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submodule
opencv
Commits
bdaad9e1
Commit
bdaad9e1
authored
Nov 26, 2010
by
Alexey Spizhevoy
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added support of buffers into gpu::minMaxLoc, reduced memory requirements, refactored
parent
59e2afe4
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Showing
5 changed files
with
270 additions
and
209 deletions
+270
-209
gpu.hpp
modules/gpu/include/opencv2/gpu/gpu.hpp
+5
-0
arithm.cpp
modules/gpu/src/arithm.cpp
+56
-33
mathfunc.cu
modules/gpu/src/cuda/mathfunc.cu
+203
-174
arithm.cpp
tests/gpu/src/arithm.cpp
+5
-2
gputest_main.cpp
tests/gpu/src/gputest_main.cpp
+1
-0
No files found.
modules/gpu/include/opencv2/gpu/gpu.hpp
View file @
bdaad9e1
...
...
@@ -430,6 +430,11 @@ namespace cv
//! finds global minimum and maximum array elements and returns their values with locations
CV_EXPORTS
void
minMaxLoc
(
const
GpuMat
&
src
,
double
*
minVal
,
double
*
maxVal
=
0
,
Point
*
minLoc
=
0
,
Point
*
maxLoc
=
0
);
//! finds global minimum and maximum array elements and returns their values with locations
CV_EXPORTS
void
minMaxLoc
(
const
GpuMat
&
src
,
double
*
minVal
,
double
*
maxVal
,
Point
*
minLoc
,
Point
*
maxLoc
,
GpuMat
&
valbuf
,
GpuMat
&
locbuf
);
//! transforms 8-bit unsigned integers using lookup table: dst(i)=lut(src(i))
//! destination array will have the depth type as lut and the same channels number as source
//! supports CV_8UC1, CV_8UC3 types
...
...
modules/gpu/src/arithm.cpp
View file @
bdaad9e1
...
...
@@ -68,6 +68,7 @@ Scalar cv::gpu::sum(const GpuMat&) { throw_nogpu(); return Scalar(); }
void
cv
::
gpu
::
minMax
(
const
GpuMat
&
,
double
*
,
double
*
)
{
throw_nogpu
();
}
void
cv
::
gpu
::
minMax
(
const
GpuMat
&
,
double
*
,
double
*
,
GpuMat
&
)
{
throw_nogpu
();
}
void
cv
::
gpu
::
minMaxLoc
(
const
GpuMat
&
,
double
*
,
double
*
,
Point
*
,
Point
*
)
{
throw_nogpu
();
}
void
cv
::
gpu
::
minMaxLoc
(
const
GpuMat
&
,
double
*
,
double
*
,
Point
*
,
Point
*
,
GpuMat
&
,
GpuMat
&
)
{
throw_nogpu
();
}
void
cv
::
gpu
::
LUT
(
const
GpuMat
&
,
const
Mat
&
,
GpuMat
&
)
{
throw_nogpu
();
}
void
cv
::
gpu
::
exp
(
const
GpuMat
&
,
GpuMat
&
)
{
throw_nogpu
();
}
void
cv
::
gpu
::
log
(
const
GpuMat
&
,
GpuMat
&
)
{
throw_nogpu
();
}
...
...
@@ -514,8 +515,8 @@ void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, GpuMat&
{
using
namespace
mathfunc
::
minmax
;
double
m
ax
Val_
;
if
(
!
maxVal
)
maxVal
=
&
maxVal_
;
double
m
inVal_
;
if
(
!
minVal
)
minVal
=
&
min
Val_
;
double
maxVal_
;
if
(
!
maxVal
)
maxVal
=
&
maxVal_
;
GpuMat
src_
=
src
.
reshape
(
1
);
...
...
