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Reduced some tegra stubs

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This commit is contained in:
Andrey Kamaev 2012-06-14 14:09:04 +00:00
parent a98d6b6217
commit 913d4541a5
2 changed files with 56 additions and 160 deletions
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29
modules/imgproc/src/imgwarp.cpp
View File

@ -2839,6 +2839,11 @@ void cv::warpAffine( InputArray _src, OutputArray _dst,
CV_Assert( (M0.type() == CV_32F || M0.type() == CV_64F) && M0.rows == 2 && M0.cols == 3 );
M0.convertTo(matM, matM.type());
#ifdef HAVE_TEGRA_OPTIMIZATION
if( tegra::warpAffine(src, dst, M, flags, borderType, borderValue) )
return;
#endif
if( !(flags & WARP_INVERSE_MAP) )
{
double D = M[0]*M[4] - M[1]*M[3];
@ -2851,22 +2856,6 @@ void cv::warpAffine( InputArray _src, OutputArray _dst,
M[2] = b1; M[5] = b2;
}
#ifdef HAVE_TEGRA_OPTIMIZATION
if (borderType == BORDER_REPLICATE)
{
if( tegra::warpAffine(src, dst, M, interpolation, borderType, borderValue) )
return;
}
else
{
double warp_mat[6];
Mat warp_m(2, 3, CV_64F, warp_mat);
M0.convertTo(warp_m, warp_m.type());
if( tegra::warpAffine(src, dst, warp_mat, interpolation, borderType, borderValue) )
return;
}
#endif
int x, y, x1, y1, width = dst.cols, height = dst.rows;
AutoBuffer<int> _abdelta(width*2);
int* adelta = &_abdelta[0], *bdelta = adelta + width;
@ -2995,14 +2984,14 @@ void cv::warpPerspective( InputArray _src, OutputArray _dst, InputArray _M0,
CV_Assert( (M0.type() == CV_32F || M0.type() == CV_64F) && M0.rows == 3 && M0.cols == 3 );
M0.convertTo(matM, matM.type());
if( !(flags & WARP_INVERSE_MAP) )
invert(matM, matM);
#ifdef HAVE_TEGRA_OPTIMIZATION
if( tegra::warpPerspective(src, dst, M, interpolation, borderType, borderValue) )
if( tegra::warpPerspective(src, dst, M, flags, borderType, borderValue) )
return;
#endif
if( !(flags & WARP_INVERSE_MAP) )
invert(matM, matM);
int x, y, x1, y1, width = dst.cols, height = dst.rows;
int bh0 = std::min(BLOCK_SZ/2, height);

187
modules/imgproc/src/thresh.cpp
View File

@ -60,41 +60,10 @@ thresh_8u( const Mat& _src, Mat& _dst, uchar thresh, uchar maxval, int type )
}
#ifdef HAVE_TEGRA_OPTIMIZATION
switch( type )
{
case THRESH_BINARY:
if(tegra::thresh_8u_binary(_src, _dst, roi.width, roi.height, thresh, maxval))
{
return;
}
break;
case THRESH_BINARY_INV:
if(tegra::thresh_8u_binary_inv(_src, _dst, roi.width, roi.height, thresh, maxval))
{
return;
}
break;
case THRESH_TRUNC:
if(tegra::thresh_8u_trunc(_src, _dst, roi.width, roi.height, thresh))
{
return;
}
break;
case THRESH_TOZERO:
if(tegra::thresh_8u_tozero(_src, _dst, roi.width, roi.height, thresh))
{
return;
}
break;
case THRESH_TOZERO_INV:
if(tegra::thresh_8u_tozero_inv(_src, _dst, roi.width, roi.height, thresh))
{
return;
}
break;
}
if (tegra::thresh_8u(_src, _dst, roi.width, roi.height, thresh, maxval, type))
return;
#endif
switch( type )
{
case THRESH_BINARY:
@ -139,7 +108,7 @@ thresh_8u( const Mat& _src, Mat& _dst, uchar thresh, uchar maxval, int type )
__m128i thresh_s = _mm_set1_epi8(thresh ^ 0x80);
__m128i maxval_ = _mm_set1_epi8(maxval);
j_scalar = roi.width & -8;
for( i = 0; i < roi.height; i++ )
{
const uchar* src = (const uchar*)(_src.data + _src.step*i);
@ -255,7 +224,7 @@ thresh_8u( const Mat& _src, Mat& _dst, uchar thresh, uchar maxval, int type )
}
}
}
#endif
#endif
if( j_scalar < roi.width )
{
@ -263,8 +232,8 @@ thresh_8u( const Mat& _src, Mat& _dst, uchar thresh, uchar maxval, int type )
{
const uchar* src = (const uchar*)(_src.data + _src.step*i);
uchar* dst = (uchar*)(_dst.data + _dst.step*i);
j = j_scalar;
#if CV_ENABLE_UNROLLED
j = j_scalar;
#if CV_ENABLE_UNROLLED
for( ; j <= roi.width - 4; j += 4 )
{
uchar t0 = tab[src[j]];
