Merge pull request #1779 from perping:integral_2.4

pull/1786/merge
Roman Donchenko 11 years ago committed by OpenCV Buildbot
commit 54ea5bbac7
  1. 8
      modules/ocl/doc/image_processing.rst
  2. 8
      modules/ocl/include/opencv2/ocl/ocl.hpp
  3. 4
      modules/ocl/perf/perf_match_template.cpp
  4. 47
      modules/ocl/src/haar.cpp
  5. 49
      modules/ocl/src/imgproc.cpp
  6. 24
      modules/ocl/src/match_template.cpp
  7. 143
      modules/ocl/src/opencl/imgproc_integral.cl
  8. 28
      modules/ocl/test/test_imgproc.cpp

@ -65,15 +65,15 @@ ocl::integral
-----------------
Computes an integral image.
.. ocv:function:: void ocl::integral(const oclMat &src, oclMat &sum, oclMat &sqsum)
.. ocv:function:: void ocl::integral(const oclMat &src, oclMat &sum, oclMat &sqsum, int sdepth=-1)
.. ocv:function:: void ocl::integral(const oclMat &src, oclMat &sum)
.. ocv:function:: void ocl::integral(const oclMat &src, oclMat &sum, int sdepth=-1)
:param src: Source image. Only ``CV_8UC1`` images are supported for now.
:param sum: Integral image containing 32-bit unsigned integer values packed into ``CV_32SC1`` .
:param sum: Integral image containing 32-bit unsigned integer or 32-bit floating-point .
:param sqsum: Sqsum values is ``CV_32FC1`` type.
:param sqsum: Sqsum values is ``CV_32FC1`` or ``CV_64FC1`` type.
.. seealso:: :ocv:func:`integral`

@ -861,10 +861,10 @@ namespace cv
CV_EXPORTS void warpPerspective(const oclMat &src, oclMat &dst, const Mat &M, Size dsize, int flags = INTER_LINEAR);
//! computes the integral image and integral for the squared image
// sum will have CV_32S type, sqsum - CV32F type
// sum will support CV_32S, CV_32F, sqsum - support CV32F, CV_64F
// supports only CV_8UC1 source type
CV_EXPORTS void integral(const oclMat &src, oclMat &sum, oclMat &sqsum);
CV_EXPORTS void integral(const oclMat &src, oclMat &sum);
CV_EXPORTS void integral(const oclMat &src, oclMat &sum, oclMat &sqsum, int sdepth=-1 );
CV_EXPORTS void integral(const oclMat &src, oclMat &sum, int sdepth=-1 );
CV_EXPORTS void cornerHarris(const oclMat &src, oclMat &dst, int blockSize, int ksize, double k, int bordertype = cv::BORDER_DEFAULT);
CV_EXPORTS void cornerHarris_dxdy(const oclMat &src, oclMat &dst, oclMat &Dx, oclMat &Dy,
int blockSize, int ksize, double k, int bordertype = cv::BORDER_DEFAULT);
@ -939,7 +939,7 @@ namespace cv
Size m_maxSize;
vector<CvSize> sizev;
vector<float> scalev;
oclMat gimg1, gsum, gsqsum;
oclMat gimg1, gsum, gsqsum, gsqsum_t;
void * buffers;
};

@ -108,13 +108,13 @@ PERF_TEST_P(CV_TM_CCORR_NORMEDFixture, matchTemplate, OCL_TYPICAL_MAT_SIZES)
oclDst.download(dst);
SANITY_CHECK(dst, 2e-2);
SANITY_CHECK(dst, 3e-2);
}
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() cv::matchTemplate(src, templ, dst, CV_TM_CCORR_NORMED);
SANITY_CHECK(dst, 2e-2);
SANITY_CHECK(dst, 3e-2);
}
else
OCL_PERF_ELSE

@ -747,6 +747,15 @@ CvSeq *cv::ocl::OclCascadeClassifier::oclHaarDetectObjects( oclMat &gimg, CvMemS
oclMat gsum(totalheight + 4, gimg.cols + 1, CV_32SC1);
oclMat gsqsum(totalheight + 4, gimg.cols + 1, CV_32FC1);
int sdepth = 0;
if(Context::getContext()->supportsFeature(FEATURE_CL_DOUBLE))
sdepth = CV_64FC1;
else
sdepth = CV_32FC1;
sdepth = CV_MAT_DEPTH(sdepth);
int type = CV_MAKE_TYPE(sdepth, 1);
oclMat gsqsum_t(totalheight + 4, gimg.cols + 1, type);
cl_mem stagebuffer;
cl_mem nodebuffer;
cl_mem candidatebuffer;
@ -754,6 +763,7 @@ CvSeq *cv::ocl::OclCascadeClassifier::oclHaarDetectObjects( oclMat &gimg, CvMemS
cv::Rect roi, roi2;
cv::Mat imgroi, imgroisq;
cv::ocl::oclMat resizeroi, gimgroi, gimgroisq;
int grp_per_CU = 12;
size_t blocksize = 8;
