/*****************************************************************************/
/* Matching procedure API */
/*****************************************************************************/
//
#ifndef _LSVM_MATCHING_H_
#define _LSVM_MATCHING_H_
#include "_latentsvm.h"
#include "_lsvm_error.h"
#include "_lsvm_distancetransform.h"
#include "_lsvm_fft.h"
#include "_lsvm_routine.h"
#ifdef HAVE_TBB
#include "_lsvm_tbbversion.h"
#endif
//extern "C" {
/*
// Function for convolution computation
//
// API
// int convolution(const filterObject *Fi, const featureMap *map, float *f);
// INPUT
// Fi - filter object
// map - feature map
// OUTPUT
// f - the convolution
// RESULT
// Error status
*/
int convolution(const CvLSVMFilterObject *Fi, const CvLSVMFeatureMap *map, float *f);
/*
// Computation multiplication of FFT images
//
// API
// int fftImagesMulti(float *fftImage1, float *fftImage2, int numRows, int numColls,
float *multi);
// INPUT
// fftImage1 - first fft image
// fftImage2 - second fft image
// (numRows, numColls) - image dimesions
// OUTPUT
// multi - multiplication
// RESULT
// Error status
*/
int fftImagesMulti(float *fftImage1, float *fftImage2, int numRows, int numColls,
float *multi);
/*
// Turnover filter matrix for the single feature
//
// API
// int rot2PI(float *filter, int dimX, int dimY, float *rot2PIFilter,
int p, int shift);
// INPUT
// filter - filter weight matrix
// (dimX, dimY) - dimension of filter matrix
// p - number of features
// shift - number of feature (or channel)
// OUTPUT
// rot2PIFilter - rotated matrix
// RESULT
// Error status
*/
int rot2PI(float *filter, int dimX, int dimY, float *rot2PIFilter,
int p, int shift);
/*
// Addition nullable bars to the dimension of feature map (single feature)
//
// API
// int addNullableBars(float *rot2PIFilter, int dimX, int dimY,
float *newFilter, int newDimX, int newDimY);
// INPUT
// rot2PIFilter - filter matrix for the single feature that was rotated
// (dimX, dimY) - dimension rot2PIFilter
// (newDimX, newDimY)- dimension of feature map for the single feature
// OUTPUT
// newFilter - filter matrix with nullable bars
// RESULT
// Error status
*/
int addNullableBars(float *rot2PIFilter, int dimX, int dimY,
float *newFilter, int newDimX, int newDimY);
/*
// Computation FFT image for filter object
//
// API
// int getFFTImageFilterObject(const filterObject *filter,
int mapDimX, int mapDimY,
fftImage **image);
// INPUT
// filter - filter object
// (mapDimX, mapDimY)- dimension of feature map
// OUTPUT
// image - fft image
// RESULT
// Error status
*/
int getFFTImageFilterObject(const CvLSVMFilterObject *filter,
int mapDimX, int mapDimY,
CvLSVMFftImage **image);
/*
// Computation FFT image for feature map
//
// API
// int getFFTImageFeatureMap(const featureMap *map, fftImage **image);
// INPUT
// OUTPUT
// RESULT
// Error status
*/
int getFFTImageFeatureMap(const CvLSVMFeatureMap *map, CvLSVMFftImage **image);
/*
// Function for convolution computation using FFT
//
// API
// int convFFTConv2d(const fftImage *featMapImage, const fftImage *filterImage,
int filterDimX, int filterDimY, float **conv);
// INPUT
// featMapImage - feature map image
// filterImage - filter image
// (filterDimX,filterDimY) - filter dimension
// OUTPUT
// conv - the convolution
// RESULT
// Error status
*/
int convFFTConv2d(const CvLSVMFftImage *featMapImage, const CvLSVMFftImage *filterImage,
int filterDimX, int filterDimY, float **conv);
/*
// Computation objective function D according the original paper
//
// API
// int filterDispositionLevel(const filterObject *Fi, const featureMap *pyramid,
float **scoreFi,
int **pointsX, int **pointsY);
// INPUT
// Fi - filter object (weights and coefficients of penalty
function that are used in this routine)
// pyramid - feature map
// OUTPUT
// scoreFi - values of distance transform on the level at all positions
// (pointsX, pointsY)- positions that correspond to the maximum value
of distance transform at all grid nodes
// RESULT
// Error status
*/
int filterDispositionLevel(const CvLSVMFilterObject *Fi, const CvLSVMFeatureMap *pyramid,
float **scoreFi,
int **pointsX, int **pointsY);
/*
// Computation objective function D according the original paper using FFT
//
// API
// int filterDispositionLevelFFT(const filterObject *Fi, const fftImage *featMapImage,
