Commit 26bcb381 authored by Andrey Kamaev's avatar Andrey Kamaev

Fix binary compatibility of opencv_contrib

parent 971d02cd
...@@ -857,6 +857,17 @@ namespace cv ...@@ -857,6 +857,17 @@ namespace cv
LDA(int num_components = 0) : LDA(int num_components = 0) :
_num_components(num_components) {}; _num_components(num_components) {};
// Initializes and performs a Discriminant Analysis with Fisher's
// Optimization Criterion on given data in src and corresponding labels
// in labels. If 0 (or less) number of components are given, they are
// automatically determined for given data in computation.
LDA(const Mat& src, vector<int> labels,
int num_components = 0) :
_num_components(num_components)
{
this->compute(src, labels); //! compute eigenvectors and eigenvalues
}
// Initializes and performs a Discriminant Analysis with Fisher's // Initializes and performs a Discriminant Analysis with Fisher's
// Optimization Criterion on given data in src and corresponding labels // Optimization Criterion on given data in src and corresponding labels
// in labels. If 0 (or less) number of components are given, they are // in labels. If 0 (or less) number of components are given, they are
...@@ -917,7 +928,7 @@ namespace cv ...@@ -917,7 +928,7 @@ namespace cv
CV_WRAP virtual void train(InputArrayOfArrays src, InputArray labels) = 0; CV_WRAP virtual void train(InputArrayOfArrays src, InputArray labels) = 0;
// Updates a FaceRecognizer. // Updates a FaceRecognizer.
CV_WRAP virtual void update(InputArrayOfArrays src, InputArray labels); CV_WRAP void update(InputArrayOfArrays src, InputArray labels);
// Gets a prediction from a FaceRecognizer. // Gets a prediction from a FaceRecognizer.
virtual int predict(InputArray src) const = 0; virtual int predict(InputArray src) const = 0;
......
...@@ -12,66 +12,17 @@ class DetectionBasedTracker ...@@ -12,66 +12,17 @@ class DetectionBasedTracker
public: public:
struct Parameters struct Parameters
{ {
int minObjectSize;
int maxObjectSize;
double scaleFactor;
int maxTrackLifetime; int maxTrackLifetime;
int minNeighbors;
int minDetectionPeriod; //the minimal time between run of the big object detector (on the whole frame) in ms (1000 mean 1 sec), default=0 int minDetectionPeriod; //the minimal time between run of the big object detector (on the whole frame) in ms (1000 mean 1 sec), default=0
Parameters(); Parameters();
}; };
class IDetector DetectionBasedTracker(const std::string& cascadeFilename, const Parameters& params);
{
public:
IDetector():
minObjSize(96, 96),
maxObjSize(INT_MAX, INT_MAX),
minNeighbours(2),
scaleFactor(1.1f)
{}
virtual ~IDetector() {}
virtual void detect(const cv::Mat& image, std::vector<cv::Rect>& objects) = 0;
void setMinObjectSize(const cv::Size& min)
{
minObjSize = min;
}
void setMaxObjectSize(const cv::Size& max)
{
maxObjSize = max;
}
cv::Size getMinObjectSize() const
{
return minObjSize;
}
cv::Size getMaxObjectSize() const
{
return maxObjSize;
}
float getScaleFactor()
{
return scaleFactor;
}
void setScaleFactor(float value)
{
scaleFactor = value;
}
int getMinNeighbours()
{
return minNeighbours;
}
void setMinNeighbours(int value)
{
minNeighbours = value;
}
protected:
cv::Size minObjSize;
cv::Size maxObjSize;
int minNeighbours;
float scaleFactor;
};
DetectionBasedTracker(cv::Ptr<IDetector> mainDetector, cv::Ptr<IDetector> trackingDetector, const Parameters& params);
virtual ~DetectionBasedTracker(); virtual ~DetectionBasedTracker();
virtual bool run(); virtual bool run();
...@@ -81,39 +32,19 @@ class DetectionBasedTracker ...@@ -81,39 +32,19 @@ class DetectionBasedTracker
virtual void process(const cv::Mat& imageGray); virtual void process(const cv::Mat& imageGray);
bool setParameters(const Parameters& params); bool setParameters(const Parameters& params);
const Parameters& getParameters() const; const Parameters& getParameters();
typedef std::pair<cv::Rect, int> Object; typedef std::pair<cv::Rect, int> Object;
virtual void getObjects(std::vector<cv::Rect>& result) const; virtual void getObjects(std::vector<cv::Rect>& result) const;
virtual void getObjects(std::vector<Object>& result) const; virtual void getObjects(std::vector<Object>& result) const;
enum ObjectStatus
{
DETECTED_NOT_SHOWN_YET,
DETECTED,
DETECTED_TEMPORARY_LOST,
WRONG_OBJECT
};
struct ExtObject
{
int id;
cv::Rect location;
ObjectStatus status;
ExtObject(int _id, cv::Rect _location, ObjectStatus _status)
:id(_id), location(_location), status(_status)
{
}
};
virtual void getObjects(std::vector<ExtObject>& result) const;
virtual int addObject(const cv::Rect& location); //returns id of the new object
protected: protected:
class SeparateDetectionWork; class SeparateDetectionWork;
cv::Ptr<SeparateDetectionWork> separateDetectionWork; cv::Ptr<SeparateDetectionWork> separateDetectionWork;
friend void* workcycleObjectDetectorFunction(void* p); friend void* workcycleObjectDetectorFunction(void* p);
struct InnerParameters struct InnerParameters
{ {
int numLastPositionsToTrack; int numLastPositionsToTrack;
...@@ -159,11 +90,11 @@ class DetectionBasedTracker ...@@ -159,11 +90,11 @@ class DetectionBasedTracker
std::vector<float> weightsPositionsSmoothing; std::vector<float> weightsPositionsSmoothing;
std::vector<float> weightsSizesSmoothing; std::vector<float> weightsSizesSmoothing;
cv::Ptr<IDetector> cascadeForTracking; cv::CascadeClassifier cascadeForTracking;
void updateTrackedObjects(const std::vector<cv::Rect>& detectedObjects); void updateTrackedObjects(const std::vector<cv::Rect>& detectedObjects);
cv::Rect calcTrackedObjectPositionToShow(int i) const; cv::Rect calcTrackedObjectPositionToShow(int i) const;
cv::Rect calcTrackedObjectPositionToShow(int i, ObjectStatus& status) const;
void detectInRegion(const cv::Mat& img, const cv::Rect& r, std::vector<cv::Rect>& detectedObjectsInRegions); void detectInRegion(const cv::Mat& img, const cv::Rect& r, std::vector<cv::Rect>& detectedObjectsInRegions);
}; };
......
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