@ -773,7 +783,7 @@ CvSeq *cv::ocl::OclCascadeClassifier::oclHaarDetectObjects( oclMat &gimg, CvMemS
roi2 = Rect(0, 0, sz.width - 1, sz.height - 1);
resizeroi = gimg1(roi2);
gimgroi = gsum(roi);
gimgroisq = gsqsum(roi);
gimgroisq = gsqsum_t(roi);
int width = gimgroi.cols - 1 - cascade->orig_window_size.width;
int height = gimgroi.rows - 1 - cascade->orig_window_size.height;
scaleinfo[i].width_height = (width << 16) | height;
@ -787,8 +797,13 @@ CvSeq *cv::ocl::OclCascadeClassifier::oclHaarDetectObjects( oclMat &gimg, CvMemS
scaleinfo[i].factor = factor;
cv::ocl::resize(gimg, resizeroi, Size(sz.width - 1, sz.height - 1), 0, 0, INTER_LINEAR);
cv::ocl::integral(resizeroi, gimgroi, gimgroisq);
indexy += sz.height;
}
if(gsqsum_t.depth() == CV_64F)
gsqsum_t.convertTo(gsqsum, CV_32FC1);
else
gsqsum = gsqsum_t;
gcascade = (GpuHidHaarClassifierCascade *)cascade->hid_cascade;
stage = (GpuHidHaarStageClassifier *)(gcascade + 1);
@ -996,7 +1011,12 @@ CvSeq *cv::ocl::OclCascadeClassifier::oclHaarDetectObjects( oclMat &gimg, CvMemS
int n_factors = 0;
oclMat gsum;
oclMat gsqsum;
cv::ocl::integral(gimg, gsum, gsqsum);
oclMat gsqsum_t;
cv::ocl::integral(gimg, gsum, gsqsum_t);
if(gsqsum_t.depth() == CV_64F)
gsqsum_t.convertTo(gsqsum, CV_32FC1);
else
gsqsum = gsqsum_t;
CvSize sz;
vector<CvSize> sizev;
vector<float> scalev;
@ -1271,12 +1291,16 @@ void cv::ocl::OclCascadeClassifierBuf::detectMultiScale(oclMat &gimg, CV_OUT std
roi2 = Rect(0, 0, sz.width - 1, sz.height - 1);
resizeroi = gimg1(roi2);
gimgroi = gsum(roi);
gimgroisq = gsqsum(roi);
gimgroisq = gsqsum_t(roi);
cv::ocl::resize(gimg, resizeroi, Size(sz.width - 1, sz.height - 1), 0, 0, INTER_LINEAR);
cv::ocl::integral(resizeroi, gimgroi, gimgroisq);
indexy += sz.height;
}
if(gsqsum_t.depth() == CV_64F)
gsqsum_t.convertTo(gsqsum, CV_32FC1);
else
gsqsum = gsqsum_t;
gcascade = (GpuHidHaarClassifierCascade *)(cascade->hid_cascade);
stage = (GpuHidHaarStageClassifier *)(gcascade + 1);
@ -1338,7 +1362,11 @@ void cv::ocl::OclCascadeClassifierBuf::detectMultiScale(oclMat &gimg, CV_OUT std
}
else
{
cv::ocl::integral(gimg, gsum, gsqsum);
cv::ocl::integral(gimg, gsum, gsqsum_t);
if(gsqsum_t.depth() == CV_64F)
gsqsum_t.convertTo(gsqsum, CV_32FC1);
else
gsqsum = gsqsum_t;
gcascade = (GpuHidHaarClassifierCascade *)cascade->hid_cascade;
@ -1564,6 +1592,7 @@ void cv::ocl::OclCascadeClassifierBuf::CreateFactorRelatedBufs(
gimg1.release();
gsum.release();
gsqsum.release();
gsqsum_t.release();
}
else if (!(m_flags & CV_HAAR_SCALE_IMAGE) && (flags & CV_HAAR_SCALE_IMAGE))
{
@ -1638,6 +1667,16 @@ void cv::ocl::OclCascadeClassifierBuf::CreateFactorRelatedBufs(
gsum.create(totalheight + 4, cols + 1, CV_32SC1);
gsqsum.create(totalheight + 4, cols + 1, CV_32FC1);
int sdepth = 0;
if(Context::getContext()->supportsFeature(FEATURE_CL_DOUBLE))
sdepth = CV_64FC1;
else
sdepth = CV_32FC1;
sdepth = CV_MAT_DEPTH(sdepth);
int type = CV_MAKE_TYPE(sdepth, 1);
gsqsum_t.create(totalheight + 4, cols + 1, type);
scaleinfo = (detect_piramid_info *)malloc(sizeof(detect_piramid_info) * loopcount);
for( int i = 0; i < loopcount; i++ )
{

@ -781,7 +781,7 @@ namespace cv
////////////////////////////////////////////////////////////////////////
// integral
void integral(const oclMat &src, oclMat &sum, oclMat &sqsum)
void integral(const oclMat &src, oclMat &sum, oclMat &sqsum, int sdepth)
{
CV_Assert(src.type() == CV_8UC1);
if (!src.clCxt->supportsFeature(ocl::FEATURE_CL_DOUBLE) && src.depth() == CV_64F)
@ -790,6 +790,11 @@ namespace cv
return;
}
if( sdepth <= 0 )
sdepth = CV_32S;
sdepth = CV_MAT_DEPTH(sdepth);
int type = CV_MAKE_TYPE(sdepth, 1);
int vlen = 4;
int offset = src.offset / vlen;