float **scoreFi,
int **pointsX, int **pointsY);
// INPUT
// Fi - filter object (weights and coefficients of penalty
function that are used in this routine)
// featMapImage - FFT image of feature map
// OUTPUT
// scoreFi - values of distance transform on the level at all positions
// (pointsX, pointsY)- positions that correspond to the maximum value
of distance transform at all grid nodes
// RESULT
// Error status
*/
int filterDispositionLevelFFT(const CvLSVMFilterObject *Fi, const CvLSVMFftImage *featMapImage,
float **scoreFi,
int **pointsX, int **pointsY);
/*
// Computation border size for feature map
//
// API
// int computeBorderSize(int maxXBorder, int maxYBorder, int *bx, int *by);
// INPUT
// maxXBorder - the largest root filter size (X-direction)
// maxYBorder - the largest root filter size (Y-direction)
// OUTPUT
// bx - border size (X-direction)
// by - border size (Y-direction)
// RESULT
// Error status
*/
int computeBorderSize(int maxXBorder, int maxYBorder, int *bx, int *by);
/*
// Addition nullable border to the feature map
//
// API
// int addNullableBorder(featureMap *map, int bx, int by);
// INPUT
// map - feature map
// bx - border size (X-direction)
// by - border size (Y-direction)
// OUTPUT
// RESULT
// Error status
*/
int addNullableBorder(CvLSVMFeatureMap *map, int bx, int by);
/*
// Computation the maximum of the score function at the level
//
// API
// int maxFunctionalScoreFixedLevel(const filterObject **all_F, int n,
const featurePyramid *H,
int level, float b,
int maxXBorder, int maxYBorder,
float *score, CvPoint **points, int *kPoints,
CvPoint ***partsDisplacement);
// INPUT
// all_F - the set of filters (the first element is root filter,
the other - part filters)
// n - the number of part filters
// H - feature pyramid
// level - feature pyramid level for computation maximum score
// b - linear term of the score function
// maxXBorder - the largest root filter size (X-direction)
// maxYBorder - the largest root filter size (Y-direction)
// OUTPUT
// score - the maximum of the score function at the level
// points - the set of root filter positions (in the block space)
// levels - the set of levels
// kPoints - number of root filter positions
// partsDisplacement - displacement of part filters (in the block space)
// RESULT
// Error status
*/
int maxFunctionalScoreFixedLevel(const CvLSVMFilterObject **all_F, int n,
const CvLSVMFeaturePyramid *H,
int level, float b,
int maxXBorder, int maxYBorder,
float *score, CvPoint **points, int *kPoints,
CvPoint ***partsDisplacement);
/*
// Computation score function at the level that exceed threshold
//
// API
// int thresholdFunctionalScoreFixedLevel(const filterObject **all_F, int n,
const featurePyramid *H,
int level, float b,
int maxXBorder, int maxYBorder,
float scoreThreshold,
float **score, CvPoint **points, int *kPoints,
CvPoint ***partsDisplacement);
// INPUT
// all_F - the set of filters (the first element is root filter,
the other - part filters)
// n - the number of part filters
// H - feature pyramid
// level - feature pyramid level for computation maximum score
// 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
// score - score function at the level that exceed threshold
// points - the set of root filter positions (in the block space)
// levels - the set of levels
// kPoints - number of root filter positions
// partsDisplacement - displacement of part filters (in the block space)
// RESULT
// Error status
*/
int thresholdFunctionalScoreFixedLevel(const CvLSVMFilterObject **all_F, int n,
const CvLSVMFeaturePyramid *H,
int level, float b,
int maxXBorder, int maxYBorder,
float scoreThreshold,
float **score, CvPoint **points, int *kPoints,
CvPoint ***partsDisplacement);
/*
// Computation the maximum of the score function
//
// API
// int maxFunctionalScore(const filterObject **all_F, int n,
const featurePyramid *H, float b,
int maxXBorder, int maxYBorder,
float *score,
CvPoint **points, int **levels, int *kPoints,
CvPoint ***partsDisplacement);
// INPUT
// all_F - the set of filters (the first element is root filter,
the other - part filters)
// n - the number of part filters
// H - feature pyramid
// b - linear term of the score function
// maxXBorder - the largest root filter size (X-direction)
