generic-library/opencv
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

Fixed windows build of FREAK

Browse Source
This commit is contained in:
Andrey Kamaev 2012-06-24 14:33:30 +00:00
parent bd901eb52d
commit 84d62b69dc
1 changed files with 28 additions and 28 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

26
modules/features2d/src/freak.cpp
View File

@ -151,17 +151,17 @@ void FREAK::buildPattern()
PatternPoint* patternLookupPtr = &patternLookup[0];
for( size_t i = 0; i < 8; ++i ) {
for( int k = 0 ; k < n[i]; ++k ) {
beta = M_PI/n[i] * (i%2); // orientation offset so that groups of points on each circles are staggered
alpha = double(k)* 2*M_PI/double(n[i])+beta+theta;
beta = CV_PI/n[i] * (i%2); // orientation offset so that groups of points on each circles are staggered
alpha = double(k)* 2*CV_PI/double(n[i])+beta+theta;
// add the point to the look-up table
PatternPoint& point = patternLookupPtr[ scaleIdx*FREAK_NB_ORIENTATION*FREAK_NB_POINTS+orientationIdx*FREAK_NB_POINTS+pointIdx ];
point.x = radius[i] * cos(alpha) * scalingFactor * patternScale;
point.y = radius[i] * sin(alpha) * scalingFactor * patternScale;
point.sigma = sigma[i] * scalingFactor * patternScale;
point.x = static_cast<float>(radius[i] * cos(alpha) * scalingFactor * patternScale);
point.y = static_cast<float>(radius[i] * sin(alpha) * scalingFactor * patternScale);
point.sigma = static_cast<float>(sigma[i] * scalingFactor * patternScale);
// adapt the sizeList if necessary
const int sizeMax = ceil((radius[i]+sigma[i])*scalingFactor*patternScale) + 1;
const int sizeMax = static_cast<int>(ceil((radius[i]+sigma[i])*scalingFactor*patternScale)) + 1;
if( patternSizes[scaleIdx] < sizeMax )
patternSizes[scaleIdx] = sizeMax;
@ -246,7 +246,7 @@ void FREAK::computeImpl( const Mat& image, std::vector<KeyPoint>& keypoints, Mat
std::vector<int> kpScaleIdx(keypoints.size()); // used to save pattern scale index corresponding to each keypoints
const std::vector<int>::iterator ScaleIdxBegin = kpScaleIdx.begin(); // used in std::vector erase function
const std::vector<cv::KeyPoint>::iterator kpBegin = keypoints.begin(); // used in std::vector erase function
const float sizeCst = FREAK_NB_SCALES/(FREAK_LOG2* nOctaves );
const float sizeCst = static_cast<float>(FREAK_NB_SCALES/(FREAK_LOG2* nOctaves));
uchar pointsValue[FREAK_NB_POINTS];
int thetaIdx = 0;
int direction0;
@ -317,7 +317,7 @@ void FREAK::computeImpl( const Mat& image, std::vector<KeyPoint>& keypoints, Mat
direction1 += delta*(orientationPairs[m].weight_dy)/2048;
}
keypoints[k].angle = atan2((float)direction1,(float)direction0)*(180.0/M_PI);//estimate orientation
keypoints[k].angle = static_cast<float>(atan2((float)direction1,(float)direction0)*(180.0/CV_PI));//estimate orientation
thetaIdx = int(FREAK_NB_ORIENTATION*keypoints[k].angle*(1/360.0)+0.5);
if( thetaIdx < 0 )
thetaIdx += FREAK_NB_ORIENTATION;
@ -388,7 +388,7 @@ void FREAK::computeImpl( const Mat& image, std::vector<KeyPoint>& keypoints, Mat
direction1 += delta*(orientationPairs[m].weight_dy)/2048;
}
keypoints[k].angle = atan2((float)direction1,(float)direction0)*(180.0/M_PI); //estimate orientation
keypoints[k].angle = static_cast<float>(atan2((float)direction1,(float)direction0)*(180.0/CV_PI)); //estimate orientation
thetaIdx = int(FREAK_NB_ORIENTATION*keypoints[k].angle*(1/360.0)+0.5);
if( thetaIdx < 0 )
@ -438,8 +438,8 @@ uchar FREAK::meanIntensity( const cv::Mat& image, const cv::Mat& integral,
int ret_val;
if( radius < 0.5 ) {
// interpolation multipliers:
const int r_x = (xf-x)*1024;
const int r_y = (yf-y)*1024;
const int r_x = static_cast<int>((xf-x)*1024);
const int r_y = static_cast<int>((yf-y)*1024);
const int r_x_1 = (1024-r_x);
const int r_y_1 = (1024-r_y);
uchar* ptr = image.data+x+y*imagecols;
@ -451,7 +451,7 @@ uchar FREAK::meanIntensity( const cv::Mat& image, const cv::Mat& integral,
ret_val += (r_x*r_y*int(*ptr));
ptr--;
ret_val += (r_x_1*r_y*int(*ptr));
return (ret_val+512)/1024;
return static_cast<uchar>((ret_val+512)/1024);
}
// expected case:
@ -468,7 +468,7 @@ uchar FREAK::meanIntensity( const cv::Mat& image, const cv::Mat& integral,
ret_val -= integral.at<int>(y_top,x_right);
ret_val = ret_val/( (x_right-x_left)* (y_bottom-y_top) );
//~ std::cout<<integral.step[1]<<std::endl;
return ret_val;
return static_cast<uchar>(ret_val);
}
// pair selection algorithm from a set of training images and corresponding keypoints