int pre_invalid = src.offset % vlen;
@ -797,17 +802,26 @@ namespace cv
oclMat t_sum , t_sqsum;
int w = src.cols + 1, h = src.rows + 1;
int depth = src.depth() == CV_8U ? CV_32S : CV_64F;
int type = CV_MAKE_TYPE(depth, 1);
char build_option[250];
if(Context::getContext()->supportsFeature(ocl::FEATURE_CL_DOUBLE))
{
t_sqsum.create(src.cols, src.rows, CV_64FC1);
sqsum.create(h, w, CV_64FC1);
sprintf(build_option, "-D TYPE=double -D TYPE4=double4 -D convert_TYPE4=convert_double4");
}
else
{
t_sqsum.create(src.cols, src.rows, CV_32FC1);
sqsum.create(h, w, CV_32FC1);
sprintf(build_option, "-D TYPE=float -D TYPE4=float4 -D convert_TYPE4=convert_float4");
}
t_sum.create(src.cols, src.rows, type);
sum.create(h, w, type);
t_sqsum.create(src.cols, src.rows, CV_32FC1);
sqsum.create(h, w, CV_32FC1);
int sum_offset = sum.offset / vlen;
int sqsum_offset = sqsum.offset / vlen;
int sum_offset = sum.offset / sum.elemSize();
int sqsum_offset = sqsum.offset / sqsum.elemSize();
vector<pair<size_t , const void *> > args;
args.push_back( make_pair( sizeof(cl_mem) , (void *)&src.data ));
@ -819,8 +833,9 @@ namespace cv
args.push_back( make_pair( sizeof(cl_int) , (void *)&src.cols ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&src.step ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&t_sum.step));
args.push_back( make_pair( sizeof(cl_int) , (void *)&t_sqsum.step));
size_t gt[3] = {((vcols + 1) / 2) * 256, 1, 1}, lt[3] = {256, 1, 1};
openCLExecuteKernel(src.clCxt, &imgproc_integral, "integral_cols", gt, lt, args, -1, depth);
openCLExecuteKernel(src.clCxt, &imgproc_integral, "integral_cols", gt, lt, args, -1, sdepth, build_option);
args.clear();
args.push_back( make_pair( sizeof(cl_mem) , (void *)&t_sum.data ));
@ -830,15 +845,16 @@ namespace cv
args.push_back( make_pair( sizeof(cl_int) , (void *)&t_sum.rows ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&t_sum.cols ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&t_sum.step ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&t_sqsum.step));
args.push_back( make_pair( sizeof(cl_int) , (void *)&sum.step));
args.push_back( make_pair( sizeof(cl_int) , (void *)&sqsum.step));
args.push_back( make_pair( sizeof(cl_int) , (void *)&sum_offset));
args.push_back( make_pair( sizeof(cl_int) , (void *)&sqsum_offset));
size_t gt2[3] = {t_sum.cols * 32, 1, 1}, lt2[3] = {256, 1, 1};
openCLExecuteKernel(src.clCxt, &imgproc_integral, "integral_rows", gt2, lt2, args, -1, depth);
openCLExecuteKernel(src.clCxt, &imgproc_integral, "integral_rows", gt2, lt2, args, -1, sdepth, build_option);
}
void integral(const oclMat &src, oclMat &sum)
void integral(const oclMat &src, oclMat &sum, int sdepth)
{
CV_Assert(src.type() == CV_8UC1);
int vlen = 4;
@ -846,10 +862,13 @@ namespace cv
int pre_invalid = src.offset % vlen;
int vcols = (pre_invalid + src.cols + vlen - 1) / vlen;
if( sdepth <= 0 )
sdepth = CV_32S;
sdepth = CV_MAT_DEPTH(sdepth);
int type = CV_MAKE_TYPE(sdepth, 1);
oclMat t_sum;
int w = src.cols + 1, h = src.rows + 1;
int depth = src.depth() == CV_8U ? CV_32S : CV_32F;
int type = CV_MAKE_TYPE(depth, 1);
t_sum.create(src.cols, src.rows, type);
sum.create(h, w, type);
@ -865,7 +884,7 @@ namespace cv
args.push_back( make_pair( sizeof(cl_int) , (void *)&src.step ));
args.push_back( make_pair( sizeof(cl_int) , (void *)&t_sum.step));
size_t gt[3] = {((vcols + 1) / 2) * 256, 1, 1}, lt[3] = {256, 1, 1};
openCLExecuteKernel(src.clCxt, &imgproc_integral_sum, "integral_sum_cols", gt, lt, args, -1, depth);
openCLExecuteKernel(src.clCxt, &imgproc_integral_sum, "integral_sum_cols", gt, lt, args, -1, sdepth);
args.clear();
