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Use new opencv includes #5

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30 changes: 15 additions & 15 deletions affine.h
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Original file line number Diff line number Diff line change
Expand Up @@ -4,14 +4,14 @@
*
* This file is part of the HessianAffine detector and is made available under
* the terms of the BSD license (see the COPYING file).
*
*
*/

#ifndef __AFFINE_H__
#define __AFFINE_H__

#include <vector>
#include <cv.h>
#include <opencv2/opencv.hpp>
#include "helpers.h"

struct AffineShapeParams
Expand All @@ -22,7 +22,7 @@ struct AffineShapeParams
// convergence threshold, i.e. maximum deviation from isotropic shape at convergence
float convergenceThreshold;

// widht and height of the SMM mask
// widht and height of the SMM mask
int smmWindowSize;

// width and height of the patch
Expand Down Expand Up @@ -52,34 +52,34 @@ struct AffineShapeCallback
float x, float y, // subpixel, image coordinates
float s, // scale
float pixelDistance, // distance between pixels in provided blured image
float a11, float a12, // affine shape matrix
float a21, float a22,
float a11, float a12, // affine shape matrix
float a21, float a22,
int type, float response, int iters) = 0;
};

struct AffineShape
{
public:
AffineShape(const AffineShapeParams &par) :
public:
AffineShape(const AffineShapeParams &par) :
patch(par.patchSize, par.patchSize, CV_32FC1),
mask(par.smmWindowSize, par.smmWindowSize, CV_32FC1),
img(par.smmWindowSize, par.smmWindowSize, CV_32FC1),
fx(par.smmWindowSize, par.smmWindowSize, CV_32FC1),
mask(par.smmWindowSize, par.smmWindowSize, CV_32FC1),
img(par.smmWindowSize, par.smmWindowSize, CV_32FC1),
fx(par.smmWindowSize, par.smmWindowSize, CV_32FC1),
fy(par.smmWindowSize, par.smmWindowSize, CV_32FC1)
{
{
this->par = par;
computeGaussMask(mask);
affineShapeCallback = 0;
fx = cv::Scalar(0);
fy = cv::Scalar(0);
}

~AffineShape()
{
}
// computes affine shape
bool findAffineShape(const cv::Mat &blur, float x, float y, float s, float pixelDistance, int type, float response);

// computes affine shape
bool findAffineShape(const cv::Mat &blur, float x, float y, float s, float pixelDistance, int type, float response);

// fills patch with affine normalized neighbourhood around point in the img, enlarged mrSize times
bool normalizeAffine(const cv::Mat &img, float x, float y, float s, float a11, float a12, float a21, float a22);
Expand Down
102 changes: 51 additions & 51 deletions helpers.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -4,12 +4,12 @@
*
* This file is part of the HessianAffine detector and is made available under
* the terms of the BSD license (see the COPYING file).
*
*
*/

#include <cmath>
#include <iostream>
#include <cv.h>
#include <opencv2/opencv.hpp>

using namespace cv;
using namespace std;
Expand All @@ -21,14 +21,14 @@ using namespace std;
#include <stdio.h>

double getTime()
{
#ifdef _POSIX_CPUTIME
{
#ifdef _POSIX_CPUTIME
struct timespec ts;
if (!clock_gettime(CLOCK_PROCESS_CPUTIME_ID, &ts))
{
return (double)(ts.tv_sec) + (double)(ts.tv_nsec)/1.0e9;
} else
#endif
#endif
{
// fall back to standard unix time
struct timeval tv;
Expand All @@ -48,34 +48,34 @@ void solveLinear3x3(float *A, float *b)
// find pivot of first column
int i = 0;
float *pr = A;
float vp = abs(A[0]);
float tmp = abs(A[3]);
if (tmp > vp)
{
float vp = abs(A[0]);
float tmp = abs(A[3]);
if (tmp > vp)
{
// pivot is in 1st row
pr = A+3;
i = 1;
vp = tmp;
pr = A+3;
i = 1;
vp = tmp;
}
if (abs(A[6]) > vp)
{
if (abs(A[6]) > vp)
{
// pivot is in 2nd row
pr = A+6;
i = 2;
}

// swap pivot row with first row
if (pr != A) { swap(pr, A); swap(pr+1, A+1); swap(pr+2, A+2); swap(b+i, b); }

// fixup elements 3,4,5,b[1]
vp = A[3] / A[0]; A[4] -= vp*A[1]; A[5] -= vp*A[2]; b[1] -= vp*b[0];

