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OpenCV Buildbot
2012-10-17 11:12:04 +04:00
committed by Andrey Kamaev
parent 0442bca235
commit 81f826db2b
1511 changed files with 258678 additions and 258624 deletions
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modules/objdetect/src/_latentsvm.h
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/*****************************************************************************/
/* Latent SVM prediction API */
/*****************************************************************************/
#ifndef _LATENTSVM_H_
#define _LATENTSVM_H_
#include <stdio.h>
#include "_lsvm_types.h"
#include "_lsvm_error.h"
#include "_lsvm_routine.h"
//////////////////////////////////////////////////////////////
// Building feature pyramid
// (pyramid constructed both contrast and non-contrast image)
//////////////////////////////////////////////////////////////
/*
// Getting feature pyramid
//
// API
// int getFeaturePyramid(IplImage * image, const filterObject **all_F,
const int n_f,
const int lambda, const int k,
const int startX, const int startY,
const int W, const int H, featurePyramid **maps);
// INPUT
// image - image
// lambda - resize scale
// k - size of cells
// startX - X coordinate of the image rectangle to search
// startY - Y coordinate of the image rectangle to search
// W - width of the image rectangle to search
// H - height of the image rectangle to search
// OUTPUT
// maps - feature maps for all levels
// RESULT
// Error status
*/
int getFeaturePyramid(IplImage * image, CvLSVMFeaturePyramid **maps);
/*
// Getting feature map for the selected subimage
//
// API
// int getFeatureMaps(const IplImage * image, const int k, featureMap **map);
// INPUT
// image - selected subimage
// k - size of cells
// OUTPUT
// map - feature map
// RESULT
// Error status
*/
int getFeatureMaps(const IplImage * image, const int k, CvLSVMFeatureMap **map);
/*
// Feature map Normalization and Truncation
//
// API
// int normalizationAndTruncationFeatureMaps(featureMap *map, const float alfa);
// INPUT
// map - feature map
// alfa - truncation threshold
// OUTPUT
// map - truncated and normalized feature map
// RESULT
// Error status
*/
int normalizeAndTruncate(CvLSVMFeatureMap *map, const float alfa);
/*
// Feature map reduction
// In each cell we reduce dimension of the feature vector
// according to original paper special procedure
//
// API
// int PCAFeatureMaps(featureMap *map)
// INPUT
// map - feature map
// OUTPUT
// map - feature map
// RESULT
// Error status
*/
int PCAFeatureMaps(CvLSVMFeatureMap *map);
//////////////////////////////////////////////////////////////
// search object
//////////////////////////////////////////////////////////////
/*
// Transformation filter displacement from the block space
// to the space of pixels at the initial image
//
// API
// int convertPoints(int countLevel, int lambda,
int initialImageLevel,
CvPoint *points, int *levels,
CvPoint **partsDisplacement, int kPoints, int n,
int maxXBorder,
int maxYBorder);
// INPUT
// countLevel - the number of levels in the feature pyramid
// lambda - method parameter
// initialImageLevel - level of feature pyramid that contains feature map
for initial image
// points - the set of root filter positions (in the block space)
// levels - the set of levels
// partsDisplacement - displacement of part filters (in the block space)
// kPoints - number of root filter positions
// n - number of part filters
// maxXBorder - the largest root filter size (X-direction)
// maxYBorder - the largest root filter size (Y-direction)
// OUTPUT
// points - the set of root filter positions (in the space of pixels)
// partsDisplacement - displacement of part filters (in the space of pixels)
// RESULT
// Error status
*/
int convertPoints(int countLevel, int lambda,
int initialImageLevel,
CvPoint *points, int *levels,
CvPoint **partsDisplacement, int kPoints, int n,
int maxXBorder,
int maxYBorder);
/*
// Elimination boxes that are outside the image boudaries