args.push_back( make_pair( sizeof(cl_mem) , (void *)&t_sum.data ));
@ -876,7 +895,7 @@ namespace cv
args.push_back( make_pair( sizeof(cl_int) , (void *)&sum.step));
args.push_back( make_pair( sizeof(cl_int) , (void *)&sum_offset));
size_t gt2[3] = {t_sum.cols * 32, 1, 1}, lt2[3] = {256, 1, 1};
openCLExecuteKernel(src.clCxt, &imgproc_integral_sum, "integral_sum_rows", gt2, lt2, args, -1, depth);
openCLExecuteKernel(src.clCxt, &imgproc_integral_sum, "integral_sum_rows", gt2, lt2, args, -1, sdepth);
}
/////////////////////// corner //////////////////////////////

@ -245,12 +245,15 @@ namespace cv
void matchTemplate_CCORR_NORMED(
const oclMat &image, const oclMat &templ, oclMat &result, MatchTemplateBuf &buf)
{
cv::ocl::oclMat temp;
matchTemplate_CCORR(image, templ, result, buf);
buf.image_sums.resize(1);
buf.image_sqsums.resize(1);
integral(image.reshape(1), buf.image_sums[0], buf.image_sqsums[0]);
integral(image.reshape(1), buf.image_sums[0], temp);
if(temp.depth() == CV_64F)
temp.convertTo(buf.image_sqsums[0], CV_32FC1);
else
buf.image_sqsums[0] = temp;
unsigned long long templ_sqsum = (unsigned long long)sqrSum(templ.reshape(1))[0];
Context *clCxt = image.clCxt;
@ -416,7 +419,12 @@ namespace cv
{
buf.image_sums.resize(1);
buf.image_sqsums.resize(1);
integral(image, buf.image_sums[0], buf.image_sqsums[0]);
cv::ocl::oclMat temp;
integral(image, buf.image_sums[0], temp);
if(temp.depth() == CV_64F)
temp.convertTo(buf.image_sqsums[0], CV_32FC1);
else
buf.image_sqsums[0] = temp;
templ_sum[0] = (float)sum(templ)[0];
@ -452,10 +460,14 @@ namespace cv
templ_sum *= scale;
buf.image_sums.resize(buf.images.size());
buf.image_sqsums.resize(buf.images.size());
cv::ocl::oclMat temp;
for(int i = 0; i < image.oclchannels(); i ++)
{
integral(buf.images[i], buf.image_sums[i], buf.image_sqsums[i]);
integral(buf.images[i], buf.image_sums[i], temp);
if(temp.depth() == CV_64F)
temp.convertTo(buf.image_sqsums[i], CV_32FC1);
else
buf.image_sqsums[i] = temp;
}
switch(image.oclchannels())

@ -49,6 +49,9 @@
#elif defined (cl_khr_fp64)
#pragma OPENCL EXTENSION cl_khr_fp64:enable
#endif
#define CONVERT(step) ((step)>>1)
#else
#define CONVERT(step) ((step))
#endif
#define LSIZE 256
@ -61,17 +64,17 @@
#define GET_CONFLICT_OFFSET(lid) ((lid) >> LOG_NUM_BANKS)
kernel void integral_cols_D4(__global uchar4 *src,__global int *sum ,__global float *sqsum,
int src_offset,int pre_invalid,int rows,int cols,int src_step,int dst_step)
kernel void integral_cols_D4(__global uchar4 *src,__global int *sum ,__global TYPE *sqsum,
int src_offset,int pre_invalid,int rows,int cols,int src_step,int dst_step,int dst1_step)
{
int lid = get_local_id(0);
int gid = get_group_id(0);
int4 src_t[2], sum_t[2];
float4 sqsum_t[2];
TYPE4 sqsum_t[2];
__local int4 lm_sum[2][LSIZE + LOG_LSIZE];
__local float4 lm_sqsum[2][LSIZE + LOG_LSIZE];
__local TYPE4 lm_sqsum[2][LSIZE + LOG_LSIZE];
__local int* sum_p;
__local float* sqsum_p;
__local TYPE* sqsum_p;
src_step = src_step >> 2;
gid = gid << 1;
for(int i = 0; i < rows; i =i + LSIZE_1)
@ -80,17 +83,17 @@ kernel void integral_cols_D4(__global uchar4 *src,__global int *sum ,__global fl
src_t[1] = (i + lid < rows ? convert_int4(src[src_offset + (lid+i) * src_step + min(gid + 1, cols - 1)]) : 0);
sum_t[0] = (i == 0 ? 0 : lm_sum[0][LSIZE_2 + LOG_LSIZE]);
sqsum_t[0] = (i == 0 ? (float4)0 : lm_sqsum[0][LSIZE_2 + LOG_LSIZE]);
sqsum_t[0] = (i == 0 ? (TYPE4)0 : lm_sqsum[0][LSIZE_2 + LOG_LSIZE]);
sum_t[1] = (i == 0 ? 0 : lm_sum[1][LSIZE_2 + LOG_LSIZE]);
sqsum_t[1] = (i == 0 ? (float4)0 : lm_sqsum[1][LSIZE_2 + LOG_LSIZE]);
sqsum_t[1] = (i == 0 ? (TYPE4)0 : lm_sqsum[1][LSIZE_2 + LOG_LSIZE]);