// fixup elements 6,7,8,b[2]]
vp = A[6] / A[0]; A[7] -= vp*A[1]; A[8] -= vp*A[2]; b[2] -= vp*b[0];

// find pivot in second column
if (abs(A[4]) < abs(A[7])) { swap(A+7, A+4); swap(A+8, A+5); swap(b+2, b+1); }

// fixup elements 7,8,b[2]
vp = A[7] / A[4];
A[8] -= vp*A[5];
Expand All @@ -89,11 +89,11 @@ void solveLinear3x3(float *A, float *b)

void rectifyAffineTransformationUpIsUp(float &a11, float &a12, float &a21, float &a22)
{
double a = a11, b = a12, c = a21, d = a22;
double a = a11, b = a12, c = a21, d = a22;
double det = sqrt(abs(a*d-b*c));
double b2a2 = sqrt(b*b + a*a);
a11 = b2a2/det; a12 = 0;
a21 = (d*b+c*a)/(b2a2*det); a22 = det/b2a2;
a21 = (d*b+c*a)/(b2a2*det); a22 = det/b2a2;
}

void rectifyAffineTransformationUpIsUp(float *U)
Expand All @@ -107,22 +107,22 @@ void computeGaussMask(Mat &mask)
int halfSize = size >> 1;
// fit 3*sigma into half_size
float scale = float(halfSize)/3.0f;
float scale2 = -2.0f * scale * scale;

float scale2 = -2.0f * scale * scale;
float *tmp = new float[halfSize+1];
for (int i = 0; i<= halfSize; i++)
tmp[i] = exp((float(i*i)/scale2));

int endSize = int(ceil(scale*5.0f)-halfSize);
for (int i = 1; i< endSize; i++)
tmp[halfSize-i] += exp((float((i+halfSize)*(i+halfSize))/scale2));

for (int i=0; i<=halfSize; i++)
for (int j=0; j<=halfSize; j++)
{
mask.at<float> ( i+halfSize,-j+halfSize) =
mask.at<float>(-i+halfSize, j+halfSize) =
mask.at<float>( i+halfSize, j+halfSize) =
mask.at<float> ( i+halfSize,-j+halfSize) =
mask.at<float>(-i+halfSize, j+halfSize) =
mask.at<float>( i+halfSize, j+halfSize) =
mask.at<float>(-i+halfSize,-j+halfSize) = tmp[i]*tmp[j];
}
delete [] tmp;
Expand All @@ -144,7 +144,7 @@ void computeCircularGaussMask(Mat &mask)
disq = float((i-halfSize)*(i-halfSize)+(j-halfSize)*(j-halfSize));
*mp++ = (disq < r2) ? exp(- disq / sigma2) : 0;
}
}
}

void invSqrt(float &a, float &b, float &c, float &l1, float &l2)
{
Expand All @@ -160,10 +160,10 @@ void invSqrt(float &a, float &b, float &c, float &l1, float &l2)
t = 0;
}
double x,z,d;

x = 1.0/sqrt(r*r*a-2*r*t*b+t*t*c);
z = 1.0/sqrt(t*t*a+2*r*t*b+r*r*c);

d = sqrt(x*z);
x /= d; z /= d;
// let l1 be the greater eigenvalue
Expand All @@ -173,23 +173,23 @@ void invSqrt(float &a, float &b, float &c, float &l1, float &l2)
b = float(-r*t*x+t*r*z);
c = float( t*t*x+r*r*z);
}

bool getEigenvalues(float a, float b, float c, float d, float &l1, float &l2)
{
float trace = a+d;
float delta1 = (trace*trace-4*(a*d-b*c));
float delta1 = (trace*trace-4*(a*d-b*c));
if (delta1 < 0)
return false;
float delta = sqrt(delta1);

l1 = (trace+delta)/2.0f;
l2 = (trace-delta)/2.0f;
return true;
}

// check if we are not too close to boundary of the image/
bool interpolateCheckBorders(const Mat &im, float ofsx, float ofsy, float a11, float a12, float a21, float a22, const Mat &res)
{
{
const int width = im.cols-2;
const int height = im.rows-2;
const int halfWidth = res.cols >> 1;
Expand All @@ -207,7 +207,7 @@ bool interpolateCheckBorders(const Mat &im, float ofsx, float ofsy, float a11, f
}