//
// API
// int clippingBoxes(int width, int height,
CvPoint *points, int kPoints);
// INPUT
// width - image wediht
// height - image heigth
// points - a set of points (coordinates of top left or
bottom right corners)
// kPoints - points number
// OUTPUT
// points - updated points (if coordinates less than zero then
set zero coordinate, if coordinates more than image
size then set coordinates equal image size)
// RESULT
// Error status
*/
#ifdef __cplusplus
extern "C"
#endif
int clippingBoxes(int width, int height,
CvPoint *points, int kPoints);
/*
// Creation feature pyramid with nullable border
//
// API
// featurePyramid* createFeaturePyramidWithBorder(const IplImage *image,
int maxXBorder, int maxYBorder);
// INPUT
// image - initial image
// maxXBorder - the largest root filter size (X-direction)
// maxYBorder - the largest root filter size (Y-direction)
// OUTPUT
// RESULT
// Feature pyramid with nullable border
*/
#ifdef __cplusplus
extern "C"
#endif
CvLSVMFeaturePyramid* createFeaturePyramidWithBorder(IplImage *image,
int maxXBorder, int maxYBorder);
/*
// Computation of the root filter displacement and values of score function
//
// API
// int searchObject(const featurePyramid *H, const filterObject **all_F, int n,
float b,
int maxXBorder,
int maxYBorder,
CvPoint **points, int **levels, int *kPoints, float *score,
CvPoint ***partsDisplacement);
// INPUT
// H - feature pyramid
// all_F - the set of filters (the first element is root filter,
other elements - part filters)
// n - the number of part filters
// b - linear term of the score function
// maxXBorder - the largest root filter size (X-direction)
// maxYBorder - the largest root filter size (Y-direction)
// OUTPUT
// points - positions (x, y) of the upper-left corner
of root filter frame
// levels - levels that correspond to each position
// kPoints - number of positions
// score - value of the score function
// partsDisplacement - part filters displacement for each position
of the root filter
// RESULT
// Error status
*/
int searchObject(const CvLSVMFeaturePyramid *H, const CvLSVMFilterObject **all_F, int n,
float b,
int maxXBorder,
int maxYBorder,
CvPoint **points, int **levels, int *kPoints, float *score,
CvPoint ***partsDisplacement);
/*
// Computation of the root filter displacement and values of score function
//
// API
// int searchObjectThreshold(const featurePyramid *H,
const filterObject **all_F, int n,
float b,
int maxXBorder, int maxYBorder,
float scoreThreshold,
CvPoint **points, int **levels, int *kPoints,
float **score, CvPoint ***partsDisplacement);
// INPUT
// H - feature pyramid
// all_F - the set of filters (the first element is root filter,
other elements - part filters)
// n - the number of part filters
// b - linear term of the score function
// maxXBorder - the largest root filter size (X-direction)
// maxYBorder - the largest root filter size (Y-direction)
// scoreThreshold - score threshold
// OUTPUT
// points - positions (x, y) of the upper-left corner
of root filter frame
// levels - levels that correspond to each position
// kPoints - number of positions
// score - values of the score function
// partsDisplacement - part filters displacement for each position
of the root filter
// RESULT
// Error status
*/
int searchObjectThreshold(const CvLSVMFeaturePyramid *H,
const CvLSVMFilterObject **all_F, int n,
float b,
int maxXBorder, int maxYBorder,
float scoreThreshold,
CvPoint **points, int **levels, int *kPoints,
float **score, CvPoint ***partsDisplacement,
int numThreads CV_DEFAULT(-1));
/*
// Computation root filters displacement and values of score function
//
// API
// int searchObjectThresholdSomeComponents(const featurePyramid *H,
const filterObject **filters,
int kComponents, const int *kPartFilters,
const float *b, float scoreThreshold,
CvPoint **points, CvPoint **oppPoints,
float **score, int *kPoints);
// INPUT
// H - feature pyramid
// filters - filters (root filter then it's part filters, etc.)