barrier(CLK_LOCAL_MEM_FENCE);
int bf_loc = lid + GET_CONFLICT_OFFSET(lid);
lm_sum[0][bf_loc] = src_t[0];
lm_sqsum[0][bf_loc] = convert_float4(src_t[0] * src_t[0]);
lm_sqsum[0][bf_loc] = convert_TYPE4(src_t[0] * src_t[0]);
lm_sum[1][bf_loc] = src_t[1];
lm_sqsum[1][bf_loc] = convert_float4(src_t[1] * src_t[1]);
lm_sqsum[1][bf_loc] = convert_TYPE4(src_t[1] * src_t[1]);
int offset = 1;
for(int d = LSIZE >> 1 ; d > 0; d>>=1)
@ -131,7 +134,8 @@ kernel void integral_cols_D4(__global uchar4 *src,__global int *sum ,__global fl
}
}
barrier(CLK_LOCAL_MEM_FENCE);
int loc_s0 = gid * dst_step + i + lid - 1 - pre_invalid * dst_step / 4, loc_s1 = loc_s0 + dst_step ;
int loc_s0 = gid * dst_step + i + lid - 1 - pre_invalid * dst_step /4, loc_s1 = loc_s0 + dst_step ;
int loc_sq0 = gid * CONVERT(dst1_step) + i + lid - 1 - pre_invalid * dst1_step / sizeof(TYPE),loc_sq1 = loc_sq0 + CONVERT(dst1_step);
if(lid > 0 && (i+lid) <= rows)
{
lm_sum[0][bf_loc] += sum_t[0];
@ -139,20 +143,20 @@ kernel void integral_cols_D4(__global uchar4 *src,__global int *sum ,__global fl
lm_sqsum[0][bf_loc] += sqsum_t[0];
lm_sqsum[1][bf_loc] += sqsum_t[1];
sum_p = (__local int*)(&(lm_sum[0][bf_loc]));
sqsum_p = (__local float*)(&(lm_sqsum[0][bf_loc]));
sqsum_p = (__local TYPE*)(&(lm_sqsum[0][bf_loc]));
for(int k = 0; k < 4; k++)
{
if(gid * 4 + k >= cols + pre_invalid || gid * 4 + k < pre_invalid) continue;
sum[loc_s0 + k * dst_step / 4] = sum_p[k];
sqsum[loc_s0 + k * dst_step / 4] = sqsum_p[k];
sqsum[loc_sq0 + k * dst1_step / sizeof(TYPE)] = sqsum_p[k];
}
sum_p = (__local int*)(&(lm_sum[1][bf_loc]));
sqsum_p = (__local float*)(&(lm_sqsum[1][bf_loc]));
sqsum_p = (__local TYPE*)(&(lm_sqsum[1][bf_loc]));
for(int k = 0; k < 4; k++)
{
if(gid * 4 + k + 4 >= cols + pre_invalid) break;
sum[loc_s1 + k * dst_step / 4] = sum_p[k];
sqsum[loc_s1 + k * dst_step / 4] = sqsum_p[k];
sqsum[loc_sq1 + k * dst1_step / sizeof(TYPE)] = sqsum_p[k];
}
}
barrier(CLK_LOCAL_MEM_FENCE);
@ -160,30 +164,32 @@ kernel void integral_cols_D4(__global uchar4 *src,__global int *sum ,__global fl
}
kernel void integral_rows_D4(__global int4 *srcsum,__global float4 * srcsqsum,__global int *sum ,
__global float *sqsum,int rows,int cols,int src_step,int sum_step,
kernel void integral_rows_D4(__global int4 *srcsum,__global TYPE4 * srcsqsum,__global int *sum ,
__global TYPE *sqsum,int rows,int cols,int src_step,int src1_step,int sum_step,
int sqsum_step,int sum_offset,int sqsum_offset)
{
int lid = get_local_id(0);
int gid = get_group_id(0);
int4 src_t[2], sum_t[2];
float4 sqsrc_t[2],sqsum_t[2];
TYPE4 sqsrc_t[2],sqsum_t[2];
__local int4 lm_sum[2][LSIZE + LOG_LSIZE];
__local float4 lm_sqsum[2][LSIZE + LOG_LSIZE];
__local TYPE4 lm_sqsum[2][LSIZE + LOG_LSIZE];
__local int *sum_p;
__local float *sqsum_p;
__local TYPE *sqsum_p;
src_step = src_step >> 4;
src1_step = (src1_step / sizeof(TYPE)) >> 2 ;
gid <<= 1;
for(int i = 0; i < rows; i =i + LSIZE_1)
{
src_t[0] = i + lid < rows ? srcsum[(lid+i) * src_step + gid * 2] : (int4)0;
sqsrc_t[0] = i + lid < rows ? srcsqsum[(lid+i) * src_step + gid * 2] : (float4)0;
src_t[1] = i + lid < rows ? srcsum[(lid+i) * src_step + gid * 2 + 1] : (int4)0;
sqsrc_t[1] = i + lid < rows ? srcsqsum[(lid+i) * src_step + gid * 2 + 1] : (float4)0;
src_t[0] = i + lid < rows ? srcsum[(lid+i) * src_step + gid ] : (int4)0;
sqsrc_t[0] = i + lid < rows ? srcsqsum[(lid+i) * src1_step + gid ] : (TYPE4)0;
src_t[1] = i + lid < rows ? srcsum[(lid+i) * src_step + gid + 1] : (int4)0;
sqsrc_t[1] = i + lid < rows ? srcsqsum[(lid+i) * src1_step + gid + 1] : (TYPE4)0;
sum_t[0] = (i == 0 ? 0 : lm_sum[0][LSIZE_2 + LOG_LSIZE]);
