Remove all using directives for STL namespace and members

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

View File

@@ -114,8 +114,8 @@ static void calcPixelCostBT( const Mat& img1, const Mat& img2, int y,
int tabOfs, int )
{
int x, c, width = img1.cols, cn = img1.channels();
int minX1 = max(maxD, 0), maxX1 = width + min(minD, 0);
int minX2 = max(minX1 - maxD, 0), maxX2 = min(maxX1 - minD, width);
int minX1 = std::max(maxD, 0), maxX1 = width + std::min(minD, 0);
int minX2 = std::max(minX1 - maxD, 0), maxX2 = std::min(maxX1 - minD, width);
int D = maxD - minD, width1 = maxX1 - minX1, width2 = maxX2 - minX2;
const PixType *row1 = img1.ptr<PixType>(y), *row2 = img2.ptr<PixType>(y);
PixType *prow1 = buffer + width2*2, *prow2 = prow1 + width*cn*2;
@@ -186,8 +186,8 @@ static void calcPixelCostBT( const Mat& img1, const Mat& img2, int y,
int v = prow2[x];
int vl = x > 0 ? (v + prow2[x-1])/2 : v;
int vr = x < width-1 ? (v + prow2[x+1])/2 : v;
int v0 = min(vl, vr); v0 = min(v0, v);
int v1 = max(vl, vr); v1 = max(v1, v);
int v0 = std::min(vl, vr); v0 = std::min(v0, v);
int v1 = std::max(vl, vr); v1 = std::max(v1, v);
buffer[x] = (PixType)v0;
buffer[x + width2] = (PixType)v1;
}
@@ -197,8 +197,8 @@ static void calcPixelCostBT( const Mat& img1, const Mat& img2, int y,
int u = prow1[x];
int ul = x > 0 ? (u + prow1[x-1])/2 : u;
int ur = x < width-1 ? (u + prow1[x+1])/2 : u;
int u0 = min(ul, ur); u0 = min(u0, u);
int u1 = max(ul, ur); u1 = max(u1, u);
int u0 = std::min(ul, ur); u0 = std::min(u0, u);
int u1 = std::max(ul, ur); u1 = std::max(u1, u);
#if CV_SSE2
if( useSIMD )
@@ -231,10 +231,10 @@ static void calcPixelCostBT( const Mat& img1, const Mat& img2, int y,
int v = prow2[width-x-1 + d];
int v0 = buffer[width-x-1 + d];
int v1 = buffer[width-x-1 + d + width2];
int c0 = max(0, u - v1); c0 = max(c0, v0 - u);
int c1 = max(0, v - u1); c1 = max(c1, u0 - v);
int c0 = std::max(0, u - v1); c0 = std::max(c0, v0 - u);
int c1 = std::max(0, v - u1); c1 = std::max(c1, u0 - v);
cost[x*D + d] = (CostType)(cost[x*D+d] + (min(c0, c1) >> diff_scale));
cost[x*D + d] = (CostType)(cost[x*D+d] + (std::min(c0, c1) >> diff_scale));
}
}
}
@@ -324,12 +324,12 @@ static void computeDisparitySGBM( const Mat& img1, const Mat& img2,
int minD = params.minDisparity, maxD = minD + params.numberOfDisparities;
Size SADWindowSize;
SADWindowSize.width = SADWindowSize.height = params.SADWindowSize > 0 ? params.SADWindowSize : 5;
int ftzero = max(params.preFilterCap, 15) | 1;
int ftzero = std::max(params.preFilterCap, 15) | 1;
int uniquenessRatio = params.uniquenessRatio >= 0 ? params.uniquenessRatio : 10;
int disp12MaxDiff = params.disp12MaxDiff > 0 ? params.disp12MaxDiff : 1;
int P1 = params.P1 > 0 ? params.P1 : 2, P2 = max(params.P2 > 0 ? params.P2 : 5, P1+1);