// kComponents - root filters number
// kPartFilters - array of part filters number for each component
// b - array of linear terms
// scoreThreshold - score threshold
// OUTPUT
// points - root filters displacement (top left corners)
// oppPoints - root filters displacement (bottom right corners)
// score - array of score values
// kPoints - number of boxes
// RESULT
// Error status
*/
#ifdef __cplusplus
extern "C"
#endif
int searchObjectThresholdSomeComponents(const CvLSVMFeaturePyramid *H,
const CvLSVMFilterObject **filters,
int kComponents, const int *kPartFilters,
const float *b, float scoreThreshold,
CvPoint **points, CvPoint **oppPoints,
float **score, int *kPoints, int numThreads);
/*
// Compute opposite point for filter box
//
// API
// int getOppositePoint(CvPoint point,
int sizeX, int sizeY,
float step, int degree,
CvPoint *oppositePoint);
// INPUT
// point - coordinates of filter top left corner
(in the space of pixels)
// (sizeX, sizeY) - filter dimension in the block space
// step - scaling factor
// degree - degree of the scaling factor
// OUTPUT
// oppositePoint - coordinates of filter bottom corner
(in the space of pixels)
// RESULT
// Error status
*/
int getOppositePoint(CvPoint point,
int sizeX, int sizeY,
float step, int degree,
CvPoint *oppositePoint);
/*
// Drawing root filter boxes
//
// API
// int showRootFilterBoxes(const IplImage *image,
const filterObject *filter,
CvPoint *points, int *levels, int kPoints,
CvScalar color, int thickness,
int line_type, int shift);
// INPUT
// image - initial image
// filter - root filter object
// points - a set of points
// levels - levels of feature pyramid
// kPoints - number of points
// color - line color for each box
// thickness - line thickness
// line_type - line type
// shift - shift
// OUTPUT
// window contained initial image and filter boxes
// RESULT
// Error status
*/
int showRootFilterBoxes(IplImage *image,
const CvLSVMFilterObject *filter,
CvPoint *points, int *levels, int kPoints,
CvScalar color, int thickness,
int line_type, int shift);
/*
// Drawing part filter boxes
//
// API
// int showPartFilterBoxes(const IplImage *image,
const filterObject *filter,
CvPoint *points, int *levels, int kPoints,
CvScalar color, int thickness,
int line_type, int shift);
// INPUT
// image - initial image
// filters - a set of part filters
// n - number of part filters
// partsDisplacement - a set of points
// levels - levels of feature pyramid
// kPoints - number of foot filter positions
// color - line color for each box
// thickness - line thickness
// line_type - line type
// shift - shift
// OUTPUT
// window contained initial image and filter boxes
// RESULT
// Error status
*/
int showPartFilterBoxes(IplImage *image,
const CvLSVMFilterObject **filters,
int n, CvPoint **partsDisplacement,
int *levels, int kPoints,
CvScalar color, int thickness,
int line_type, int shift);
/*
// Drawing boxes
//
// API
// int showBoxes(const IplImage *img,
const CvPoint *points, const CvPoint *oppositePoints, int kPoints,
CvScalar color, int thickness, int line_type, int shift);
// INPUT
// img - initial image
// points - top left corner coordinates
// oppositePoints - right bottom corner coordinates
// kPoints - points number
// color - line color for each box
// thickness - line thickness
// line_type - line type
// shift - shift
// OUTPUT
// RESULT
// Error status
*/
int showBoxes(IplImage *img,
const CvPoint *points, const CvPoint *oppositePoints, int kPoints,
CvScalar color, int thickness, int line_type, int shift);
#endif
/*****************************************************************************/
/* Latent SVM prediction API */
/*****************************************************************************/
#ifndef _LATENTSVM_H_
#define _LATENTSVM_H_
#include <stdio.h>
#include "_lsvm_types.h"
#include "_lsvm_error.h"
#include "_lsvm_routine.h"
//////////////////////////////////////////////////////////////
// Building feature pyramid
// (pyramid constructed both contrast and non-contrast image)
//////////////////////////////////////////////////////////////
/*
// Getting feature pyramid
//
// API
// int getFeaturePyramid(IplImage * image, const filterObject **all_F,
const int n_f,
const int lambda, const int k,
const int startX, const int startY,
const int W, const int H, featurePyramid **maps);
// INPUT
// image - image
// lambda - resize scale
// k - size of cells
// startX - X coordinate of the image rectangle to search
// startY - Y coordinate of the image rectangle to search
// W - width of the image rectangle to search
// H - height of the image rectangle to search
// OUTPUT
// maps - feature maps for all levels
// RESULT
// Error status
*/
int getFeaturePyramid(IplImage * image, CvLSVMFeaturePyramid **maps);
/*
// Getting feature map for the selected subimage
//
// API
// int getFeatureMaps(const IplImage * image, const int k, featureMap **map);
// INPUT
// image - selected subimage
// k - size of cells
// OUTPUT
// map - feature map
// RESULT
// Error status
*/
int getFeatureMaps(const IplImage * image, const int k, CvLSVMFeatureMap **map);
/*
// Feature map Normalization and Truncation
//
// API
// int normalizationAndTruncationFeatureMaps(featureMap *map, const float alfa);
// INPUT
// map - feature map
// alfa - truncation threshold
// OUTPUT
// map - truncated and normalized feature map
// RESULT
// Error status
*/
int normalizeAndTruncate(CvLSVMFeatureMap *map, const float alfa);
/*
// Feature map reduction
// In each cell we reduce dimension of the feature vector
// according to original paper special procedure
