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

integrate speprocessing strategy

Browse Source
This commit is contained in:
marina.kolpakova
2012-12-12 03:43:20 +04:00
parent d23a4f50bd
commit c470e15d45
5 changed files with 212 additions and 272 deletions
Download Patch File Download Diff File Expand all files Collapse all files

67
modules/gpu/include/opencv2/gpu/gpu.hpp
View File

@@ -1529,33 +1529,38 @@ public:
// ======================== GPU version for soft cascade ===================== //
class CV_EXPORTS ChannelsProcessor
{
public:
enum
{
GENERIC = 1 << 4,
SEPARABLE = 2 << 4
};
// Appends specified number of HOG first-order features integrals into given vector.
// Param frame is an input 3-channel bgr image.
// Param channels is a GPU matrix of optionally shrinked channels
// Param stream is stream is a high-level CUDA stream abstraction used for asynchronous execution.
virtual void apply(InputArray frame, OutputArray channels, Stream& stream = Stream::Null()) = 0;
// Creates a specific preprocessor implementation.
// Param shrinkage is a resizing factor. Resize is applied before the computing integral sum
// Param bins is a number of HOG-like channels.
// Param flags is a channel computing extra flags.
static cv::Ptr<ChannelsProcessor> create(const int shrinkage, const int bins, const int flags = GENERIC);
virtual ~ChannelsProcessor();
protected:
ChannelsProcessor();
};
// Implementation of soft (stageless) cascaded detector.
class CV_EXPORTS SCascade : public Algorithm
{
public:
enum { GENERIC = 1, SEPARABLE = 2};
class CV_EXPORTS Preprocessor
{
public:
// Appends specified number of HOG first-order features integrals into given vector.
// Param frame is an input 3-channel bgr image.
// Param channels is a GPU matrix of integrals.
// Param stream is stream is a high-level CUDA stream abstraction used for asynchronous execution.
virtual void apply(InputArray frame, OutputArray channels, Stream& stream = Stream::Null()) = 0;
// Creates a specific preprocessor implementation.
// Param shrinkage is a resizing factor. Resize is applied before the computing integral sum
// Param bins is a number of HOG-like channels.
// Param method is a channel computing method.
static cv::Ptr<Preprocessor> create(const int shrinkage, const int bins, const int method = GENERIC);
protected:
Preprocessor();
};
// Representation of detectors result.
struct CV_EXPORTS Detection
{
@@ -1569,14 +1574,15 @@ public:
enum {PEDESTRIAN = 0};
};
enum { NO_REJECT = 1, DOLLAR = 2, /*PASCAL = 4,*/ DEFAULT = NO_REJECT};
enum { NO_REJECT = 1, DOLLAR = 2, /*PASCAL = 4,*/ DEFAULT = NO_REJECT, NMS_MASK = 0xF};
// 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 rejfactor is used for NMS.
SCascade(const double minScale = 0.4, const double maxScale = 5., const int scales = 55, const int rejCriteria = 1);
// Param flags is an extra tuning flags.
SCascade(const double minScale = 0.4, const double maxScale = 5., const int scales = 55,
const int flags = NO_REJECT || ChannelsProcessor::GENERIC);
virtual ~SCascade();
@@ -1598,13 +1604,6 @@ public:
// Param stream is stream is a high-level CUDA stream abstraction used for asynchronous execution
virtual void detect(InputArray image, InputArray rois, OutputArray objects, Stream& stream = Stream::Null()) const;
// Convert ROI matrix into the suitable for detect method.
// Param roi is an input matrix of the same size as the image.
// There non zero value mean that detector should be executed in this point.
// Param mask is an output mask
// Param stream is stream is a high-level CUDA stream abstraction used for asynchronous execution
virtual void genRoi(InputArray roi, OutputArray mask, Stream& stream = Stream::Null()) const;
private:
struct Fields;
@@ -1612,9 +1611,9 @@ private:
double minScale;
double maxScale;
int scales;
int rejCriteria;
int flags;
};
CV_EXPORTS bool initModule_gpu(void);