@@ -561,53 +562,75 @@ void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, GpuMat&
namespace
cv
{
namespace
gpu
{
namespace
mathfunc
{
namespace
minmaxloc
{
void
get_buf_size_required
(
int
elem_size
,
int
&
b1cols
,
int
&
b1rows
,
int
&
b2cols
,
int
&
b2rows
);
template
<
typename
T
>
void
min_max_loc_caller
(
const
DevMem2D
src
,
double
*
minval
,
double
*
maxval
,
int
*
minlocx
,
int
*
minlocy
,
int
*
maxlocx
,
int
*
maxlocy
);
int
minloc
[
2
],
int
maxloc
[
2
],
PtrStep
valbuf
,
PtrStep
locbuf
);
template
<
typename
T
>
void
min_max_loc_caller_2steps
(
const
DevMem2D
src
,
double
*
minval
,
double
*
maxval
,
int
minloc
[
2
],
int
maxloc
[
2
],
PtrStep
valbuf
,
PtrStep
locbuf
);
}}}}
void
cv
::
gpu
::
minMaxLoc
(
const
GpuMat
&
src
,
double
*
minVal
,
double
*
maxVal
,
Point
*
minLoc
,
Point
*
maxLoc
)
{
using
namespace
mathfunc
::
minmaxloc
;
GpuMat
valbuf
,
locbuf
;
minMaxLoc
(
src
,
minVal
,
maxVal
,
minLoc
,
maxLoc
,
valbuf
,
locbuf
);
}
void
cv
::
gpu
::
minMaxLoc
(
const
GpuMat
&
src
,
double
*
minVal
,
double
*
maxVal
,
Point
*
minLoc
,
Point
*
maxLoc
,
GpuMat
&
valbuf
,
GpuMat
&
locbuf
)
{
using
namespace
mathfunc
::
minmaxloc
;
CV_Assert
(
src
.
channels
()
==
1
);
double
maxVal_
;
if
(
!
maxVal
)
maxVal
=
&
maxVal_
;
double
minVal_
;
if
(
!
minVal
)
minVal
=
&
minVal_
;
double
maxVal_
;
if
(
!
maxVal
)
maxVal
=
&
maxVal_
;
int
minLoc_
[
2
];
int
maxLoc_
[
2
];
cv
::
Point
minLoc_
;
if
(
!
minLoc
)
minLoc
=
&
minLoc_
;
Size
valbuf_size
,
locbuf_size
;
get_buf_size_required
(
src
.
elemSize
(),
valbuf_size
.
width
,
valbuf_size
.
height
,
locbuf_size
.
width
,
locbuf_size
.
height
);
valbuf
.
create
(
valbuf_size
,
CV_8U
);
locbuf
.
create
(
locbuf_size
,
CV_8U
);
cv
::
Point
maxLoc_
;
if
(
!
maxLoc
)
maxLoc
=
&
maxLoc_
;
int
major
,
minor
;
getComputeCapability
(
getDevice
(),
major
,
minor
)
;
if
(
major
>=
1
&&
minor
>=
1
)
{
switch
(
src
.
type
())
{
case
CV_8U
:
min_max_loc_caller
<
unsigned
char
>
(
src
,
minVal
,
maxVal
,
&
minLoc
->
x
,
&
minLoc
->
y
,
&
maxLoc
->
x
,
&
maxLoc
->
y
);
break
;
case
CV_8S
:
min_max_loc_caller
<
signed
char
>
(
src
,
minVal
,
maxVal
,
&
minLoc
->
x
,
&
minLoc
->
y
,
&
maxLoc
->
x
,
&
maxLoc
->
y
);
break
;
case
CV_16U
:
min_max_loc_caller
<
unsigned
short
>
(
src
,
minVal
,
maxVal
,
&
minLoc
->
x
,
&
minLoc
->
y
,
&
maxLoc
->
x
,
&
maxLoc
->
y
);
break
;
case
CV_16S
:
min_max_loc_caller
<
signed
short
>
(
src
,
minVal
,
maxVal
,
&
minLoc
->
x
,
&
minLoc
->
y
,
&
maxLoc
->
x
,
&
maxLoc
->
y
);
break
;
case
CV_32S
:
min_max_loc_caller
<
int
>
(
src
,
minVal
,
maxVal
,
&
minLoc
->
x
,
&
minLoc
->
y
,
&
maxLoc
->
x
,
&
maxLoc
->
y
);
break
;
case
CV_32F
:
min_max_loc_caller
<
float
>
(
src
,
minVal
,
maxVal
,
&
minLoc
->
x
,
&
minLoc
->
y
,
&
maxLoc
->
x
,
&
maxLoc
->
y
);
break
;
case
CV_64F
:
min_max_loc_caller
<
double
>
(
src
,
minVal
,
maxVal
,
&
minLoc
->
x
,
&
minLoc
->
y
,
&
maxLoc
->
x
,
&
maxLoc
->
y
);
break
;
default
:
CV_Error
(
CV_StsBadArg
,
"Unsupported type"
);
case
CV_8U
:
min_max_loc_caller
<
unsigned
char
>
(
src
,
minVal
,
maxVal
,
minLoc_
,
maxLoc_
,
valbuf
,
locbuf
);
break
;
case
CV_8S
:
min_max_loc_caller
<
signed
char
>
(
src
,
minVal
,
maxVal
,
minLoc_
,
maxLoc_
,
valbuf
,
locbuf
);
break
;
case
CV_16U
:
min_max_loc_caller
<
unsigned
short
>
(
src
,
minVal
,
maxVal
,
minLoc_
,
maxLoc_
,
valbuf
,
locbuf
);
break
;
case
CV_16S
:
min_max_loc_caller
<
signed
short
>
(
src
,
minVal
,
maxVal
,
minLoc_
,
maxLoc_
,
valbuf
,
locbuf
);
break
;
case
CV_32S
:
min_max_loc_caller
<
int
>
(
src
,
minVal
,
maxVal
,
minLoc_
,
maxLoc_
,
valbuf
,
locbuf
);
break
;
case
CV_32F
:
min_max_loc_caller
<
float
>
(
src
,
minVal
,
maxVal
,
minLoc_
,
maxLoc_
,
valbuf
,
locbuf
);
break
;
case
CV_64F
:
min_max_loc_caller
<
double
>
(
src
,
minVal
,
maxVal
,
minLoc_
,
maxLoc_
,
valbuf
,
locbuf
);
break
;
default
:
CV_Error
(
CV_StsBadArg
,
"Unsupported type"
);
}
}
else
{
switch
(
src
.