//
// API
// int PCAFeatureMaps(featureMap *map)
// INPUT
// map - feature map
// OUTPUT
// map - feature map
// RESULT
// Error status
*/
int PCAFeatureMaps(CvLSVMFeatureMap *map);
//////////////////////////////////////////////////////////////
// search object
//////////////////////////////////////////////////////////////
/*
// Transformation filter displacement from the block space
// to the space of pixels at the initial image
//
// API
// int convertPoints(int countLevel, int lambda,
int initialImageLevel,
CvPoint *points, int *levels,
CvPoint **partsDisplacement, int kPoints, int n,
int maxXBorder,
int maxYBorder);
// INPUT
// countLevel - the number of levels in the feature pyramid
// lambda - method parameter
// initialImageLevel - level of feature pyramid that contains feature map
for initial image
// points - the set of root filter positions (in the block space)
// levels - the set of levels
// partsDisplacement - displacement of part filters (in the block space)
// kPoints - number of root filter positions
// n - number of part filters
// maxXBorder - the largest root filter size (X-direction)
// maxYBorder - the largest root filter size (Y-direction)
// OUTPUT
// points - the set of root filter positions (in the space of pixels)
// partsDisplacement - displacement of part filters (in the space of pixels)
// RESULT
// Error status
*/
int convertPoints(int countLevel, int lambda,
int initialImageLevel,
CvPoint *points, int *levels,
CvPoint **partsDisplacement, int kPoints, int n,
int maxXBorder,
int maxYBorder);
/*
// Elimination boxes that are outside the image boudaries
//
// API
// int clippingBoxes(int width, int height,
CvPoint *points, int kPoints);
// INPUT
// width - image wediht
// height - image heigth
// points - a set of points (coordinates of top left or
bottom right corners)
// kPoints - points number
// OUTPUT
// points - updated points (if coordinates less than zero then
set zero coordinate, if coordinates more than image
size then set coordinates equal image size)
// RESULT
// Error status
*/
#ifdef __cplusplus
extern "C"
#endif
int clippingBoxes(int width, int height,
CvPoint *points, int kPoints);
/*
// Creation feature pyramid with nullable border
//
// API
// featurePyramid* createFeaturePyramidWithBorder(const IplImage *image,
int maxXBorder, int maxYBorder);
// INPUT
// image - initial image
// maxXBorder - the largest root filter size (X-direction)
// maxYBorder - the largest root filter size (Y-direction)
// OUTPUT
// RESULT
// Feature pyramid with nullable border
*/
#ifdef __cplusplus
extern "C"
#endif
CvLSVMFeaturePyramid* createFeaturePyramidWithBorder(IplImage *image,
int maxXBorder, int maxYBorder);
/*
// Computation of the root filter displacement and values of score function
//
// API
// int searchObject(const featurePyramid *H, const filterObject **all_F, int n,
float b,
int maxXBorder,
int maxYBorder,
CvPoint **points, int **levels, int *kPoints, float *score,
CvPoint ***partsDisplacement);
// INPUT
// H - feature pyramid
// all_F - the set of filters (the first element is root filter,
other elements - part filters)
// n - the number of part filters
// b - linear term of the score function
// maxXBorder - the largest root filter size (X-direction)
// maxYBorder - the largest root filter size (Y-direction)
// OUTPUT
// points - positions (x, y) of the upper-left corner
of root filter frame
// levels - levels that correspond to each position
// kPoints - number of positions
// score - value of the score function
// partsDisplacement - part filters displacement for each position
of the root filter
// RESULT
// Error status
*/
int searchObject(const CvLSVMFeaturePyramid *H, const CvLSVMFilterObject **all_F, int n,
float b,
int maxXBorder,
int maxYBorder,
CvPoint **points, int **levels, int *kPoints, float *score,
CvPoint ***partsDisplacement);
/*
// Computation of the root filter displacement and values of score function
//
// API
// int searchObjectThreshold(const featurePyramid *H,
const filterObject **all_F, int n,
float b,
int maxXBorder, int maxYBorder,
float scoreThreshold,
CvPoint **points, int **levels, int *kPoints,
float **score, CvPoint ***partsDisplacement);
// INPUT
// H - feature pyramid
// all_F - the set of filters (the first element is root filter,
other elements - part filters)
// n - the number of part filters
// b - linear term of the score function
// maxXBorder - the largest root filter size (X-direction)
// maxYBorder - the largest root filter size (Y-direction)
// scoreThreshold - score threshold
// OUTPUT
// points - positions (x, y) of the upper-left corner
of root filter frame
// levels - levels that correspond to each position
// kPoints - number of positions
// score - values of the score function
// partsDisplacement - part filters displacement for each position
of the root filter
// RESULT
// Error status
*/
int searchObjectThreshold(const CvLSVMFeaturePyramid *H,
const CvLSVMFilterObject **all_F, int n,
float b,
int maxXBorder, int maxYBorder,
float scoreThreshold,
CvPoint **points, int **levels, int *kPoints,
float **score, CvPoint ***partsDisplacement,
int numThreads CV_DEFAULT(-1));
/*
// Computation root filters displacement and values of score function
//
// API
// int searchObjectThresholdSomeComponents(const featurePyramid *H,
const filterObject **filters,
int kComponents, const int *kPartFilters,
const float *b, float scoreThreshold,
CvPoint **points, CvPoint **oppPoints,
float **score, int *kPoints);
// INPUT
// H - feature pyramid
// filters - filters (root filter then it's part filters, etc.)
