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Merge remote-tracking branch 'origin/2.4' into merge-2.4

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Conflicts:
	.gitignore
	modules/contrib/src/detection_based_tracker.cpp
	modules/core/include/opencv2/core/core.hpp
	modules/core/include/opencv2/core/internal.hpp
	modules/core/src/gpumat.cpp
	modules/core/src/opengl.cpp
	modules/gpu/src/cuda/safe_call.hpp
	modules/highgui/src/cap.cpp
	modules/imgproc/include/opencv2/imgproc/imgproc.hpp
	modules/ocl/doc/image_processing.rst
	modules/ocl/include/opencv2/ocl/ocl.hpp
	modules/ocl/perf/perf_haar.cpp
	modules/ocl/src/haar.cpp
	modules/ocl/src/imgproc.cpp
	modules/ocl/src/kmeans.cpp
	modules/ocl/src/svm.cpp
	modules/ocl/test/test_objdetect.cpp
	samples/ocl/adaptive_bilateral_filter.cpp
This commit is contained in:
Roman Donchenko
2013-11-11 16:55:36 +04:00
parent 469d7eed72 0ac61240c5
commit 4f1aed98de
59 changed files with 961 additions and 755 deletions
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85
modules/imgproc/src/smooth.cpp
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@@ -2287,15 +2287,24 @@ void cv::bilateralFilter( InputArray _src, OutputArray _dst, int d,
namespace cv
{
#define CALCVAR 1
#define FIXED_WEIGHT 0
#ifndef ABF_CALCVAR
#define ABF_CALCVAR 1
#endif
#ifndef ABF_FIXED_WEIGHT
#define ABF_FIXED_WEIGHT 0
#endif
#ifndef ABF_GAUSSIAN
#define ABF_GAUSSIAN 1
#endif
class adaptiveBilateralFilter_8u_Invoker :
public ParallelLoopBody
{
public:
adaptiveBilateralFilter_8u_Invoker(Mat& _dest, const Mat& _temp, Size _ksize, double _sigma_space, Point _anchor) :
temp(&_temp), dest(&_dest), ksize(_ksize), sigma_space(_sigma_space), anchor(_anchor)
adaptiveBilateralFilter_8u_Invoker(Mat& _dest, const Mat& _temp, Size _ksize, double _sigma_space, double _maxSigmaColor, Point _anchor) :
temp(&_temp), dest(&_dest), ksize(_ksize), sigma_space(_sigma_space), maxSigma_Color(_maxSigmaColor), anchor(_anchor)
{
if( sigma_space <= 0 )
sigma_space = 1;
@@ -2308,7 +2317,11 @@ public:
for(int y=-h; y<=h; y++)
for(int x=-w; x<=w; x++)
{
#if ABF_GAUSSIAN
space_weight[idx++] = (float)exp ( -0.5*(x * x + y * y)/sigma2);
#else
space_weight[idx++] = (float)(sigma2 / (sigma2 + x * x + y * y));
#endif
}
}
virtual void operator()(const Range& range) const
@@ -2344,7 +2357,7 @@ public:
int startLMJ = 0;
int endLMJ = ksize.width - 1;
int howManyAll = (anX *2 +1)*(ksize.width );
#if CALCVAR
#if ABF_CALCVAR
for(int x = startLMJ; x< endLMJ; x++)
{
tptr = temp->ptr(startY + x) +j;
@@ -2356,8 +2369,14 @@ public:
}
}
var = ( (sumValSqr * howManyAll)- sumVal * sumVal ) / ( (float)(howManyAll*howManyAll));
if(var < 0.01)
var = 0.01f;
else if(var > (float)(maxSigma_Color*maxSigma_Color) )
var = (float)(maxSigma_Color*maxSigma_Color) ;
#else
var = 900.0;
var = maxSigmaColor*maxSigmaColor;
#endif
startLMJ = 0;
endLMJ = ksize.width;
@@ -2368,13 +2387,18 @@ public:
tptr = temp->ptr(startY + x) +j;
for(int y=-anX; y<=anX; y++)
{
#if FIXED_WEIGHT
#if ABF_FIXED_WEIGHT
weight = 1.0;
#else
currVal = tptr[cn*(y+anX)];
currWRTCenter = currVal - currValCenter;
weight = var / ( var + (currWRTCenter * currWRTCenter) ) * space_weight[x*ksize.width+y+anX];;
#if ABF_GAUSSIAN
weight = exp ( -0.5f * currWRTCenter * currWRTCenter/var ) * space_weight[x*ksize.width+y+anX];
#else
weight = var / ( var + (currWRTCenter * currWRTCenter) ) * space_weight[x*ksize.width+y+anX];
#endif
#endif
tmpSum += ((float)tptr[cn*(y+anX)] * weight);
totalWeight += weight;
@@ -2409,7 +2433,8 @@ public:
int startLMJ = 0;
int endLMJ = ksize.width - 1;
int howManyAll = (anX *2 +1)*(ksize.width);
#if CALCVAR
#if ABF_CALCVAR
float max_var = (float)( maxSigma_Color*maxSigma_Color);
