#include <iostream>
#include <algorithm>
#include "SIFT.hpp"
#include "__SIFT.hpp"
#include "ocl_SIFT.hpp"
#include "ocl_MathU.h"

Functions
void	ocl_init ()

void	ocl_extractSiftFeatures (const Mat &img, vector< KeyPoint > &keypoints, Mat &descriptor, int intervals, double sigma, double contrast_thres, int curvature_thres, bool img_dbl, int descr_width, int descr_hist_bins)

void	ocl_convertGrayAndNormalize (const Mat &input, Mat &output)

Mat	ocl_createInitImg (const Mat &img, double sigma)

void	ocl_gaussianBlur (const Mat &src, Mat &output, int kSize, float *_gKernel)

void	ocl_resizeHalf (const Mat &input, Mat &output, Size outSize)

void	ocl_buildGaussPyramid (const Mat &base, vector< Mat > &gaussian_pyramid, int octaves, int intervals, double sigma)

void	ocl_scaleSpaceExtrema2 (const vector< Mat > &dog_pyramid, vector< oclFeature > &feats, int octaves, int intervals, double contrast_thres, int curvature_thres)

void	ocl_scaleSpaceExtrema (const vector< Mat > &dog_pyramid, vector< oclFeature > &feats, int octaves, int intervals, double contrast_thres, int curvature_thres)

bool	ocl_isExtremum (float prev_dog, float dog, float *next_dog, int dog_width, int r, int c)

void	ocl_derivative (float dog, int dog_width, int r, int c, float dD)

void	ocl_hessian (float prev_dog, float dog, float next_dog, int dog_width, int r, int c, float H)

bool	ocl_interpExtremum (float prev_dog, float dog, float *next_dog, int dog_width, int dog_height, oclFeature &feat, int idx, int r, int c, int intervals, double contrast_thres, int curvature_thres)

void	ocl_calcFeatureScales (vector< oclFeature > &feats, double sigma, int intervals)

void	ocl_oriHist (float gaussian, int width, int height, float hist, int hist_size, int r, int c, int rad, double sigma)

void	ocl_constructGaussianPyrBuffer (vector< oclFeature > &feats, vector< Mat > &gaussian_pyramid, cl::Buffer &__feats, cl::Buffer &__gaussian_pyramid, cl::Buffer &__gauss_size_accum, cl::Buffer &__gauss_width, cl::Buffer &__gauss_height)

void	ocl_ReleaseGaussianPyrBuffer (cl::Buffer &__feats, cl::Buffer &__gaussian_pyramid, cl::Buffer &__gauss_size_accum, cl::Buffer &__gauss_width, cl::Buffer &__gauss_height)

void	ocl_calcFeatureOris2 (vector< oclFeature > &feats, vector< Mat > &gaussian_pyramid, int layer_per_octave, cl::Buffer &__feats, cl::Buffer &__gaussian_pyramid, cl::Buffer &__gauss_size_accum, cl::Buffer &__gauss_width, cl::Buffer &__gauss_height)

void	ocl_calcFeatureOris (vector< oclFeature > &feats, vector< Mat > &gaussian_pyramid, int layer_per_octave)

void	ocl_descriptorHist (Mat &gaussian, float *hist, int r, int c, float ori, float scl, int d, int n)

void	ocl_computeDescriptors (vector< oclFeature > &feats, vector< Mat > &gaussian_pyramid, int layer_per_octave, int d, int n)

void	ocl_normalizeDescriptor (float *descriptor, int cnt)

void	ocl_hist2Descriptor (float *hist, oclFeature &feat, int d, int n)

void	ocl_feats2KeyPoints (const vector< oclFeature > &feats, vector< KeyPoint > &keypoints)

void	ocl_featsVec2Mat (const vector< oclFeature > &feats, Mat &mat)

void	ocl_computeDescriptors2 (vector< oclFeature > &feats, vector< Mat > &gaussian_pyramid, int layer_per_octave, int d, int n, cl::Buffer &__feats, cl::Buffer &__gaussian_pyramid, cl::Buffer &__gauss_size_accum, cl::Buffer &__gauss_width, cl::Buffer &__gauss_height)

Variables
char	platformChooser

vector< cl::Platform >	platforms

cl::Context	context

cl::CommandQueue	commandQueue

cl::Program	program

cl::Kernel	cvtGrayNormKernel

cl::Kernel	resizeKernel

cl::Kernel	gaussianKernel

cl::Kernel	scaleSpaceExtremaKernel

cl::Kernel	calcFeatureOrisKernel

cl::Kernel	computeDescriptorKernel

vector< cl::Device >	devices

cl_int	errNum

float *	oclgKernel

Function Documentation

◆ ocl_buildGaussPyramid()

void ocl_buildGaussPyramid	(	const Mat &	base,
		vector< Mat > &	gaussian_pyramid,
		int	octaves,
		int	intervals,
		double	sigma
	)