@ -279,7 +248,7 @@ thresh_8u( const Mat& _src, Mat& _dst, uchar thresh, uchar maxval, int type )
dst[j+2] = t0;
dst[j+3] = t1;
}
#endif
#endif
for( ; j < roi.width; j++ )
dst[j] = tab[src[j]];
}
@ -297,7 +266,7 @@ thresh_16s( const Mat& _src, Mat& _dst, short thresh, short maxval, int type )
short* dst = (short*)_dst.data;
size_t src_step = _src.step/sizeof(src[0]);
size_t dst_step = _dst.step/sizeof(dst[0]);
#if CV_SSE2
volatile bool useSIMD = checkHardwareSupport(CV_CPU_SSE);
#endif
@ -307,41 +276,12 @@ thresh_16s( const Mat& _src, Mat& _dst, short thresh, short maxval, int type )
roi.width *= roi.height;
roi.height = 1;
}
#ifdef HAVE_TEGRA_OPTIMIZATION
switch( type )
{
case THRESH_BINARY:
if(tegra::thresh_16s_binary(_src, _dst, roi.width, roi.height, thresh, maxval))
{
return;
}
break;
case THRESH_BINARY_INV:
if(tegra::thresh_16s_binary_inv(_src, _dst, roi.width, roi.height, thresh, maxval))
{
return;
}
break;
case THRESH_TRUNC:
if(tegra::thresh_16s_trunc(_src, _dst, roi.width, roi.height, thresh))
{
return;
}
break;
case THRESH_TOZERO:
if(tegra::thresh_16s_tozero(_src, _dst, roi.width, roi.height, thresh))
{
return;
}
break;
case THRESH_TOZERO_INV:
if(tegra::thresh_16s_tozero_inv(_src, _dst, roi.width, roi.height, thresh))
{
return;
}
break;
}
#endif
if (tegra::thresh_16s(_src, _dst, roi.width, roi.height, thresh, maxval, type))
return;
#endif
switch( type )
{
case THRESH_BINARY:
@ -393,8 +333,8 @@ thresh_16s( const Mat& _src, Mat& _dst, short thresh, short maxval, int type )
_mm_storeu_si128((__m128i*)(dst + j + 8), v1 );
}
}
#endif
#endif
for( ; j < roi.width; j++ )
dst[j] = src[j] <= thresh ? maxval : 0;
}
@ -419,8 +359,8 @@ thresh_16s( const Mat& _src, Mat& _dst, short thresh, short maxval, int type )
_mm_storeu_si128((__m128i*)(dst + j + 8), v1 );
}
}
#endif
#endif
for( ; j < roi.width; j++ )
dst[j] = std::min(src[j], thresh);
}
@ -446,7 +386,7 @@ thresh_16s( const Mat& _src, Mat& _dst, short thresh, short maxval, int type )
}
}
#endif
for( ; j < roi.width; j++ )
{
short v = src[j];
@ -487,7 +427,7 @@ thresh_16s( const Mat& _src, Mat& _dst, short thresh, short maxval, int type )
}
}
static void
thresh_32f( const Mat& _src, Mat& _dst, float thresh, float maxval, int type )
{
@ -498,52 +438,22 @@ thresh_32f( const Mat& _src, Mat& _dst, float thresh, float maxval, int type )
float* dst = (float*)_dst.data;
size_t src_step = _src.step/sizeof(src[0]);
size_t dst_step = _dst.step/sizeof(dst[0]);
#if CV_SSE2
volatile bool useSIMD = checkHardwareSupport(CV_CPU_SSE);
#endif
if( _src.isContinuous() && _dst.isContinuous() )
{
roi.width *= roi.height;
roi.height = 1;
}
#ifdef HAVE_TEGRA_OPTIMIZATION
switch( type )
{
case THRESH_BINARY:
if(tegra::thresh_32f_binary(_src, _dst, roi.width, roi.height, thresh, maxval))
{
return;
}
break;
case THRESH_BINARY_INV:
if(tegra::thresh_32f_binary_inv(_src, _dst, roi.width, roi.height, thresh, maxval))
{
return;
}
break;
case THRESH_TRUNC:
if(tegra::thresh_32f_trunc(_src, _dst, roi.width, roi.height, thresh))
{
return;
}
break;
case THRESH_TOZERO:
if(tegra::thresh_32f_tozero(_src, _dst, roi.width, roi.height, thresh))
{
return;
}
break;
case THRESH_TOZERO_INV:
if(tegra::thresh_32f_tozero_inv(_src, _dst, roi.width, roi.height, thresh))
{
return;
}
break;
}
#endif
if (tegra::thresh_32f(_src, _dst, roi.width, roi.height, thresh, maxval, type))
return;
#endif
switch( type )
{
case THRESH_BINARY:
@ -568,12 +478,12 @@ thresh_32f( const Mat& _src, Mat& _dst, float thresh, float maxval, int type )
}
}
#endif
for( ; j < roi.width; j++ )
dst[j] = src[j] > thresh ? maxval : 0;
}
break;
case THRESH_BINARY_INV:
for( i = 0; i < roi.height; i++, src += src_step, dst += dst_step )
{
@ -595,13 +505,13 @@ thresh_32f( const Mat& _src, Mat& _dst, float thresh, float maxval, int type )
