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refactored CascadeClassifier to hide implementation details (take 2)

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This commit is contained in:
Vadim Pisarevsky
2013-12-04 19:00:39 +04:00
parent 0736ede7e5
commit ff87385201
4 changed files with 369 additions and 178 deletions
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195
modules/objdetect/include/opencv2/objdetect.hpp
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@@ -149,143 +149,96 @@ enum { CASCADE_DO_CANNY_PRUNING = 1,
CASCADE_DO_ROUGH_SEARCH = 8
};
class CV_EXPORTS_W CascadeClassifier
class CV_EXPORTS_W BaseCascadeClassifier : public Algorithm
{
public:
CV_WRAP CascadeClassifier();
CV_WRAP CascadeClassifier( const String& filename );
virtual ~CascadeClassifier();
virtual ~BaseCascadeClassifier();
virtual bool empty() const = 0;
virtual bool load( const String& filename ) = 0;
virtual void detectMultiScale( InputArray image,
CV_OUT std::vector<Rect>& objects,
double scaleFactor,
int minNeighbors, int flags,
Size minSize, Size maxSize ) = 0;
CV_WRAP virtual bool empty() const;
CV_WRAP bool load( const String& filename );
virtual bool read( const FileNode& node );
CV_WRAP virtual void detectMultiScale( InputArray image,
CV_OUT std::vector<Rect>& objects,
double scaleFactor = 1.1,
int minNeighbors = 3, int flags = 0,
Size minSize = Size(),
Size maxSize = Size() );
virtual void detectMultiScale( InputArray image,
CV_OUT std::vector<Rect>& objects,
CV_OUT std::vector<int>& numDetections,
double scaleFactor,
int minNeighbors, int flags,
Size minSize, Size maxSize ) = 0;
CV_WRAP virtual void detectMultiScale( InputArray image,
CV_OUT std::vector<Rect>& objects,
CV_OUT std::vector<int>& numDetections,
double scaleFactor=1.1,
int minNeighbors=3, int flags=0,
Size minSize=Size(),
Size maxSize=Size() );
CV_WRAP virtual void detectMultiScale( InputArray image,
virtual void detectMultiScale( InputArray image,
CV_OUT std::vector<Rect>& objects,
CV_OUT std::vector<int>& rejectLevels,
CV_OUT std::vector<double>& levelWeights,
double scaleFactor = 1.1,
int minNeighbors = 3, int flags = 0,
Size minSize = Size(),
Size maxSize = Size(),
bool outputRejectLevels = false );
double scaleFactor,
int minNeighbors, int flags,
Size minSize, Size maxSize,
bool outputRejectLevels ) = 0;
virtual bool isOldFormatCascade() const = 0;
virtual Size getOriginalWindowSize() const = 0;
virtual int getFeatureType() const = 0;
virtual void* getOldCascade() = 0;
bool isOldFormatCascade() const;
virtual Size getOriginalWindowSize() const;
int getFeatureType() const;
bool setImage( const Mat& );
protected:
virtual bool detectSingleScale( const Mat& image, int stripCount, Size processingRectSize,
int stripSize, int yStep, double factor, std::vector<Rect>& candidates,
std::vector<int>& rejectLevels, std::vector<double>& levelWeights, bool outputRejectLevels = false );
virtual void detectMultiScaleNoGrouping( const Mat& image, std::vector<Rect>& candidates,
std::vector<int>& rejectLevels, std::vector<double>& levelWeights,
double scaleFactor, Size minObjectSize, Size maxObjectSize,
bool outputRejectLevels = false );
protected:
enum { BOOST = 0
};
enum { DO_CANNY_PRUNING = CASCADE_DO_CANNY_PRUNING,
SCALE_IMAGE = CASCADE_SCALE_IMAGE,
FIND_BIGGEST_OBJECT = CASCADE_FIND_BIGGEST_OBJECT,
DO_ROUGH_SEARCH = CASCADE_DO_ROUGH_SEARCH
};
friend class CascadeClassifierInvoker;
template<class FEval>
