generic-library/opencv
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

move soft cascade functionality into dedicated module

Browse Source
This commit is contained in:
marina.kolpakova
2013-01-29 12:26:12 +04:00
parent 28098b6632
commit 1b43b0e2df
24 changed files with 631 additions and 164 deletions
Download Patch File Download Diff File Expand all files Collapse all files

99
modules/objdetect/include/opencv2/objdetect/objdetect.hpp
View File

@@ -488,105 +488,6 @@ protected:
Ptr<MaskGenerator> maskGenerator;
};
class CV_EXPORTS_W ICFPreprocessor
{
public:
CV_WRAP ICFPreprocessor();
CV_WRAP void apply(cv::InputArray _frame, cv::OutputArray _integrals) const;
protected:
enum {BINS = 10};
};
// Implementation of soft (stageless) cascaded detector.
class CV_EXPORTS_W SCascade : public Algorithm
{
public:
// Representation of detectors result.
struct CV_EXPORTS Detection
{
// Default object type.
enum {PEDESTRIAN = 1};
// Creates Detection from an object bounding box and confidence.
// Param b is a bounding box
// Param c is a confidence that object belongs to class k
// Paral k is an object class
Detection(const cv::Rect& b, const float c, int k = PEDESTRIAN) : bb(b), confidence(c), kind(k) {}
cv::Rect bb;
float confidence;
int kind;
};
// Create channel integrals for Soft Cascade detector.
class CV_EXPORTS Channels
{
public:
// constrictor form resizing factor.
// Param shr is a resizing factor. Resize is applied before the computing integral sum
Channels(const int shrinkage);
// Appends specified number of HOG first-order features integrals into given vector.
// Param gray is an input 1-channel gray image.
// Param integrals is a vector of integrals. Hog-channels will be appended to it.
// Param bins is a number of hog-bins
void appendHogBins(const cv::Mat& gray, std::vector<cv::Mat>& integrals, int bins) const;
// Converts 3-channel BGR input frame in Luv and appends each channel to the integrals.
// Param frame is an input 3-channel BGR colored image.
// Param integrals is a vector of integrals. Computed from the frame luv-channels will be appended to it.
void appendLuvBins(const cv::Mat& frame, std::vector<cv::Mat>& integrals) const;
private:
int shrinkage;
};
enum { NO_REJECT = 1, DOLLAR = 2, /*PASCAL = 4,*/ DEFAULT = NO_REJECT};
// An empty cascade will be created.
// Param minScale is a minimum scale relative to the original size of the image on which cascade will be applyed.
// Param minScale is a maximum scale relative to the original size of the image on which cascade will be applyed.
// Param scales is a number of scales from minScale to maxScale.
// Param rejCriteria is used for NMS.
CV_WRAP SCascade(const double minScale = 0.4, const double maxScale = 5., const int scales = 55, const int rejCriteria = 1);
CV_WRAP virtual ~SCascade();
cv::AlgorithmInfo* info() const;
// Load cascade from FileNode.
// Param fn is a root node for cascade. Should be <cascade>.
CV_WRAP virtual bool load(const FileNode& fn);
// Load cascade config.
CV_WRAP virtual void read(const FileNode& fn);
// Return the vector of Decection objcts.
// Param image is a frame on which detector will be applied.
// Param rois is a vector of regions of interest. Only the objects that fall into one of the regions will be returned.
// Param objects is an output array of Detections
virtual void detect(InputArray image, InputArray rois, std::vector<Detection>& objects) const;
// Param rects is an output array of bounding rectangles for detected objects.
// Param confs is an output array of confidence for detected objects. i-th bounding rectangle corresponds i-th configence.
CV_WRAP virtual void detect(InputArray image, InputArray rois, OutputArray rects, OutputArray confs) const;
private:
void detectNoRoi(const Mat& image, std::vector<Detection>& objects) const;
struct Fields;
Fields* fields;
double minScale;
double maxScale;
int scales;
int rejCriteria;
};
CV_EXPORTS bool initModule_objdetect(void);
//////////////// HOG (Histogram-of-Oriented-Gradients) Descriptor and Object Detector //////////////
// struct for detection region of interest (ROI)