Build Gaussian pyramid

Parameters

base	base image for the pyramid
gaussian_pyramid	returned gaussian pyramid, size : octaves x (intervals + 3)
octaves	number of octaves
intervals	number of intervals per octave
sigma	sigma for gaussian smoothing

◆ ocl_calcFeatureOris()

void ocl_calcFeatureOris	(	vector< oclFeature > &	feats,
		vector< Mat > &	gaussian_pyramid,
		int	layer_per_octave
	)

Computes a canonical orientation for each image feature (Native)

Parameters

feats	feature vector
gaussian_pyramid	gaussian pyramid
layer_per_octave	number of layers per octave

◆ ocl_calcFeatureOris2()

void ocl_calcFeatureOris2	(	vector< oclFeature > &	feats,
		vector< Mat > &	gaussian_pyramid,
		int	layer_per_octave,
		cl::Buffer &	__feats,
		cl::Buffer &	__gaussian_pyramid,
		cl::Buffer &	__gauss_size_accum,
		cl::Buffer &	__gauss_width,
		cl::Buffer &	__gauss_height
	)

Computes a canonical orientation for each image feature (OpenCL)

Parameters

feats	feature vector
gaussian_pyramid	gaussian pyramid
layer_per_octave	number of layers per octave
__feats	feature OpenCL buffer
__gaussian_pyramid	gaussian pyramid OpenCL buffer
__gauss_size_accum	gaussian accumulated total size OpenCL buffer
__gauss_width	gaussian width OpenCL buffer
__gauss_height	gaussian height OpenCL buffer

◆ ocl_calcFeatureScales()

void ocl_calcFeatureScales	(	vector< oclFeature > &	feats,
		double	sigma,
		int	intervals
	)

Calculates characteristic scale

Parameters

feats	feature vector
sigma	sigma for Gaussian smoothing
intervals	intervals per octave

◆ ocl_computeDescriptors()

void ocl_computeDescriptors	(	vector< oclFeature > &	feats,
		vector< Mat > &	gaussian_pyramid,
		int	layer_per_octave,
		int	d,
		int	n
	)

Computes feature descriptors (Native)

Parameters

feats	feature vector
gaussian_pyramid	Gaussian pyramid
layer_per_octave	number of layers per octave in Gaussian pyramid
d	width of 2d hist
n	number of bins for descriptor

◆ ocl_computeDescriptors2()

void ocl_computeDescriptors2	(	vector< oclFeature > &	feats,
		vector< Mat > &	gaussian_pyramid,
		int	layer_per_octave,
		int	d,
		int	n,
		cl::Buffer &	__feats,
		cl::Buffer &	__gaussian_pyramid,
		cl::Buffer &	__gauss_size_accum,
		cl::Buffer &	__gauss_width,
		cl::Buffer &	__gauss_height
	)

Computes feature descriptors (OpenCL)

Parameters

feats	feature vector
gaussian_pyramid	Gaussian pyramid
layer_per_octave	number of layers per octave in Gaussian pyramid
d	width of 2d hist
n	number of bins for descriptor
__feats	feature OpenCL buffer
__gaussian_pyramid	gaussian pyramid OpenCL buffer
__gauss_size_accum	gaussian accumulated total size OpenCL buffer
__gauss_width	gaussian width OpenCL buffer
__gauss_height	gaussian height OpenCL buffer

◆ ocl_constructGaussianPyrBuffer()

void ocl_constructGaussianPyrBuffer	(	vector< oclFeature > &	feats,
		vector< Mat > &	gaussian_pyramid,
		cl::Buffer &	__feats,
		cl::Buffer &	__gaussian_pyramid,
		cl::Buffer &	__gauss_size_accum,
		cl::Buffer &	__gauss_width,
		cl::Buffer &	__gauss_height
	)

Initialize OpenCL buffer

Parameters

feats	calculated features
gaussian_pyramid	calculated gaussian pyramid
__feats	feature OpenCL buffer
__gaussian_pyramid	gaussian pyramid OpenCL buffer
__gauss_size_accum	gaussian accumulated total size OpenCL buffer
__gauss_width	gaussian width OpenCL buffer
__gauss_height	gaussian height OpenCL buffer

◆ ocl_convertGrayAndNormalize()

void ocl_convertGrayAndNormalize	(	const Mat &	input,
		Mat &	output
	)

Change 3Channel RGB image to normalized gray image.

