renamed internal headers to avoid conflicts with system header files
This commit is contained in:
Vadim Pisarevsky
396
modules/objdetect/src/_lsvm_matching.h
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396
modules/objdetect/src/_lsvm_matching.h
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/*****************************************************************************/
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/* Matching procedure API */
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/*****************************************************************************/
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//
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#ifndef SVM_MATCHING
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#define SVM_MATCHING
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#include "_latentsvm.h"
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#include "_lsvm_error.h"
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#include "_lsvm_distancetransform.h"
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#include "_lsvm_fft.h"
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#include "_lsvm_routine.h"
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//extern "C" {
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/*
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// Function for convolution computation
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//
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// API
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// int convolution(const filterObject *Fi, const featureMap *map, float *f);
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// INPUT
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// Fi - filter object
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// map - feature map
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// OUTPUT
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// f - the convolution
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// RESULT
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// Error status
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*/
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int convolution(const filterObject *Fi, const featureMap *map, float *f);
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/*
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// Computation multiplication of FFT images
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//
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// API
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// int fftImagesMulti(float *fftImage1, float *fftImage2, int numRows, int numColls,
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float *multi);
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// INPUT
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// fftImage1 - first fft image
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// fftImage2 - second fft image
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// (numRows, numColls) - image dimesions
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// OUTPUT
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// multi - multiplication
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// RESULT
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// Error status
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*/
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int fftImagesMulti(float *fftImage1, float *fftImage2, int numRows, int numColls,
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float *multi);
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/*
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// Turnover filter matrix for the single feature
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//
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// API
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// int rot2PI(float *filter, int dimX, int dimY, float *rot2PIFilter,
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int p, int shift);
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// INPUT
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// filter - filter weight matrix
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// (dimX, dimY) - dimension of filter matrix
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// p - number of features
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// shift - number of feature (or channel)
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// OUTPUT
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// rot2PIFilter - rotated matrix
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// RESULT
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// Error status
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*/
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int rot2PI(float *filter, int dimX, int dimY, float *rot2PIFilter,
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int p, int shift);
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/*
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// Addition nullable bars to the dimension of feature map (single feature)
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//
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// API
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// int addNullableBars(float *rot2PIFilter, int dimX, int dimY,
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float *newFilter, int newDimX, int newDimY);
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// INPUT
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// rot2PIFilter - filter matrix for the single feature that was rotated
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// (dimX, dimY) - dimension rot2PIFilter
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// (newDimX, newDimY)- dimension of feature map for the single feature
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// OUTPUT
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// newFilter - filter matrix with nullable bars
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// RESULT
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// Error status
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*/
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int addNullableBars(float *rot2PIFilter, int dimX, int dimY,
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float *newFilter, int newDimX, int newDimY);
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/*
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// Computation FFT image for filter object
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//
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// API
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// int getFFTImageFilterObject(const filterObject *filter,
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int mapDimX, int mapDimY,
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fftImage **image);
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// INPUT
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// filter - filter object
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// (mapDimX, mapDimY)- dimension of feature map
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// OUTPUT
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// image - fft image
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// RESULT
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// Error status
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*/
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int getFFTImageFilterObject(const filterObject *filter,
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int mapDimX, int mapDimY,
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fftImage **image);
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/*
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// Computation FFT image for feature map
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//
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// API
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// int getFFTImageFeatureMap(const featureMap *map, fftImage **image);
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// INPUT
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// OUTPUT
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// RESULT
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// Error status
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*/
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int getFFTImageFeatureMap(const featureMap *map, fftImage **image);
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/*
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// Function for convolution computation using FFT
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//
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// API
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// int convFFTConv2d(const fftImage *featMapImage, const fftImage *filterImage,
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int filterDimX, int filterDimY, float **conv);
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// INPUT
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// featMapImage - feature map image
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// filterImage - filter image
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// (filterDimX,filterDimY) - filter dimension
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// OUTPUT
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// conv - the convolution
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// RESULT
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// Error status
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*/
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int convFFTConv2d(const fftImage *featMapImage, const fftImage *filterImage,
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int filterDimX, int filterDimY, float **conv);
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/*
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// Computation objective function D according the original paper
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//
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// API
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// int filterDispositionLevel(const filterObject *Fi, const featureMap *pyramid,
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float **scoreFi,