friend int predictOrdered( CascadeClassifier& cascade, Ptr<FeatureEvaluator> &featureEvaluator, double& weight);
template<class FEval>
friend int predictCategorical( CascadeClassifier& cascade, Ptr<FeatureEvaluator> &featureEvaluator, double& weight);
template<class FEval>
friend int predictOrderedStump( CascadeClassifier& cascade, Ptr<FeatureEvaluator> &featureEvaluator, double& weight);
template<class FEval>
friend int predictCategoricalStump( CascadeClassifier& cascade, Ptr<FeatureEvaluator> &featureEvaluator, double& weight);
bool setImage( Ptr<FeatureEvaluator>& feval, const Mat& image);
virtual int runAt( Ptr<FeatureEvaluator>& feval, Point pt, double& weight );
class Data
{
public:
struct CV_EXPORTS DTreeNode
{
int featureIdx;
float threshold; // for ordered features only
int left;
int right;
};
struct CV_EXPORTS DTree
{
int nodeCount;
};
struct CV_EXPORTS Stage
{
int first;
int ntrees;
float threshold;
};
bool read(const FileNode &node);
bool isStumpBased;
int stageType;
int featureType;
int ncategories;
Size origWinSize;
std::vector<Stage> stages;
std::vector<DTree> classifiers;
std::vector<DTreeNode> nodes;
std::vector<float> leaves;
std::vector<int> subsets;
};
Data data;
Ptr<FeatureEvaluator> featureEvaluator;
Ptr<CvHaarClassifierCascade> oldCascade;
public:
class CV_EXPORTS MaskGenerator
{
public:
virtual ~MaskGenerator() {}
virtual cv::Mat generateMask(const cv::Mat& src)=0;
virtual void initializeMask(const cv::Mat& /*src*/) {};
virtual Mat generateMask(const Mat& src)=0;
virtual void initializeMask(const Mat& /*src*/) {};
};
void setMaskGenerator(Ptr<MaskGenerator> maskGenerator);
Ptr<MaskGenerator> getMaskGenerator();
void setFaceDetectionMaskGenerator();
protected:
Ptr<MaskGenerator> maskGenerator;
virtual void setMaskGenerator(const Ptr<MaskGenerator>& maskGenerator) = 0;
virtual Ptr<MaskGenerator> getMaskGenerator() = 0;
};
class CV_EXPORTS_W CascadeClassifier : public BaseCascadeClassifier
{
public:
CV_WRAP CascadeClassifier();
CV_WRAP explicit CascadeClassifier(const String& filename);
virtual ~CascadeClassifier();
CV_WRAP virtual bool empty() const;
CV_WRAP virtual bool load( const String& filename );
CV_WRAP virtual void detectMultiScale( InputArray image,
CV_OUT std::vector<Rect>& objects,
double scaleFactor = 1.1,
int minNeighbors = 3, int flags = 0,
Size minSize = Size(),
Size maxSize = Size() );
CV_WRAP virtual void detectMultiScale( InputArray image,
CV_OUT std::vector<Rect>& objects,
CV_OUT std::vector<int>& numDetections,
double scaleFactor=1.1,
int minNeighbors=3, int flags=0,
Size minSize=Size(),
Size maxSize=Size() );
CV_WRAP virtual void detectMultiScale( InputArray image,
CV_OUT std::vector<Rect>& objects,
CV_OUT std::vector<int>& rejectLevels,
CV_OUT std::vector<double>& levelWeights,
double scaleFactor = 1.1,
int minNeighbors = 3, int flags = 0,
Size minSize = Size(),
Size maxSize = Size(),
bool outputRejectLevels = false );
CV_WRAP virtual bool isOldFormatCascade() const;
CV_WRAP virtual Size getOriginalWindowSize() const;
CV_WRAP virtual int getFeatureType() const;
virtual void* getOldCascade();
virtual void setMaskGenerator(const Ptr<MaskGenerator>& maskGenerator);
virtual Ptr<MaskGenerator> getMaskGenerator();
protected:
Ptr<BaseCascadeClassifier> cc;
};
CV_EXPORTS Ptr<CascadeClassifier::MaskGenerator> createFaceDetectionMaskGenerator();
//////////////// HOG (Histogram-of-Oriented-Gradients) Descriptor and Object Detector //////////////
// struct for detection region of interest (ROI)