Parameters

input	3Channel RGB input image
output	normalized grayscale output image with pixel values in 0.0f~1.0f

◆ ocl_createInitImg()

Mat ocl_createInitImg	(	const Mat &	img,
		double	sigma
	)

Create the initial image for builing gaussian pyramid, optionally double the image size before smoothing]

Parameters

img	input image
sigma	sigma for gaussian smoothing

Returns: returned image

◆ ocl_derivative()

void ocl_derivative	(	float *	dog,
		int	dog_width,
		int	r,
		int	c,
		float *	dD
	)

◆ ocl_descriptorHist()

void ocl_descriptorHist	(	Mat &	gaussian,
		float *	hist,
		int	r,
		int	c,
		float	ori,
		float	scl,
		int	d,
		int	n
	)

◆ ocl_extractSiftFeatures()

void ocl_extractSiftFeatures	(	const Mat &	img,
		vector< KeyPoint > &	keypoints,
		Mat &	descriptor,
		int	intervals = `SIFT_INTERVALS`,
		double	sigma = `SIFT_SIGMA`,
		double	contrast_thres = `SIFT_CONTRAST_THRES`,
		int	curvature_thres = `SIFT_CURVATURE_THRES`,
		bool	img_dbl = `SIFT_IMG_DBL`,
		int	descr_width = `SIFT_DESCR_WIDTH`,
		int	descr_hist_bins = `SIFT_DESCR_HIST_BINS`
	)

Detect & extract sift features for an image

Parameters

img	source image for extract sift features : grayscale image with pixel values in 0.0f~1.0f
keypoints	vector for store sift feature point
descriptor	Mat for store sift descriptor, each row for a keypoint
intervals	the number of sampled intervals per octave
sigma	sigma for initial gaussian smoothing
contrast_thres	threshold on keypoint contrast
curvature_thres	threshold on keypoint ratio of principle curvatures
img_dbl	double image size before pyramid construction?
descr_width	width of descriptor histogram array
descr_hist_bins	number of bins per histogram in descriptor array

◆ ocl_feats2KeyPoints()

void ocl_feats2KeyPoints	(	const vector< oclFeature > &	feats,
		vector< KeyPoint > &	keypoints
	)

Convert features to keypoints

Parameters

feats	features in vector
keypoints	returned keypoint vector

◆ ocl_featsVec2Mat()

void ocl_featsVec2Mat	(	const vector< oclFeature > &	feats,
		Mat &	mat
	)

Convert features from vector to Mat

Parameters

feats	features in vector
mat	returned Mat

◆ ocl_gaussianBlur()

void ocl_gaussianBlur	(	const Mat &	src,
		Mat &	output,
		int	kSize,
		float *	_gKernel
	)

Blurs an image using a Gaussian filter using padding.
Assume that dst already copy the data of src.

Parameters

src	input image; Normalized grayscale input image
output	output image of the same size and type as src.
kSize	width of the input image
gKernel	Gaussian kernel

◆ ocl_hessian()

void ocl_hessian	(	float *	prev_dog,
		float *	dog,
		float *	next_dog,
		int	dog_width,
		int	r,
		int	c,
		float *	H
	)

◆ ocl_hist2Descriptor()

void ocl_hist2Descriptor	(	float *	hist,
		oclFeature &	feat,
		int	d,
		int	n
	)

converts 2d hist into 1d descriptor

Parameters

hist	2d histogram
feat	feature point
d	width of 2d hist
n	number of bins for descriptor

◆ ocl_init()

void ocl_init ( )

Declare for OpenCL code execution

◆ ocl_interpExtremum()

bool ocl_interpExtremum	(	float *	prev_dog,
		float *	dog,
		float *	next_dog,
		int	dog_width,
		int	dog_height,
		oclFeature &	feat,
		int	idx,
		int	r,
		int	c,
		int	intervals,
		double	contrast_thres,
		int	curvature_thres
	)

Interpolates a scale-space extremum's location

Parameters

prev_dog	previous Dog image
dog	current Dog image
next_dog	next Dog image
dog_width	width of current Dog image
dog_height	height of current Dog image
feat	returned feature
idx	index of intervals
r	pixel's image row
c	pixel's image col
intervals	number of intervals per octave
contrast_thres	low threshold on feature contrast
curvature_thres	threshold on feature curvature

Returns: is a feature?

◆ ocl_isExtremum()

bool ocl_isExtremum	(	float *	prev_dog,
		float *	dog,
		float *	next_dog,
		int	dog_width,
		int	r,
		int	c
	)

Determines whether a pixel is a scale-space extremum

Parameters

prev_dog	previous Dog image
dog	current Dog image
next_dog	next Dog image
dog_width	width of current Dog image
r	pixel's image row
c	pixel's image col

Returns: is a extremum?