// maxYBorder - the largest root filter size (Y-direction)
// OUTPUT
// score - the maximum of the score function
// points - the set of root filter positions (in the block space)
// levels - the set of levels
// kPoints - number of root filter positions
// partsDisplacement - displacement of part filters (in the block space)
// RESULT
// Error status
*/
int maxFunctionalScore(const CvLSVMFilterObject **all_F, int n,
const CvLSVMFeaturePyramid *H, float b,
int maxXBorder, int maxYBorder,
float *score,
CvPoint **points, int **levels, int *kPoints,
CvPoint ***partsDisplacement);
/*
// Computation score function that exceed threshold
//
// API
// int thresholdFunctionalScore(const filterObject **all_F, int n,
const featurePyramid *H,
float b,
int maxXBorder, int maxYBorder,
float scoreThreshold,
float **score,
CvPoint **points, int **levels, int *kPoints,
CvPoint ***partsDisplacement);
// INPUT
// all_F - the set of filters (the first element is root filter,
the other - part filters)
// n - the number of part filters
// H - feature pyramid
// 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
// score - score function values that exceed threshold
// points - the set of root filter positions (in the block space)
// levels - the set of levels
// kPoints - number of root filter positions
// partsDisplacement - displacement of part filters (in the block space)
// RESULT
// Error status
*/
int thresholdFunctionalScore(const CvLSVMFilterObject **all_F, int n,
const CvLSVMFeaturePyramid *H,
float b,
int maxXBorder, int maxYBorder,
float scoreThreshold,
float **score,
CvPoint **points, int **levels, int *kPoints,
CvPoint ***partsDisplacement);
#ifdef HAVE_TBB
/*
// int tbbThresholdFunctionalScore(const CvLSVMFilterObject **all_F, int n,
const CvLSVMFeaturePyramid *H,
const float b,
const int maxXBorder, const int maxYBorder,
const float scoreThreshold,
const int threadsNum,
float **score,
CvPoint **points, int **levels, int *kPoints,
CvPoint ***partsDisplacement);
// INPUT
// all_F - the set of filters (the first element is root filter,
the other - part filters)
// n - the number of part filters
// H - feature pyramid
// 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
// threadsNum - number of threads that will be created using TBB version
// OUTPUT
// score - score function values that exceed threshold
// points - the set of root filter positions (in the block space)
// levels - the set of levels
// kPoints - number of root filter positions
// partsDisplacement - displacement of part filters (in the block space)
// RESULT
// Error status
*/
int tbbThresholdFunctionalScore(const CvLSVMFilterObject **all_F, int n,
const CvLSVMFeaturePyramid *H,
const float b,
const int maxXBorder, const int maxYBorder,
const float scoreThreshold,
const int threadsNum,
float **score,
CvPoint **points, int **levels, int *kPoints,
CvPoint ***partsDisplacement);
#endif
/*
// Perform non-maximum suppression algorithm (described in original paper)
// to remove "similar" bounding boxes
//
// API
// int nonMaximumSuppression(int numBoxes, const CvPoint *points,
const CvPoint *oppositePoints, const float *score,
float overlapThreshold,
int *numBoxesout, CvPoint **pointsOut,
CvPoint **oppositePointsOut, float **scoreOut);
// INPUT
// numBoxes - number of bounding boxes
// points - array of left top corner coordinates
// oppositePoints - array of right bottom corner coordinates
// score - array of detection scores
// overlapThreshold - threshold: bounding box is removed if overlap part
is greater than passed value
// OUTPUT
// numBoxesOut - the number of bounding boxes algorithm returns
// pointsOut - array of left top corner coordinates
// oppositePointsOut - array of right bottom corner coordinates
// scoreOut - array of detection scores
// RESULT
// Error status
*/
#ifdef __cplusplus
extern "C"
#endif
int nonMaximumSuppression(int numBoxes, const CvPoint *points,
const CvPoint *oppositePoints, const float *score,
float overlapThreshold,
int *numBoxesOut, CvPoint **pointsOut,
CvPoint **oppositePointsOut, float **scoreOut);
#ifdef __cplusplus
extern "C"
#endif
int getMaxFilterDims(const CvLSVMFilterObject **filters, int kComponents,
const int *kPartFilters,
unsigned int *maxXBorder, unsigned int *maxYBorder);
//}
#endif