for(int x = startLMJ; x< endLMJ; x++)
{
tptr = temp->ptr(startY + x) +j;
@@ -2424,11 +2449,27 @@ public:
sumValSqr_r += (currVal_r *currVal_r);
}
}
var_b = ( (sumValSqr_b * howManyAll)- sumVal_b * sumVal_b ) / ( (float)(howManyAll*howManyAll));
var_g = ( (sumValSqr_g * howManyAll)- sumVal_g * sumVal_g ) / ( (float)(howManyAll*howManyAll));
var_r = ( (sumValSqr_r * howManyAll)- sumVal_r * sumVal_r ) / ( (float)(howManyAll*howManyAll));
var_b = ( (sumValSqr_b * howManyAll)- sumVal_b * sumVal_b ) / ( (float)(howManyAll*howManyAll));
var_g = ( (sumValSqr_g * howManyAll)- sumVal_g * sumVal_g ) / ( (float)(howManyAll*howManyAll));
var_r = ( (sumValSqr_r * howManyAll)- sumVal_r * sumVal_r ) / ( (float)(howManyAll*howManyAll));
if(var_b < 0.01)
var_b = 0.01f;
else if(var_b > max_var )
var_b = (float)(max_var) ;
if(var_g < 0.01)
var_g = 0.01f;
else if(var_g > max_var )
var_g = (float)(max_var) ;
if(var_r < 0.01)
var_r = 0.01f;
else if(var_r > max_var )
var_r = (float)(max_var) ;
#else
var_b = 900.0; var_g = 900.0;var_r = 900.0;
var_b = maxSigma_Color*maxSigma_Color; var_g = maxSigma_Color*maxSigma_Color; var_r = maxSigma_Color*maxSigma_Color;
#endif
startLMJ = 0;
endLMJ = ksize.width;
@@ -2439,7 +2480,7 @@ public:
tptr = temp->ptr(startY + x) +j;
for(int y=-anX; y<=anX; y++)
{
#if FIXED_WEIGHT
#if ABF_FIXED_WEIGHT
weight_b = 1.0;
weight_g = 1.0;
weight_r = 1.0;
@@ -2450,9 +2491,16 @@ public:
currWRTCenter_r = currVal_r - currValCenter_r;
float cur_spw = space_weight[x*ksize.width+y+anX];
#if ABF_GAUSSIAN
weight_b = exp( -0.5f * currWRTCenter_b * currWRTCenter_b/ var_b ) * cur_spw;
weight_g = exp( -0.5f * currWRTCenter_g * currWRTCenter_g/ var_g ) * cur_spw;
weight_r = exp( -0.5f * currWRTCenter_r * currWRTCenter_r/ var_r ) * cur_spw;
#else
weight_b = var_b / ( var_b + (currWRTCenter_b * currWRTCenter_b) ) * cur_spw;
weight_g = var_g / ( var_g + (currWRTCenter_g * currWRTCenter_g) ) * cur_spw;
weight_r = var_r / ( var_r + (currWRTCenter_r * currWRTCenter_r) ) * cur_spw;
#endif
#endif
tmpSum_b += ((float)tptr[cn*(y+anX)] * weight_b);
tmpSum_g += ((float)tptr[cn*(y+anX)+1] * weight_g);
@@ -2476,10 +2524,11 @@ private:
Mat *dest;
Size ksize;
double sigma_space;
double maxSigma_Color;
Point anchor;
std::vector<float> space_weight;
};
static void adaptiveBilateralFilter_8u( const Mat& src, Mat& dst, Size ksize, double sigmaSpace, Point anchor, int borderType )
static void adaptiveBilateralFilter_8u( const Mat& src, Mat& dst, Size ksize, double sigmaSpace, double maxSigmaColor, Point anchor, int borderType )
{
Size size = src.size();
@@ -2489,12 +2538,12 @@ static void adaptiveBilateralFilter_8u( const Mat& src, Mat& dst, Size ksize, do
Mat temp;
copyMakeBorder(src, temp, anchor.x, anchor.y, anchor.x, anchor.y, borderType);
adaptiveBilateralFilter_8u_Invoker body(dst, temp, ksize, sigmaSpace, anchor);
adaptiveBilateralFilter_8u_Invoker body(dst, temp, ksize, sigmaSpace, maxSigmaColor, anchor);
parallel_for_(Range(0, size.height), body, dst.total()/(double)(1<<16));
}
}
void cv::adaptiveBilateralFilter( InputArray _src, OutputArray _dst, Size ksize,
double sigmaSpace, Point anchor, int borderType )
double sigmaSpace, double maxSigmaColor, Point anchor, int borderType )
{
Mat src = _src.getMat();
_dst.create(src.size(), src.type());
@@ -2504,7 +2553,7 @@ void cv::adaptiveBilateralFilter( InputArray _src, OutputArray _dst, Size ksize,
anchor = normalizeAnchor(anchor,ksize);
if( src.depth() == CV_8U )
adaptiveBilateralFilter_8u( src, dst, ksize, sigmaSpace, anchor, borderType );
adaptiveBilateralFilter_8u( src, dst, ksize, sigmaSpace, maxSigmaColor, anchor, borderType );
else
CV_Error( CV_StsUnsupportedFormat,
"Adaptive Bilateral filtering is only implemented for 8u images" );