◆ ocl_normalizeDescriptor()

void ocl_normalizeDescriptor	(	float *	descriptor,
		int	cnt
	)

◆ ocl_oriHist()

void ocl_oriHist	(	float *	gaussian,
		int	width,
		int	height,
		float *	hist,
		int	hist_size,
		int	r,
		int	c,
		int	rad,
		double	sigma
	)

◆ ocl_ReleaseGaussianPyrBuffer()

void ocl_ReleaseGaussianPyrBuffer	(	cl::Buffer &	__feats,
		cl::Buffer &	__gaussian_pyramid,
		cl::Buffer &	__gauss_size_accum,
		cl::Buffer &	__gauss_width,
		cl::Buffer &	__gauss_height
	)

Release OpenCL buffer

Parameters

__feats	feature OpenCL buffer
__gaussian_pyramid	gaussian pyramid OpenCL buffer
__gauss_size_accum	gaussian accumulated total size OpenCL buffer
__gauss_width	gaussian width OpenCL buffer
__gauss_height	gaussian height OpenCL buffer

◆ ocl_resizeHalf()

void ocl_resizeHalf	(	const Mat &	input,
		Mat &	output,
		Size	outSize
	)

Resize image using Nearest neighbor sampling. Reduce width and height in half.

Parameters

input	normalized grayscale input image
output	resized output image
outSize	output image size

◆ ocl_scaleSpaceExtrema()

void ocl_scaleSpaceExtrema	(	const vector< Mat > &	dog_pyramid,
		vector< oclFeature > &	feats,
		int	octaves,
		int	intervals,
		double	contrast_thres,
		int	curvature_thres
	)

Detects features at extrema in DoG scale space (Native)

Parameters

dog_pyramid	Dog pyramid
feats	Detected features with scales, origentations and descriptors to be determined
octaves	number of octaves
intervals	number of intervals per octave
contrast_thres	low threshold on feature contrast
curvature_thres	high threshold on feature ratio of principal curvatures

◆ ocl_scaleSpaceExtrema2()

void ocl_scaleSpaceExtrema2	(	const vector< Mat > &	dog_pyramid,
		vector< oclFeature > &	feats,
		int	octaves,
		int	intervals,
		double	contrast_thres,
		int	curvature_thres
	)

Detects features at extrema in DoG scale space (OpenCL)

Parameters

dog_pyramid	Dog pyramid
feats	Detected features with scales, origentations and descriptors to be determined
octaves	number of octaves
intervals	number of intervals per octave
contrast_thres	low threshold on feature contrast
curvature_thres	high threshold on feature ratio of principal curvatures

Variable Documentation

◆ calcFeatureOrisKernel

cl::Kernel calcFeatureOrisKernel

◆ commandQueue

cl::CommandQueue commandQueue

◆ computeDescriptorKernel

cl::Kernel computeDescriptorKernel

◆ context

cl::Context context

◆ cvtGrayNormKernel

cl::Kernel cvtGrayNormKernel

◆ devices

vector<cl::Device> devices

◆ errNum

cl_int errNum

◆ gaussianKernel

cl::Kernel gaussianKernel

◆ oclgKernel

float* oclgKernel

◆ platformChooser

char platformChooser

Choose Platform

0 for desktop or laptop with non-optimus
1 for laptop with optimus
2 for embedded board (e.g. Odroid-XU4)

◆ platforms

vector<cl::Platform> platforms

◆ program

cl::Program program

◆ resizeKernel

cl::Kernel resizeKernel

◆ scaleSpaceExtremaKernel

cl::Kernel scaleSpaceExtremaKernel

Functions

Variables

Function Documentation

◆ ocl_buildGaussPyramid()

◆ ocl_calcFeatureOris()

◆ ocl_calcFeatureOris2()

◆ ocl_calcFeatureScales()

◆ ocl_computeDescriptors()

◆ ocl_computeDescriptors2()

◆ ocl_constructGaussianPyrBuffer()

◆ ocl_convertGrayAndNormalize()

◆ ocl_createInitImg()

◆ ocl_derivative()

◆ ocl_descriptorHist()

◆ ocl_extractSiftFeatures()

◆ ocl_feats2KeyPoints()

◆ ocl_featsVec2Mat()

◆ ocl_gaussianBlur()

◆ ocl_hessian()

◆ ocl_hist2Descriptor()

◆ ocl_init()

◆ ocl_interpExtremum()

◆ ocl_isExtremum()

◆ ocl_normalizeDescriptor()

◆ ocl_oriHist()

◆ ocl_ReleaseGaussianPyrBuffer()

◆ ocl_resizeHalf()

◆ ocl_scaleSpaceExtrema()

◆ ocl_scaleSpaceExtrema2()

Variable Documentation

◆ calcFeatureOrisKernel

◆ commandQueue

◆ computeDescriptorKernel

◆ context

◆ cvtGrayNormKernel

◆ devices

◆ errNum

◆ gaussianKernel

◆ oclgKernel

◆ platformChooser

◆ platforms

◆ program

◆ resizeKernel

◆ scaleSpaceExtremaKernel