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Remove all using directives for STL namespace and members

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Made all STL usages explicit to be able automatically find all usages of
particular class or function.
This commit is contained in:
Andrey Kamaev
2013-02-24 20:14:01 +04:00
parent f783f34e0b
commit 2a6fb2867e
310 changed files with 5744 additions and 5964 deletions
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modules/imgproc/src/hough.cpp
+21 -21
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@@ -60,7 +60,7 @@ struct hough_cmp_gt
const int* aux;
};
/*
Here image is an input raster;
step is it's step; size characterizes it's ROI;
@@ -72,7 +72,7 @@ Functions return the actual number of found lines.
*/
static void
HoughLinesStandard( const Mat& img, float rho, float theta,
int threshold, vector<Vec2f>& lines, int linesMax )
int threshold, std::vector<Vec2f>& lines, int linesMax )
{
int i, j;
float irho = 1 / rho;
@@ -88,7 +88,7 @@ HoughLinesStandard( const Mat& img, float rho, float theta,
int numrho = cvRound(((width + height) * 2 + 1) / rho);
AutoBuffer<int> _accum((numangle+2) * (numrho+2));
vector<int> _sort_buf;
std::vector<int> _sort_buf;
AutoBuffer<float> _tabSin(numangle);
AutoBuffer<float> _tabCos(numangle);
int *accum = _accum;
@@ -131,7 +131,7 @@ HoughLinesStandard( const Mat& img, float rho, float theta,
cv::sort(_sort_buf, hough_cmp_gt(accum));
// stage 4. store the first min(total,linesMax) lines to the output buffer
linesMax = min(linesMax, (int)_sort_buf.size());
linesMax = std::min(linesMax, (int)_sort_buf.size());
double scale = 1./(numrho+2);
for( i = 0; i < linesMax; i++ )
{
@@ -153,17 +153,17 @@ struct hough_index
hough_index() : value(0), rho(0.f), theta(0.f) {}
hough_index(int _val, float _rho, float _theta)
: value(_val), rho(_rho), theta(_theta) {}
int value;
float rho, theta;
};
static void
HoughLinesSDiv( const Mat& img,
float rho, float theta, int threshold,
int srn, int stn,
vector<Vec2f>& lines, int linesMax )
std::vector<Vec2f>& lines, int linesMax )
{
#define _POINT(row, column)\
(image_src[(row)*step+(column)])
@@ -183,7 +183,7 @@ HoughLinesSDiv( const Mat& img,
int count;
int cmax = 0;
vector<hough_index> lst;
std::vector<hough_index> lst;
CV_Assert( img.type() == CV_8UC1 );
CV_Assert( linesMax > 0 && rho > 0 && theta > 0 );
@@ -202,19 +202,19 @@ HoughLinesSDiv( const Mat& img,
float isrho = 1 / srho;
float istheta = 1 / stheta;
int rn = cvFloor( sqrt( (double)w * w + (double)h * h ) * irho );
int rn = cvFloor( std::sqrt( (double)w * w + (double)h * h ) * irho );
int tn = cvFloor( 2 * CV_PI * itheta );
lst.push_back(hough_index(threshold, -1.f, 0.f));
// Precalculate sin table
vector<float> _sinTable( 5 * tn * stn );
std::vector<float> _sinTable( 5 * tn * stn );
float* sinTable = &_sinTable[0];
for( index = 0; index < 5 * tn * stn; index++ )
sinTable[index] = (float)cos( stheta * index * 0.2f );
vector<uchar> _caccum(rn * tn, (uchar)0);
std::vector<uchar> _caccum(rn * tn, (uchar)0);
uchar* caccum = &_caccum[0];
// Counting all feature pixels
@@ -222,7 +222,7 @@ HoughLinesSDiv( const Mat& img,
for( col = 0; col < w; col++ )
fn += _POINT( row, col ) != 0;
vector<int> _x(fn), _y(fn);
std::vector<int> _x(fn), _y(fn);
int* x = &_x[0], *y = &_y[0];
// Full Hough Transform (it's accumulator update part)
@@ -250,7 +250,7 @@ HoughLinesSDiv( const Mat& img,
/* Update the accumulator */
t = (float) fabs( cvFastArctan( yc, xc ) * d2r );
r = (float) sqrt( (double)xc * xc + (double)yc * yc );
r = (float) std::sqrt( (double)xc * xc + (double)yc * yc );
r0 = r * irho;
ti0 = cvFloor( (t + CV_PI*0.5) * itheta );
@@ -294,7 +294,7 @@ HoughLinesSDiv( const Mat& img,
return;
}
vector<uchar> _buffer(srn * stn + 2);
std::vector<uchar> _buffer(srn * stn + 2);
uchar* buffer = &_buffer[0];
uchar* mcaccum = buffer + 1;
@@ -318,7 +318,7 @@ HoughLinesSDiv( const Mat& img,
// Update the accumulator
t = (float) fabs( cvFastArctan( yc, xc ) * d2r );
r = (float) sqrt( (double)xc * xc + (double)yc * yc ) * isrho;
r = (float) std::sqrt( (double)xc * xc + (double)yc * yc ) * isrho;
ti0 = cvFloor( (t + CV_PI * 0.5) * istheta );
ti2 = (ti * stn - ti0) * 5;
r0 = (float) ri *srn;
@@ -379,7 +379,7 @@ static void
HoughLinesProbabilistic( Mat& image,
float rho, float theta, int threshold,
int lineLength, int lineGap,
vector<Vec4i>& lines, int linesMax )
std::vector<Vec4i>& lines, int linesMax )
{
Point pt;
float irho = 1 / rho;
@@ -395,7 +395,7 @@ HoughLinesProbabilistic( Mat& image,
Mat accum = Mat::zeros( numangle, numrho, CV_32SC1 );
Mat mask( height, width, CV_8UC1 );
vector<float> trigtab(numangle*2);
std::vector<float> trigtab(numangle*2);
for( int n = 0; n < numangle; n++ )
{
@@ -404,7 +404,7 @@ HoughLinesProbabilistic( Mat& image,
}
const float* ttab = &trigtab[0];
uchar* mdata0 = mask.data;
vector<Point> nzloc;
std::vector<Point> nzloc;
// stage 1. collect non-zero image points
for( pt.y = 0; pt.y < height; pt.y++ )
@@ -601,7 +601,7 @@ void cv::HoughLines( InputArray _image, OutputArray _lines,
double srn, double stn )
{
Mat image = _image.getMat();
vector<Vec2f> lines;
std::vector<Vec2f> lines;
if( srn == 0 && stn == 0 )
HoughLinesStandard(image, (float)rho, (float)theta, threshold, lines, INT_MAX);
@@ -617,7 +617,7 @@ void cv::HoughLinesP(InputArray _image, OutputArray _lines,
double minLineLength, double maxGap )
{
Mat image = _image.getMat();
vector<Vec4i> lines;
std::vector<Vec4i> lines;
HoughLinesProbabilistic(image, (float)rho, (float)theta, threshold, cvRound(minLineLength), cvRound(maxGap), lines, INT_MAX);
Mat(lines).copyTo(_lines);
}
@@ -806,7 +806,7 @@ icvHoughCirclesGradient( CvMat* img, float dp, float min_dist,
if( !edges_row[x] || (vx == 0 && vy == 0) )
continue;
float mag = sqrt(vx*vx+vy*vy);
float mag = std::sqrt(vx*vx+vy*vy);
assert( mag >= 1 );
sx = cvRound((vx*idp)*ONE/mag);
sy = cvRound((vy*idp)*ONE/mag);