int P1 = params.P1 > 0 ? params.P1 : 2, P2 = std::max(params.P2 > 0 ? params.P2 : 5, P1+1);
int k, width = disp1.cols, height = disp1.rows;
int minX1 = max(maxD, 0), maxX1 = width + min(minD, 0);
int minX1 = std::max(maxD, 0), maxX1 = width + std::min(minD, 0);
int D = maxD - minD, width1 = maxX1 - minX1;
int INVALID_DISP = minD - 1, INVALID_DISP_SCALED = INVALID_DISP*DISP_SCALE;
int SW2 = SADWindowSize.width/2, SH2 = SADWindowSize.height/2;
@@ -338,7 +338,7 @@ static void computeDisparitySGBM( const Mat& img1, const Mat& img2,
PixType clipTab[TAB_SIZE];
for( k = 0; k < TAB_SIZE; k++ )
clipTab[k] = (PixType)(min(max(k - TAB_OFS, -ftzero), ftzero) + ftzero);
clipTab[k] = (PixType)(std::min(std::max(k - TAB_OFS, -ftzero), ftzero) + ftzero);
if( minX1 >= maxX1 )
{
@@ -432,7 +432,7 @@ static void computeDisparitySGBM( const Mat& img1, const Mat& img2,
for( k = dy1; k <= dy2; k++ )
{
CostType* hsumAdd = hsumBuf + (min(k, height-1) % hsumBufNRows)*costBufSize;
CostType* hsumAdd = hsumBuf + (std::min(k, height-1) % hsumBufNRows)*costBufSize;
if( k < height )
{
@@ -448,13 +448,13 @@ static void computeDisparitySGBM( const Mat& img1, const Mat& img2,
if( y > 0 )
{
const CostType* hsumSub = hsumBuf + (max(y - SH2 - 1, 0) % hsumBufNRows)*costBufSize;
const CostType* hsumSub = hsumBuf + (std::max(y - SH2 - 1, 0) % hsumBufNRows)*costBufSize;
const CostType* Cprev = !params.fullDP || y == 0 ? C : C - costBufSize;
for( x = D; x < width1*D; x += D )
{
const CostType* pixAdd = pixDiff + min(x + SW2*D, (width1-1)*D);
const CostType* pixSub = pixDiff + max(x - (SW2+1)*D, 0);
const CostType* pixAdd = pixDiff + std::min(x + SW2*D, (width1-1)*D);
const CostType* pixSub = pixDiff + std::max(x - (SW2+1)*D, 0);
#if CV_SSE2
if( useSIMD )
@@ -488,8 +488,8 @@ static void computeDisparitySGBM( const Mat& img1, const Mat& img2,
{
for( x = D; x < width1*D; x += D )
{
const CostType* pixAdd = pixDiff + min(x + SW2*D, (width1-1)*D);
const CostType* pixSub = pixDiff + max(x - (SW2+1)*D, 0);
const CostType* pixAdd = pixDiff + std::min(x + SW2*D, (width1-1)*D);
const CostType* pixSub = pixDiff + std::max(x - (SW2+1)*D, 0);
for( d = 0; d < D; d++ )
hsumAdd[x + d] = (CostType)(hsumAdd[x - D + d] + pixAdd[d] - pixSub[d]);
@@ -630,22 +630,22 @@ static void computeDisparitySGBM( const Mat& img1, const Mat& img2,
{
int Cpd = Cp[d], L0, L1, L2, L3;
L0 = Cpd + min((int)Lr_p0[d], min(Lr_p0[d-1] + P1, min(Lr_p0[d+1] + P1, delta0))) - delta0;
L1 = Cpd + min((int)Lr_p1[d], min(Lr_p1[d-1] + P1, min(Lr_p1[d+1] + P1, delta1))) - delta1;
L2 = Cpd + min((int)Lr_p2[d], min(Lr_p2[d-1] + P1, min(Lr_p2[d+1] + P1, delta2))) - delta2;
L3 = Cpd + min((int)Lr_p3[d], min(Lr_p3[d-1] + P1, min(Lr_p3[d+1] + P1, delta3))) - delta3;
L0 = Cpd + std::min((int)Lr_p0[d], std::min(Lr_p0[d-1] + P1, std::min(Lr_p0[d+1] + P1, delta0))) - delta0;