// kComponents - root filters number
// kPartFilters - array of part filters number for each component
// b - array of linear terms
// scoreThreshold - score threshold
// OUTPUT
// points - root filters displacement (top left corners)
// oppPoints - root filters displacement (bottom right corners)
// score - array of score values
// kPoints - number of boxes
// RESULT
// Error status
*/
#ifdef __cplusplus
extern "C"
#endif
int searchObjectThresholdSomeComponents(const CvLSVMFeaturePyramid *H,
const CvLSVMFilterObject **filters,
int kComponents, const int *kPartFilters,
const float *b, float scoreThreshold,
CvPoint **points, CvPoint **oppPoints,
float **score, int *kPoints, int numThreads);
/*
// Compute opposite point for filter box
//
// API
// int getOppositePoint(CvPoint point,
int sizeX, int sizeY,
float step, int degree,
CvPoint *oppositePoint);
// INPUT
// point - coordinates of filter top left corner
(in the space of pixels)
// (sizeX, sizeY) - filter dimension in the block space
// step - scaling factor
// degree - degree of the scaling factor
// OUTPUT
// oppositePoint - coordinates of filter bottom corner
(in the space of pixels)
// RESULT
// Error status
*/
int getOppositePoint(CvPoint point,
int sizeX, int sizeY,
float step, int degree,
CvPoint *oppositePoint);
/*
// Drawing root filter boxes
//
// API
// int showRootFilterBoxes(const IplImage *image,
const filterObject *filter,
CvPoint *points, int *levels, int kPoints,
CvScalar color, int thickness,
int line_type, int shift);
// INPUT
// image - initial image
// filter - root filter object
// points - a set of points
// levels - levels of feature pyramid
// kPoints - number of points
// color - line color for each box
// thickness - line thickness
// line_type - line type
// shift - shift
// OUTPUT
// window contained initial image and filter boxes
// RESULT
// Error status
*/
int showRootFilterBoxes(IplImage *image,
const CvLSVMFilterObject *filter,
CvPoint *points, int *levels, int kPoints,
CvScalar color, int thickness,
int line_type, int shift);
/*
// Drawing part filter boxes
//
// API
// int showPartFilterBoxes(const IplImage *image,
const filterObject *filter,
CvPoint *points, int *levels, int kPoints,
CvScalar color, int thickness,
int line_type, int shift);
// INPUT
// image - initial image
// filters - a set of part filters
// n - number of part filters
// partsDisplacement - a set of points
// levels - levels of feature pyramid
// kPoints - number of foot filter positions
// color - line color for each box
// thickness - line thickness
// line_type - line type
// shift - shift
// OUTPUT
// window contained initial image and filter boxes
// RESULT
// Error status
*/
int showPartFilterBoxes(IplImage *image,
const CvLSVMFilterObject **filters,
int n, CvPoint **partsDisplacement,
int *levels, int kPoints,
CvScalar color, int thickness,
int line_type, int shift);
/*
// Drawing boxes
//
// API
// int showBoxes(const IplImage *img,
const CvPoint *points, const CvPoint *oppositePoints, int kPoints,
CvScalar color, int thickness, int line_type, int shift);
// INPUT
// img - initial image
// points - top left corner coordinates
// oppositePoints - right bottom corner coordinates
// kPoints - points number
// color - line color for each box
// thickness - line thickness
// line_type - line type
// shift - shift
// OUTPUT
// RESULT
// Error status
*/
int showBoxes(IplImage *img,
const CvPoint *points, const CvPoint *oppositePoints, int kPoints,
CvScalar color, int thickness, int line_type, int shift);
#endif