sqsum_t[0] = (i == 0 ? (float4)0 : lm_sqsum[0][LSIZE_2 + LOG_LSIZE]);
sqsum_t[0] = (i == 0 ? (TYPE4)0 : lm_sqsum[0][LSIZE_2 + LOG_LSIZE]);
sum_t[1] = (i == 0 ? 0 : lm_sum[1][LSIZE_2 + LOG_LSIZE]);
sqsum_t[1] = (i == 0 ? (float4)0 : lm_sqsum[1][LSIZE_2 + LOG_LSIZE]);
sqsum_t[1] = (i == 0 ? (TYPE4)0 : lm_sqsum[1][LSIZE_2 + LOG_LSIZE]);
barrier(CLK_LOCAL_MEM_FENCE);
int bf_loc = lid + GET_CONFLICT_OFFSET(lid);
@ -239,17 +245,18 @@ kernel void integral_rows_D4(__global int4 *srcsum,__global float4 * srcsqsum,__
}
if(i + lid == 0)
{
int loc0 = gid * 2 * sum_step;
int loc1 = gid * 2 * sqsum_step;
int loc0 = gid * sum_step;
int loc1 = gid * CONVERT(sqsum_step);
for(int k = 1; k <= 8; k++)
{
if(gid * 8 + k > cols) break;
if(gid * 4 + k > cols) break;
sum[sum_offset + loc0 + k * sum_step / 4] = 0;
sqsum[sqsum_offset + loc1 + k * sqsum_step / 4] = 0;
sqsum[sqsum_offset + loc1 + k * sqsum_step / sizeof(TYPE)] = 0;
}
}
int loc_s0 = sum_offset + gid * 2 * sum_step + sum_step / 4 + i + lid, loc_s1 = loc_s0 + sum_step ;
int loc_sq0 = sqsum_offset + gid * 2 * sqsum_step + sqsum_step / 4 + i + lid, loc_sq1 = loc_sq0 + sqsum_step ;
int loc_s0 = sum_offset + gid * sum_step + sum_step / 4 + i + lid, loc_s1 = loc_s0 + sum_step ;
int loc_sq0 = sqsum_offset + gid * CONVERT(sqsum_step) + sqsum_step / sizeof(TYPE) + i + lid, loc_sq1 = loc_sq0 + CONVERT(sqsum_step) ;
if(lid > 0 && (i+lid) <= rows)
{
lm_sum[0][bf_loc] += sum_t[0];
@ -257,37 +264,37 @@ kernel void integral_rows_D4(__global int4 *srcsum,__global float4 * srcsqsum,__
lm_sqsum[0][bf_loc] += sqsum_t[0];
lm_sqsum[1][bf_loc] += sqsum_t[1];
sum_p = (__local int*)(&(lm_sum[0][bf_loc]));
sqsum_p = (__local float*)(&(lm_sqsum[0][bf_loc]));
sqsum_p = (__local TYPE*)(&(lm_sqsum[0][bf_loc]));
for(int k = 0; k < 4; k++)
{
if(gid * 8 + k >= cols) break;
if(gid * 4 + k >= cols) break;
sum[loc_s0 + k * sum_step / 4] = sum_p[k];
sqsum[loc_sq0 + k * sqsum_step / 4] = sqsum_p[k];
sqsum[loc_sq0 + k * sqsum_step / sizeof(TYPE)] = sqsum_p[k];
}
sum_p = (__local int*)(&(lm_sum[1][bf_loc]));
sqsum_p = (__local float*)(&(lm_sqsum[1][bf_loc]));
sqsum_p = (__local TYPE*)(&(lm_sqsum[1][bf_loc]));
for(int k = 0; k < 4; k++)
{
if(gid * 8 + 4 + k >= cols) break;
if(gid * 4 + 4 + k >= cols) break;
sum[loc_s1 + k * sum_step / 4] = sum_p[k];
sqsum[loc_sq1 + k * sqsum_step / 4] = sqsum_p[k];
sqsum[loc_sq1 + k * sqsum_step / sizeof(TYPE)] = sqsum_p[k];
}
}
}
barrier(CLK_LOCAL_MEM_FENCE);
}
}
kernel void integral_cols_D5(__global uchar4 *src,__global float *sum ,__global float *sqsum,
int src_offset,int pre_invalid,int rows,int cols,int src_step,int dst_step)
kernel void integral_cols_D5(__global uchar4 *src,__global float *sum ,__global TYPE *sqsum,
int src_offset,int pre_invalid,int rows,int cols,int src_step,int dst_step, int dst1_step)
{
int lid = get_local_id(0);
int gid = get_group_id(0);
float4 src_t[2], sum_t[2];
float4 sqsum_t[2];
TYPE4 sqsum_t[2];
__local float4 lm_sum[2][LSIZE + LOG_LSIZE];
__local float4 lm_sqsum[2][LSIZE + LOG_LSIZE];
__local TYPE4 lm_sqsum[2][LSIZE + LOG_LSIZE];
__local float* sum_p;
__local float* sqsum_p;
__local TYPE* sqsum_p;
src_step = src_step >> 2;
gid = gid << 1;
for(int i = 0; i < rows; i =i + LSIZE_1)
@ -296,17 +303,17 @@ kernel void integral_cols_D5(__global uchar4 *src,__global float *sum ,__global
src_t[1] = (i + lid < rows ? convert_float4(src[src_offset + (lid+i) * src_step + min(gid + 1, cols - 1)]) : (float4)0);
sum_t[0] = (i == 0 ? (float4)0 : lm_sum[0][LSIZE_2 + LOG_LSIZE]);
sqsum_t[0] = (i == 0 ? (float4)0 : lm_sqsum[0][LSIZE_2 + LOG_LSIZE]);
sqsum_t[0] = (i == 0 ? (TYPE4)0 : lm_sqsum[0][LSIZE_2 + LOG_LSIZE]);