L1 = Cpd + std::min((int)Lr_p1[d], std::min(Lr_p1[d-1] + P1, std::min(Lr_p1[d+1] + P1, delta1))) - delta1;
L2 = Cpd + std::min((int)Lr_p2[d], std::min(Lr_p2[d-1] + P1, std::min(Lr_p2[d+1] + P1, delta2))) - delta2;
L3 = Cpd + std::min((int)Lr_p3[d], std::min(Lr_p3[d-1] + P1, std::min(Lr_p3[d+1] + P1, delta3))) - delta3;
Lr_p[d] = (CostType)L0;
minL0 = min(minL0, L0);
minL0 = std::min(minL0, L0);
Lr_p[d + D2] = (CostType)L1;
minL1 = min(minL1, L1);
minL1 = std::min(minL1, L1);
Lr_p[d + D2*2] = (CostType)L2;
minL2 = min(minL2, L2);
minL2 = std::min(minL2, L2);
Lr_p[d + D2*3] = (CostType)L3;
minL3 = min(minL3, L3);
minL3 = std::min(minL3, L3);
Sp[d] = saturate_cast<CostType>(Sp[d] + L0 + L1 + L2 + L3);
}
@@ -737,10 +737,10 @@ static void computeDisparitySGBM( const Mat& img1, const Mat& img2,
{
for( d = 0; d < D; d++ )
{
int L0 = Cp[d] + min((int)Lr_p0[d], min(Lr_p0[d-1] + P1, min(Lr_p0[d+1] + P1, delta0))) - delta0;
int L0 = Cp[d] + std::min((int)Lr_p0[d], std::min(Lr_p0[d-1] + P1, std::min(Lr_p0[d+1] + P1, delta0))) - delta0;
Lr_p[d] = (CostType)L0;
minL0 = min(minL0, L0);
minL0 = std::min(minL0, L0);
int Sval = Sp[d] = saturate_cast<CostType>(Sp[d] + L0);
if( Sval < minS )
@@ -785,7 +785,7 @@ static void computeDisparitySGBM( const Mat& img1, const Mat& img2,
// do subpixel quadratic interpolation:
// fit parabola into (x1=d-1, y1=Sp[d-1]), (x2=d, y2=Sp[d]), (x3=d+1, y3=Sp[d+1])
// then find minimum of the parabola.
int denom2 = max(Sp[d-1] + Sp[d+1] - 2*Sp[d], 1);
int denom2 = std::max(Sp[d-1] + Sp[d+1] - 2*Sp[d], 1);
d = d*DISP_SCALE + ((Sp[d-1] - Sp[d+1])*DISP_SCALE + denom2)/(denom2*2);
}
else
@@ -845,10 +845,10 @@ Rect getValidDisparityROI( Rect roi1, Rect roi2,
int SW2 = SADWindowSize/2;
int minD = minDisparity, maxD = minDisparity + numberOfDisparities - 1;
int xmin = max(roi1.x, roi2.x + maxD) + SW2;
int xmax = min(roi1.x + roi1.width, roi2.x + roi2.width - minD) - SW2;
int ymin = max(roi1.y, roi2.y) + SW2;
int ymax = min(roi1.y + roi1.height, roi2.y + roi2.height) - SW2;
int xmin = std::max(roi1.x, roi2.x + maxD) + SW2;
int xmax = std::min(roi1.x + roi1.width, roi2.x + roi2.width - minD) - SW2;
int ymin = std::max(roi1.y, roi2.y) + SW2;
int ymax = std::min(roi1.y + roi1.height, roi2.y + roi2.height) - SW2;
Rect r(xmin, ymin, xmax - xmin, ymax - ymin);
@@ -979,7 +979,7 @@ void cv::validateDisparity( InputOutputArray _disp, InputArray _cost, int minDis
Mat disp = _disp.getMat(), cost = _cost.getMat();
int cols = disp.cols, rows = disp.rows;
int minD = minDisparity, maxD = minDisparity + numberOfDisparities;
int x, minX1 = max(maxD, 0), maxX1 = cols + min(minD, 0);
int x, minX1 = std::max(maxD, 0), maxX1 = cols + std::min(minD, 0);
AutoBuffer<int> _disp2buf(cols*2);
int* disp2buf = _disp2buf;
int* disp2cost = disp2buf + cols;