type
())
{
case
CV_8U
:
min_max_loc_caller_2steps
<
unsigned
char
>
(
src
,
minVal
,
maxVal
,
minLoc_
,
maxLoc_
,
valbuf
,
locbuf
);
break
;
case
CV_8S
:
min_max_loc_caller_2steps
<
signed
char
>
(
src
,
minVal
,
maxVal
,
minLoc_
,
maxLoc_
,
valbuf
,
locbuf
);
break
;
case
CV_16U
:
min_max_loc_caller_2steps
<
unsigned
short
>
(
src
,
minVal
,
maxVal
,
minLoc_
,
maxLoc_
,
valbuf
,
locbuf
);
break
;
case
CV_16S
:
min_max_loc_caller_2steps
<
signed
short
>
(
src
,
minVal
,
maxVal
,
minLoc_
,
maxLoc_
,
valbuf
,
locbuf
);
break
;
case
CV_32S
:
min_max_loc_caller_2steps
<
int
>
(
src
,
minVal
,
maxVal
,
minLoc_
,
maxLoc_
,
valbuf
,
locbuf
);
break
;
case
CV_32F
:
min_max_loc_caller_2steps
<
float
>
(
src
,
minVal
,
maxVal
,
minLoc_
,
maxLoc_
,
valbuf
,
locbuf
);
break
;
default
:
CV_Error
(
CV_StsBadArg
,
"Unsupported type"
);
}
}
if
(
minLoc
)
{
minLoc
->
x
=
minLoc_
[
0
];
minLoc
->
y
=
minLoc_
[
1
];
}
if
(
maxLoc
)
{
maxLoc
->
x
=
maxLoc_
[
0
];
maxLoc
->
y
=
maxLoc_
[
1
];
}
}
////////////////////////////////////////////////////////////////////////
...
...
modules/gpu/src/cuda/mathfunc.cu
View file @
bdaad9e1
...
...
@@ -412,8 +412,6 @@ namespace cv { namespace gpu { namespace mathfunc
template <> struct MinMaxTypeTraits<float> { typedef float best_type; };
template <> struct MinMaxTypeTraits<double> { typedef double best_type; };
// Available optimization operations
enum { OP_MIN, OP_MAX };
namespace minmax
{
...
...
@@ -466,7 +464,7 @@ namespace cv { namespace gpu { namespace mathfunc
template <int nthreads, typename T>
__global__ void min_max_kernel(
int cols, int rows, const PtrStep
src, T* minval, T* maxval)
__global__ void min_max_kernel(
const DevMem2D
src, T* minval, T* maxval)
{
typedef typename MinMaxTypeTraits<T>::best_type best_type;
__shared__ best_type sminval[nthreads];
...
...
@@ -479,10 +477,10 @@ namespace cv { namespace gpu { namespace mathfunc
T val;
T mymin = numeric_limits_gpu<T>::max();
T mymax = numeric_limits_gpu<T>::min();
for (unsigned int y = 0; y < ctheight && y0 + y * blockDim.y < rows; ++y)
for (unsigned int y = 0; y < ctheight && y0 + y * blockDim.y <
src.
rows; ++y)
{
const T* ptr = (const T*)src.ptr(y0 + y * blockDim.y);
for (unsigned int x = 0; x < ctwidth && x0 + x * blockDim.x < cols; ++x)
for (unsigned int x = 0; x < ctwidth && x0 + x * blockDim.x <
src.
cols; ++x)
{
val = ptr[x0 + x * blockDim.x];
mymin = min(mymin, val);
...
...
