetect.hpp:166
GLuint GLuint GLsizei GLenum type
Definition: core_c.h:114
const GLubyte * c
Definition: legacy.hpp:633
Definition: objdetect.hpp:101
Definition: objdetect.hpp:163
CV_PROP vector< float > svmDetector
Definition: objdetect.hpp:612
int count
Definition: objdetect.hpp:104
template 2D point class.
Definition: core.hpp:82
CV_EXPORTS CvSeq * cvHaarDetectObjectsForROC(const CvArr *image, CvHaarClassifierCascade *cascade, CvMemStorage *storage, std::vector< int > &rejectLevels, std::vector< double > &levelWeightds, double scale_factor CV_DEFAULT(1.1), int min_neighbors CV_DEFAULT(3), int flags CV_DEFAULT(0), CvSize min_size CV_DEFAULT(cvSize(0, 0)), CvSize max_size CV_DEFAULT(cvSize(0, 0)), bool outputRejectLevels=false)
int flags
Definition: objdetect.hpp:103
Size origWinSize
Definition: objdetect.hpp:478
int num_filters
Definition: objdetect.hpp:203
float weak_threshold
Definition: objdetect.hpp:841
int count
Definition: objdetect.hpp:90
CV_EXPORTS_W void drawDataMatrixCodes(InputOutputArray image, const vector< string > &codes, InputArray corners)
int pyramid_level
Definition: objdetect.hpp:697
Candidate(int x, int y, int label, float score)
Definition: objdetect.hpp:764
GLsizei const GLint * locations
CvSize orig_window_size
Definition: objdetect.hpp:121
double factor
Definition: imgproc_c.h:459
CvMat * corners
Definition: objdetect.hpp:651
CvLSVMFilterPosition V
Definition: objdetect.hpp:185
Definition: types_c.h:1333
GLenum GLsizei GLenum format
CvHaarClassifierCascade CvMemStorage double scale_factor CV_DEFAULT(1.1)
GLuint dst
Definition: calib3d.hpp:134
float similarity
Definition: objdetect.hpp:922
TemplatesMap class_templates
Definition: objdetect.hpp:1040
CvHaarStageClassifier * stage_classifier
Definition: objdetect.hpp:108
const CvArr * sum
Definition: objdetect.hpp:147
true
Definition: color.hpp:221
const CvArr * templ
Definition: imgproc_c.h:281
Smart pointer to dynamically allocated objects.
Definition: core.hpp:1268
CV_EXPORTS void groupRectangles_meanshift(vector< Rect > &rectList, vector< double > &foundWeights, vector< double > &foundScales, double detectThreshold=0.0, Size winDetSize=Size(64, 128))
Definition: objdetect.hpp:201
std::vector< std::vector< LinearMemories > > LinearMemoryPyramid
Definition: objdetect.hpp:1044
bool operator()(const Rect &r1, const Rect &r2) const
Definition: objdetect.hpp:336
virtual void quantize(Mat &dst) const =0
Compute quantized image at current pyramid level for online detection.
Definition: objdetect.hpp:184
CvHaarFeature * haar_feature
Definition: objdetect.hpp:81
class CV_EXPORTS FileNode
Definition: core.hpp:3941
Definition: objdetect.hpp:379
CV_EXPORTS OutputArray noArray()
GLenum GLenum GLenum GLenum GLenum scale
std::map< std::string, std::vector< TemplatePyramid > > TemplatesMap
Definition: objdetect.hpp:1039
CvRect r
Definition: objdetect.hpp:73
int sizeY
Definition: objdetect.hpp:188
virtual void copyTo(HOGDescriptor &c) const
CvHaarClassifierCascade * cascade
Definition: objdetect.hpp:140
Ptr< FeatureEvaluator > featureEvaluator
Definition: objdetect.hpp:488
Candidate feature with a score.
Definition: objdetect.hpp:737
struct CvLatentSvmDetector CvLatentSvmDetector
Definition: objdetect.hpp:112
struct CvLSVMFilterObject CvLSVMFilterObject
GLenum GLint GLuint mask
Definition: tracking.hpp:132
struct CvObjectDetection CvObjectDetection
CV_WRAP HOGDescriptor(const String &filename)
Definition: objdetect.hpp:545
CV_WRAP HOGDescriptor()
Definition: objdetect.hpp:528
CvLatentSvmDetector * detector
Definition: objdetect.hpp:270
Definition: objdetect.hpp:216
const CvArr const CvArr * sqsum
Definition: objdetect.hpp:147
Ptr< CvHaarClassifierCascade > oldCascade
Definition: objdetect.hpp:489
size_t num_features
Definition: objdetect.hpp:842
Proxy datatype for passing Mat's and vector<>'s as input parameters.
Definition: core.hpp:1400
CV_EXPORTS Ptr< Detector > getDefaultLINE()
Factory function for detector using LINE algorithm with color gradients.
CV_EXPORTS void groupRectangles(CV_OUT CV_IN_OUT vector< Rect > &rectList, int groupThreshold, double eps=0.2)
struct CvAvgComp CvAvgComp
CV_PROP int nlevels
Definition: objdetect.hpp:613
CV_PROP bool gammaCorrection
Definition: objdetect.hpp:611
static void selectScatteredFeatures(const std::vector< Candidate > &candidates, std::vector< Feature > &features, size_t num_features, float distance)
Choose candidate features so that they are not bunched together.
Represents a successful template match.
Definition: objdetect.hpp:897
Rect_< int > Rect
Definition: core.hpp:897
float * b
Definition: objdetect.hpp:207
int numClasses() const
Definition: objdetect.hpp:1019
_Tp width
Definition: core.hpp:883
int extract_threshold
Definition: objdetect.hpp:882
float * alpha
Definition: objdetect.hpp:85
int next
Definition: objdetect.hpp:94
bool operator==(const Match &rhs) const
Definition: objdetect.hpp:915
int x
x offset
Definition: objdetect.hpp:680
int ncategories
Definition: objdetect.hpp:477