_mm_storeu_ps( dst + j + 4, v1 );
}
}
#endif
#endif
for( ; j < roi.width; j++ )
dst[j] = src[j] <= thresh ? maxval : 0;
}
break;
case THRESH_TRUNC:
for( i = 0; i < roi.height; i++, src += src_step, dst += dst_step )
{
@ -621,13 +531,13 @@ thresh_32f( const Mat& _src, Mat& _dst, float thresh, float maxval, int type )
_mm_storeu_ps( dst + j + 4, v1 );
}
}
#endif
#endif
for( ; j < roi.width; j++ )
dst[j] = std::min(src[j], thresh);
}
break;
case THRESH_TOZERO:
for( i = 0; i < roi.height; i++, src += src_step, dst += dst_step )
{
@ -648,7 +558,7 @@ thresh_32f( const Mat& _src, Mat& _dst, float thresh, float maxval, int type )
}
}
#endif
for( ; j < roi.width; j++ )
{
float v = src[j];
@ -656,7 +566,7 @@ thresh_32f( const Mat& _src, Mat& _dst, float thresh, float maxval, int type )
}
}
break;
case THRESH_TOZERO_INV:
for( i = 0; i < roi.height; i++, src += src_step, dst += dst_step )
{
@ -688,7 +598,7 @@ thresh_32f( const Mat& _src, Mat& _dst, float thresh, float maxval, int type )
return CV_Error( CV_StsBadArg, "" );
}
}
static double
getThreshVal_Otsu_8u( const Mat& _src )
@ -704,8 +614,8 @@ getThreshVal_Otsu_8u( const Mat& _src )
for( i = 0; i < size.height; i++ )
{
const uchar* src = _src.data + _src.step*i;
j = 0;
#if CV_ENABLE_UNROLLED
j = 0;
#if CV_ENABLE_UNROLLED
for( ; j <= size.width - 4; j += 4 )
{
int v0 = src[j], v1 = src[j+1];
@ -721,7 +631,7 @@ getThreshVal_Otsu_8u( const Mat& _src )
double mu = 0, scale = 1./(size.width*size.height);
for( i = 0; i < N; i++ )
mu += i*(double)h[i];
mu *= scale;
double mu1 = 0, q1 = 0;
double max_sigma = 0, max_val = 0;
@ -803,7 +713,7 @@ private:
};
}
double cv::threshold( InputArray _src, OutputArray _dst, double thresh, double maxval, int type )
{
Mat src = _src.getMat();
@ -815,12 +725,12 @@ double cv::threshold( InputArray _src, OutputArray _dst, double thresh, double m
CV_Assert( src.type() == CV_8UC1 );
thresh = getThreshVal_Otsu_8u(src);
}
_dst.create( src.size(), src.type() );
Mat dst = _dst.getMat();
int nStripes = 1;
#if defined HAVE_TBB && defined HAVE_TEGRA_OPTIMIZATION
#if defined HAVE_TBB && defined ANDROID
nStripes = 4;
#endif
@ -849,7 +759,6 @@ double cv::threshold( InputArray _src, OutputArray _dst, double thresh, double m
}
else
{
//thresh_8u( src, dst, (uchar)ithresh, (uchar)imaxval, type );
parallel_for(BlockedRange(0, nStripes),
ThresholdRunner(src, dst, nStripes, (uchar)ithresh, (uchar)imaxval, type));
}
@ -862,7 +771,7 @@ double cv::threshold( InputArray _src, OutputArray _dst, double thresh, double m
if( type == THRESH_TRUNC )
imaxval = ithresh;
imaxval = saturate_cast<short>(imaxval);
if( ithresh < SHRT_MIN || ithresh >= SHRT_MAX )
{
if( type == THRESH_BINARY || type == THRESH_BINARY_INV ||
@ -879,14 +788,12 @@ double cv::threshold( InputArray _src, OutputArray _dst, double thresh, double m
}
else
{
//thresh_16s( src, dst, (short)ithresh, (short)imaxval, type );
parallel_for(BlockedRange(0, nStripes),
ThresholdRunner(src, dst, nStripes, (short)ithresh, (short)imaxval, type));
}
}
else if( src.depth() == CV_32F )
{
//thresh_32f( src, dst, (float)thresh, (float)maxval, type );
parallel_for(BlockedRange(0, nStripes),
ThresholdRunner(src, dst, nStripes, (float)thresh, (float)maxval, type));
}
@ -913,7 +820,7 @@ void cv::adaptiveThreshold( InputArray _src, OutputArray _dst, double maxValue,
dst = Scalar(0);
return;
}
Mat mean;
if( src.data != dst.data )
@ -930,7 +837,7 @@ void cv::adaptiveThreshold( InputArray _src, OutputArray _dst, double maxValue,
int i, j;
uchar imaxval = saturate_cast<uchar>(maxValue);
int idelta = type == THRESH_BINARY ? cvCeil(delta) : cvFloor(delta);
uchar tab[768];
uchar tab[768];
if( type == CV_THRESH_BINARY )
for( i = 0; i < 768; i++ )