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int **pointsX, int **pointsY);
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// INPUT
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// Fi - filter object (weights and coefficients of penalty
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function that are used in this routine)
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// pyramid - feature map
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// OUTPUT
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// scoreFi - values of distance transform on the level at all positions
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// (pointsX, pointsY)- positions that correspond to the maximum value
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of distance transform at all grid nodes
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// RESULT
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// Error status
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*/
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int filterDispositionLevel(const filterObject *Fi, const featureMap *pyramid,
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float **scoreFi,
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int **pointsX, int **pointsY);
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/*
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// Computation objective function D according the original paper using FFT
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//
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// API
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// int filterDispositionLevelFFT(const filterObject *Fi, const fftImage *featMapImage,
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float **scoreFi,
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int **pointsX, int **pointsY);
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// INPUT
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// Fi - filter object (weights and coefficients of penalty
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function that are used in this routine)
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// featMapImage - FFT image of feature map
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// OUTPUT
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// scoreFi - values of distance transform on the level at all positions
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// (pointsX, pointsY)- positions that correspond to the maximum value
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of distance transform at all grid nodes
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// RESULT
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// Error status
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*/
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int filterDispositionLevelFFT(const filterObject *Fi, const fftImage *featMapImage,
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float **scoreFi,
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int **pointsX, int **pointsY);
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/*
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// Computation border size for feature map
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//
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// API
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// int computeBorderSize(int maxXBorder, int maxYBorder, int *bx, int *by);
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// INPUT
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// maxXBorder - the largest root filter size (X-direction)
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// maxYBorder - the largest root filter size (Y-direction)
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// OUTPUT
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// bx - border size (X-direction)
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// by - border size (Y-direction)
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// RESULT
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// Error status
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*/
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int computeBorderSize(int maxXBorder, int maxYBorder, int *bx, int *by);
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/*
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// Addition nullable border to the feature map
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//
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// API
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// int addNullableBorder(featureMap *map, int bx, int by);
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// INPUT
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// map - feature map
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// bx - border size (X-direction)
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// by - border size (Y-direction)
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// OUTPUT
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// RESULT
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// Error status
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*/
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int addNullableBorder(featureMap *map, int bx, int by);
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/*
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// Computation the maximum of the score function at the level
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//
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// API
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// int maxFunctionalScoreFixedLevel(const filterObject **all_F, int n,
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const featurePyramid *H,
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int level, float b,
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int maxXBorder, int maxYBorder,
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float *score, CvPoint **points, int *kPoints,
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CvPoint ***partsDisplacement);
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// INPUT
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// all_F - the set of filters (the first element is root filter,
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the other - part filters)
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// n - the number of part filters
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// H - feature pyramid
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// level - feature pyramid level for computation maximum score
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// b - linear term of the score function
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// maxXBorder - the largest root filter size (X-direction)
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// maxYBorder - the largest root filter size (Y-direction)
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// OUTPUT
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// score - the maximum of the score function at the level
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// points - the set of root filter positions (in the block space)
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// levels - the set of levels
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// kPoints - number of root filter positions
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// partsDisplacement - displacement of part filters (in the block space)
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// RESULT
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// Error status
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*/
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int maxFunctionalScoreFixedLevel(const filterObject **all_F, int n,
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const featurePyramid *H,
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int level, float b,
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int maxXBorder, int maxYBorder,
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float *score, CvPoint **points, int *kPoints,
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CvPoint ***partsDisplacement);
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/*
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// Computation score function at the level that exceed threshold
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//
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// API
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// int thresholdFunctionalScoreFixedLevel(const filterObject **all_F, int n,
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const featurePyramid *H,
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int level, float b,
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int maxXBorder, int maxYBorder,
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float scoreThreshold,
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float **score, CvPoint **points, int *kPoints,
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CvPoint ***partsDisplacement);
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// INPUT
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// all_F - the set of filters (the first element is root filter,
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the other - part filters)
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// n - the number of part filters
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// H - feature pyramid
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// level - feature pyramid level for computation maximum score
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// b - linear term of the score function
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// maxXBorder - the largest root filter size (X-direction)
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// maxYBorder - the largest root filter size (Y-direction)
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// scoreThreshold - score threshold
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// OUTPUT
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// score - score function at the level that exceed threshold
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// points - the set of root filter positions (in the block space)
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// levels - the set of levels