bool interpolate(const Mat &im, float ofsx, float ofsy, float a11, float a12, float a21, float a22, Mat &res)
{
{
bool ret = false;
// input size (-1 for the safe bilinear interpolation)
const int width = im.cols-1;
Expand All @@ -231,34 +231,34 @@ bool interpolate(const Mat &im, float ofsx, float ofsy, float a11, float a12, fl
// compute weights
wx -= x; wy -= y;
// bilinear interpolation
*out++ =
*out++ =
(1.0f - wy) * ((1.0f - wx) * im.at<float>(y,x) + wx * im.at<float>(y,x+1)) +
( wy) * ((1.0f - wx) * im.at<float>(y+1,x) + wx * im.at<float>(y+1,x+1));
} else {
*out++ = 0;
ret = true; // touching boundary of the input
ret = true; // touching boundary of the input
}
}
}
return ret;
}

void photometricallyNormalize(Mat &image, const Mat &binaryMask, float &sum, float &var)
{
{
const int width = image.cols;
const int height = image.rows;
sum=0;
float gsum=0;
float gsum=0;

for (int j=0; j < height; j++)
for (int i=0; i < width; i++)
if (binaryMask.at<float>(j,i)>0)
{
sum += image.at<float>(j,i);
sum += image.at<float>(j,i);
gsum ++;
}
sum = sum / gsum;

var=0;
for (int j=0; j < height; j++)
for (int i=0; i < width; i++)
Expand All @@ -270,10 +270,10 @@ void photometricallyNormalize(Mat &image, const Mat &binaryMask, float &sum, flo
// if variance is too low, don't do anything
return;

float fac = 50.0f/var;
float fac = 50.0f/var;
for (int j=0; j < height; j++)
for (int i=0; i < width; i++)
{
{
image.at<float>(j,i) = 128 + fac * (image.at<float>(j,i) - sum);
if (image.at<float>(j,i) > 255) image.at<float>(j,i)=255;
if (image.at<float>(j,i) < 0) image.at<float>(j,i)=0;
Expand All @@ -283,26 +283,26 @@ void photometricallyNormalize(Mat &image, const Mat &binaryMask, float &sum, flo
Mat gaussianBlur(const Mat input, float sigma)
{
Mat ret(input.rows, input.cols, input.type());
int size = (int)(2.0 * 3.0 * sigma + 1.0); if (size % 2 == 0) size++;
int size = (int)(2.0 * 3.0 * sigma + 1.0); if (size % 2 == 0) size++;
GaussianBlur(input, ret, Size(size, size), sigma, sigma, BORDER_REPLICATE);
return ret;
}

void gaussianBlurInplace(Mat &inplace, float sigma)
{
int size = (int)(2.0 * 3.0 * sigma + 1.0); if (size % 2 == 0) size++;
int size = (int)(2.0 * 3.0 * sigma + 1.0); if (size % 2 == 0) size++;
GaussianBlur(inplace, inplace, Size(size, size), sigma, sigma, BORDER_REPLICATE);
}

Mat doubleImage(const Mat &input)
{
Mat n(input.rows*2, input.cols*2, input.type());
const float *in = input.ptr<float>(0);

for (int r = 0; r < input.rows-1; r++)
for (int c = 0; c < input.cols-1; c++)
for (int c = 0; c < input.cols-1; c++)
{
const int r2 = r << 1;
const int r2 = r << 1;
const int c2 = c << 1;
n.at<float>(r2,c2) = in[0];
n.at<float>(r2+1,c2) = 0.5f *(in[0]+in[input.step]);
Expand All @@ -312,14 +312,14 @@ Mat doubleImage(const Mat &input)
}
for (int r = 0; r < input.rows-1; r++)
{
const int r2 = r << 1;
const int r2 = r << 1;
const int c2 = (input.cols-1) << 1;
n.at<float>(r2,c2) = input.at<float>(r,input.cols-1);
n.at<float>(r2+1,c2) = 0.5f*(input.at<float>(r,input.cols-1) + input.at<float>(r+1,input.cols-1));
}
for (int c = 0; c < input.cols - 1; c++)
for (int c = 0; c < input.cols - 1; c++)
{
const int r2 = (input.rows-1) << 1;
const int r2 = (input.rows-1) << 1;
const int c2 = c << 1;
n.at<float>(r2,c2) = input.at<float>(input.rows-1,c);
n.at<float>(r2,c2+1) = 0.5f*(input.at<float>(input.rows-1,c) + input.at<float>(input.rows-1,c+1));
Expand Down
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