sum_t[1] = (i == 0 ? (float4)0 : lm_sum[1][LSIZE_2 + LOG_LSIZE]);
sqsum_t[1] = (i == 0 ? (float4)0 : lm_sqsum[1][LSIZE_2 + LOG_LSIZE]);
sqsum_t[1] = (i == 0 ? (TYPE4)0 : lm_sqsum[1][LSIZE_2 + LOG_LSIZE]);
barrier(CLK_LOCAL_MEM_FENCE);
int bf_loc = lid + GET_CONFLICT_OFFSET(lid);
lm_sum[0][bf_loc] = src_t[0];
lm_sqsum[0][bf_loc] = convert_float4(src_t[0] * src_t[0]);
lm_sqsum[0][bf_loc] = convert_TYPE4(src_t[0] * src_t[0]);
lm_sum[1][bf_loc] = src_t[1];
lm_sqsum[1][bf_loc] = convert_float4(src_t[1] * src_t[1]);
lm_sqsum[1][bf_loc] = convert_TYPE4(src_t[1] * src_t[1]);
int offset = 1;
for(int d = LSIZE >> 1 ; d > 0; d>>=1)
@ -348,6 +355,7 @@ kernel void integral_cols_D5(__global uchar4 *src,__global float *sum ,__global
}
barrier(CLK_LOCAL_MEM_FENCE);
int loc_s0 = gid * dst_step + i + lid - 1 - pre_invalid * dst_step / 4, loc_s1 = loc_s0 + dst_step ;
int loc_sq0 = gid * CONVERT(dst1_step) + i + lid - 1 - pre_invalid * dst1_step / sizeof(TYPE), loc_sq1 = loc_sq0 + CONVERT(dst1_step);
if(lid > 0 && (i+lid) <= rows)
{
lm_sum[0][bf_loc] += sum_t[0];
@ -355,20 +363,20 @@ kernel void integral_cols_D5(__global uchar4 *src,__global float *sum ,__global
lm_sqsum[0][bf_loc] += sqsum_t[0];
lm_sqsum[1][bf_loc] += sqsum_t[1];
sum_p = (__local float*)(&(lm_sum[0][bf_loc]));
sqsum_p = (__local float*)(&(lm_sqsum[0][bf_loc]));
sqsum_p = (__local TYPE*)(&(lm_sqsum[0][bf_loc]));
for(int k = 0; k < 4; k++)
{
if(gid * 4 + k >= cols + pre_invalid || gid * 4 + k < pre_invalid) continue;
sum[loc_s0 + k * dst_step / 4] = sum_p[k];
sqsum[loc_s0 + k * dst_step / 4] = sqsum_p[k];
sqsum[loc_sq0 + k * dst1_step / sizeof(TYPE)] = sqsum_p[k];
}
sum_p = (__local float*)(&(lm_sum[1][bf_loc]));
sqsum_p = (__local float*)(&(lm_sqsum[1][bf_loc]));
sqsum_p = (__local TYPE*)(&(lm_sqsum[1][bf_loc]));
for(int k = 0; k < 4; k++)
{
if(gid * 4 + k + 4 >= cols + pre_invalid) break;
sum[loc_s1 + k * dst_step / 4] = sum_p[k];
sqsum[loc_s1 + k * dst_step / 4] = sqsum_p[k];
sqsum[loc_sq1 + k * dst1_step / sizeof(TYPE)] = sqsum_p[k];
}
}
barrier(CLK_LOCAL_MEM_FENCE);
@ -376,30 +384,31 @@ kernel void integral_cols_D5(__global uchar4 *src,__global float *sum ,__global
}
kernel void integral_rows_D5(__global float4 *srcsum,__global float4 * srcsqsum,__global float *sum ,
__global float *sqsum,int rows,int cols,int src_step,int sum_step,
kernel void integral_rows_D5(__global float4 *srcsum,__global TYPE4 * srcsqsum,__global float *sum ,
__global TYPE *sqsum,int rows,int cols,int src_step,int src1_step, int sum_step,
int sqsum_step,int sum_offset,int sqsum_offset)
{
int lid = get_local_id(0);
int gid = get_group_id(0);
float4 src_t[2], sum_t[2];
float4 sqsrc_t[2],sqsum_t[2];
TYPE4 sqsrc_t[2],sqsum_t[2];
__local float4 lm_sum[2][LSIZE + LOG_LSIZE];
__local float4 lm_sqsum[2][LSIZE + LOG_LSIZE];
__local TYPE4 lm_sqsum[2][LSIZE + LOG_LSIZE];
__local float *sum_p;
__local float *sqsum_p;
__local TYPE *sqsum_p;
src_step = src_step >> 4;
src1_step = (src1_step / sizeof(TYPE)) >> 2;
for(int i = 0; i < rows; i =i + LSIZE_1)
{
src_t[0] = i + lid < rows ? srcsum[(lid+i) * src_step + gid * 2] : (float4)0;
sqsrc_t[0] = i + lid < rows ? srcsqsum[(lid+i) * src_step + gid * 2] : (float4)0;
sqsrc_t[0] = i + lid < rows ? srcsqsum[(lid+i) * src1_step + gid * 2] : (TYPE4)0;
src_t[1] = i + lid < rows ? srcsum[(lid+i) * src_step + gid * 2 + 1] : (float4)0;
sqsrc_t[1] = i + lid < rows ? srcsqsum[(lid+i) * src_step + gid * 2 + 1] : (float4)0;
sqsrc_t[1] = i + lid < rows ? srcsqsum[(lid+i) * src1_step + gid * 2 + 1] : (TYPE4)0;
sum_t[0] = (i == 0 ? (float4)0 : lm_sum[0][LSIZE_2 + LOG_LSIZE]);
sqsum_t[0] = (i == 0 ? (float4)0 : lm_sqsum[0][LSIZE_2 + LOG_LSIZE]);