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// kPoints - number of root filter positions
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// partsDisplacement - displacement of part filters (in the block space)
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// RESULT
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// Error status
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*/
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int thresholdFunctionalScoreFixedLevel(const filterObject **all_F, int n,
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const featurePyramid *H,
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int level, float b,
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int maxXBorder, int maxYBorder,
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float scoreThreshold,
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float **score, CvPoint **points, int *kPoints,
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CvPoint ***partsDisplacement);
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/*
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// Computation the maximum of the score function
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//
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// API
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// int maxFunctionalScore(const filterObject **all_F, int n,
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const featurePyramid *H, float b,
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int maxXBorder, int maxYBorder,
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float *score,
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CvPoint **points, int **levels, int *kPoints,
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CvPoint ***partsDisplacement);
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// INPUT
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// all_F - the set of filters (the first element is root filter,
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the other - part filters)
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// n - the number of part filters
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// H - feature pyramid
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// b - linear term of the score function
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// maxXBorder - the largest root filter size (X-direction)
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// maxYBorder - the largest root filter size (Y-direction)
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// OUTPUT
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// score - the maximum of the score function
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// points - the set of root filter positions (in the block space)
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// levels - the set of levels
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// kPoints - number of root filter positions
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// partsDisplacement - displacement of part filters (in the block space)
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// RESULT
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// Error status
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*/
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int maxFunctionalScore(const filterObject **all_F, int n,
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const featurePyramid *H, float b,
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int maxXBorder, int maxYBorder,
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float *score,
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CvPoint **points, int **levels, int *kPoints,
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CvPoint ***partsDisplacement);
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/*
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// Computation score function that exceed threshold
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//
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// API
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// int thresholdFunctionalScore(const filterObject **all_F, int n,
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const featurePyramid *H,
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float b,
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int maxXBorder, int maxYBorder,
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float scoreThreshold,
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float **score,
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CvPoint **points, int **levels, int *kPoints,
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CvPoint ***partsDisplacement);
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// INPUT
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// all_F - the set of filters (the first element is root filter,
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the other - part filters)
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// n - the number of part filters
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// H - feature pyramid
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// b - linear term of the score function
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// maxXBorder - the largest root filter size (X-direction)
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// maxYBorder - the largest root filter size (Y-direction)
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// scoreThreshold - score threshold
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// OUTPUT
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// score - score function values that exceed threshold
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// points - the set of root filter positions (in the block space)
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// levels - the set of levels
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// kPoints - number of root filter positions
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// partsDisplacement - displacement of part filters (in the block space)
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// RESULT
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// Error status
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*/
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int thresholdFunctionalScore(const filterObject **all_F, int n,
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const featurePyramid *H,
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float b,
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int maxXBorder, int maxYBorder,
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float scoreThreshold,
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float **score,
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CvPoint **points, int **levels, int *kPoints,
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CvPoint ***partsDisplacement);
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/*
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// Perform non-maximum suppression algorithm (described in original paper)
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// to remove "similar" bounding boxes
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//
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// API
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// int nonMaximumSuppression(int numBoxes, const CvPoint *points,
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const CvPoint *oppositePoints, const float *score,
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float overlapThreshold,
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int *numBoxesout, CvPoint **pointsOut,
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CvPoint **oppositePointsOut, float **scoreOut);
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// INPUT
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// numBoxes - number of bounding boxes
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// points - array of left top corner coordinates
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// oppositePoints - array of right bottom corner coordinates
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// score - array of detection scores
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// overlapThreshold - threshold: bounding box is removed if overlap part
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is greater than passed value
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// OUTPUT
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// numBoxesOut - the number of bounding boxes algorithm returns
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// pointsOut - array of left top corner coordinates
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// oppositePointsOut - array of right bottom corner coordinates
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// scoreOut - array of detection scores
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// RESULT
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// Error status
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*/
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#ifdef __cplusplus
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extern "C"
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#endif
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int nonMaximumSuppression(int numBoxes, const CvPoint *points,
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const CvPoint *oppositePoints, const float *score,
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float overlapThreshold,
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int *numBoxesOut, CvPoint **pointsOut,
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CvPoint **oppositePointsOut, float **scoreOut);
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#ifdef __cplusplus
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extern "C"
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#endif
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int getMaxFilterDims(const filterObject **filters, int kComponents,
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const int *kPartFilters,
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unsigned int *maxXBorder, unsigned int *maxYBorder);
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//}
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#endif
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