sqsum_t[0] = (i == 0 ? (TYPE4)0 : lm_sqsum[0][LSIZE_2 + LOG_LSIZE]);
sum_t[1] = (i == 0 ? (float4)0 : lm_sum[1][LSIZE_2 + LOG_LSIZE]);
sqsum_t[1] = (i == 0 ? (float4)0 : lm_sqsum[1][LSIZE_2 + LOG_LSIZE]);
sqsum_t[1] = (i == 0 ? (TYPE4)0 : lm_sqsum[1][LSIZE_2 + LOG_LSIZE]);
barrier(CLK_LOCAL_MEM_FENCE);
int bf_loc = lid + GET_CONFLICT_OFFSET(lid);
@ -456,16 +465,16 @@ kernel void integral_rows_D5(__global float4 *srcsum,__global float4 * srcsqsum,
if(i + lid == 0)
{
int loc0 = gid * 2 * sum_step;
int loc1 = gid * 2 * sqsum_step;
int loc1 = gid * 2 * CONVERT(sqsum_step);
for(int k = 1; k <= 8; k++)
{
if(gid * 8 + k > cols) break;
sum[sum_offset + loc0 + k * sum_step / 4] = 0;
sqsum[sqsum_offset + loc1 + k * sqsum_step / 4] = 0;
sqsum[sqsum_offset + loc1 + k * sqsum_step / sizeof(TYPE)] = 0;
}
}
int loc_s0 = sum_offset + gid * 2 * sum_step + sum_step / 4 + i + lid, loc_s1 = loc_s0 + sum_step ;
int loc_sq0 = sqsum_offset + gid * 2 * sqsum_step + sqsum_step / 4 + i + lid, loc_sq1 = loc_sq0 + sqsum_step ;
int loc_sq0 = sqsum_offset + gid * 2 * CONVERT(sqsum_step) + sqsum_step / sizeof(TYPE) + i + lid, loc_sq1 = loc_sq0 + CONVERT(sqsum_step) ;
if(lid > 0 && (i+lid) <= rows)
{
lm_sum[0][bf_loc] += sum_t[0];
@ -473,20 +482,20 @@ kernel void integral_rows_D5(__global float4 *srcsum,__global float4 * srcsqsum,
lm_sqsum[0][bf_loc] += sqsum_t[0];
lm_sqsum[1][bf_loc] += sqsum_t[1];
sum_p = (__local float*)(&(lm_sum[0][bf_loc]));
sqsum_p = (__local float*)(&(lm_sqsum[0][bf_loc]));
sqsum_p = (__local TYPE*)(&(lm_sqsum[0][bf_loc]));
for(int k = 0; k < 4; k++)
{
if(gid * 8 + k >= cols) break;
sum[loc_s0 + k * sum_step / 4] = sum_p[k];
sqsum[loc_sq0 + k * sqsum_step / 4] = sqsum_p[k];
sqsum[loc_sq0 + k * sqsum_step / sizeof(TYPE)] = sqsum_p[k];
}
sum_p = (__local float*)(&(lm_sum[1][bf_loc]));
sqsum_p = (__local float*)(&(lm_sqsum[1][bf_loc]));
sqsum_p = (__local TYPE*)(&(lm_sqsum[1][bf_loc]));
for(int k = 0; k < 4; k++)
{
if(gid * 8 + 4 + k >= cols) break;
sum[loc_s1 + k * sum_step / 4] = sum_p[k];
sqsum[loc_sq1 + k * sqsum_step / 4] = sqsum_p[k];
sqsum[loc_sq1 + k * sqsum_step / sizeof(TYPE)] = sqsum_p[k];
}
}
barrier(CLK_LOCAL_MEM_FENCE);

@ -275,23 +275,33 @@ OCL_TEST_P(CornerHarris, Mat)
//////////////////////////////////integral/////////////////////////////////////////////////
typedef ImgprocTestBase Integral;
struct Integral :
public ImgprocTestBase
{
int sdepth;
virtual void SetUp()
{
type = GET_PARAM(0);
blockSize = GET_PARAM(1);
sdepth = GET_PARAM(2);
useRoi = GET_PARAM(3);
}
};
OCL_TEST_P(Integral, Mat1)
{
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
ocl::integral(gsrc_roi, gdst_roi);
integral(src_roi, dst_roi);
ocl::integral(gsrc_roi, gdst_roi, sdepth);
integral(src_roi, dst_roi, sdepth);
Near();
}
}
// TODO wrong output type
OCL_TEST_P(Integral, DISABLED_Mat2)
OCL_TEST_P(Integral, Mat2)
{
Mat dst1;
ocl::oclMat gdst1;
@ -300,10 +310,12 @@ OCL_TEST_P(Integral, DISABLED_Mat2)
{
random_roi();
integral(src_roi, dst1, dst_roi);
ocl::integral(gsrc_roi, gdst1, gdst_roi);
integral(src_roi, dst_roi, dst1, sdepth);
ocl::integral(gsrc_roi, gdst_roi, gdst1, sdepth);
Near();
if(gdst1.clCxt->supportsFeature(ocl::FEATURE_CL_DOUBLE))
EXPECT_MAT_NEAR(dst1, Mat(gdst1), 0.);
}
}
@ -543,7 +555,7 @@ INSTANTIATE_TEST_CASE_P(Imgproc, CornerHarris, Combine(
INSTANTIATE_TEST_CASE_P(Imgproc, Integral, Combine(
Values((MatType)CV_8UC1), // TODO does not work with CV_32F, CV_64F
Values(0), // not used
Values(0), // not used
Values((MatType)CV_32SC1, (MatType)CV_32FC1),
Bool()));
INSTANTIATE_TEST_CASE_P(Imgproc, Threshold, Combine(

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