@@ -509,8 +507,6 @@ namespace cv { namespace gpu { namespace mathfunc
if (nthreads >= 2) merge(tid, 1, sminval, smaxval);
}
__syncthreads();
if (tid == 0)
{
minval[blockIdx.y * gridDim.x + blockIdx.x] = (T)sminval[0];
...
...
@@ -525,9 +521,9 @@ namespace cv { namespace gpu { namespace mathfunc
__threadfence();
if (atomicInc(&blocks_finished, gridDim.x * gridDim.y) == gridDim.x * gridDim.y - 1)
{
mymin =
numeric_limits_gpu<T>::max()
;
mymax =
numeric_limits_gpu<T>::min()
;
for (unsigned int i =
0
; i < gridDim.x * gridDim.y; ++i)
mymin =
minval[0]
;
mymax =
maxval[0]
;
for (unsigned int i =
1
; i < gridDim.x * gridDim.y; ++i)
{
mymin = min(mymin, minval[i]);
mymax = max(mymax, maxval[i]);
...
...
@@ -552,7 +548,7 @@ namespace cv { namespace gpu { namespace mathfunc
T* maxval_buf = (T*)buf.ptr(1);
cudaSafeCall(cudaMemcpyToSymbol(blocks_finished, &czero, sizeof(blocks_finished)));
min_max_kernel<256, T><<<grid, threads>>>(src
.cols, src.rows, src
, minval_buf, maxval_buf);
min_max_kernel<256, T><<<grid, threads>>>(src, minval_buf, maxval_buf);
cudaSafeCall(cudaThreadSynchronize());
T minval_, maxval_;
...
...
@@ -576,9 +572,9 @@ namespace cv { namespace gpu { namespace mathfunc
__global__ void min_max_kernel_2ndstep(T* minval, T* maxval, int size)
{
T val;
T mymin =
numeric_limits_gpu<T>::max()
;
T mymax =
numeric_limits_gpu<T>::min()
;
for (unsigned int i =
0
; i < size; ++i)
T mymin =
minval[0]
;
T mymax =
maxval[0]
;
for (unsigned int i =
1
; i < size; ++i)
{
val = minval[i]; if (val < mymin) mymin = val;
val = maxval[i]; if (val > mymax) mymax = val;
...
...
@@ -599,7 +595,7 @@ namespace cv { namespace gpu { namespace mathfunc
T* maxval_buf = (T*)buf.ptr(1);
cudaSafeCall(cudaMemcpyToSymbol(blocks_finished, &czero, sizeof(blocks_finished)));
min_max_kernel<256, T><<<grid, threads>>>(src
.cols, src.rows, src
, minval_buf, maxval_buf);
min_max_kernel<256, T><<<grid, threads>>>(src, minval_buf, maxval_buf);
min_max_kernel_2ndstep<T><<<1, 1>>>(minval_buf, maxval_buf, grid.x * grid.y);
cudaSafeCall(cudaThreadSynchronize());
...
...
@@ -622,220 +618,253 @@ namespace cv { namespace gpu { namespace mathfunc
namespace minmaxloc {
template <typename T, int op> struct OptLoc {};
__constant__ int ctwidth;
__constant__ int ctheight;
template <typename T>
struct OptLoc<T, OP_MIN>
{
static __device__ void call(unsigned int tid, unsigned int offset, volatile T* optval, volatile unsigned int* optloc)
static const unsigned int czero = 0;
// Global counter of blocks finished its work
__device__ unsigned int blocks_finished;
// Estimates good thread configuration
// - threads variable satisfies to threads.x * threads.y == 256
void estimate_thread_cfg(dim3& threads, dim3& grid)
{
T val = optval[tid + offset];
if (val < optval[tid])
threads = dim3(64, 4);
grid = dim3(6, 5);
}
// Returns required buffer sizes
void get_buf_size_required(int elem_size, int& b1cols, int& b1rows,
int& b2cols, int& b2rows)
{
optval[tid] = val;
optloc[tid] = optloc[tid + offset];
dim3 threads, grid;
estimate_thread_cfg(threads, grid);
b1cols = grid.x * grid.y * elem_size; // For values
b1rows = 2;
b2cols = grid.x * grid.y * sizeof(int); // For locations
b2rows = 2;
}
// Estimates device constants which are used in the kernels using specified thread configuration
void estimate_kernel_consts(int cols, int rows, const dim3& threads, const dim3& grid)
{
int twidth = divUp(divUp(cols, grid.x), threads.x);
int theight = divUp(divUp(rows, grid.y), threads.y);
cudaSafeCall(cudaMemcpyToSymbol(ctwidth, &twidth, sizeof(ctwidth)));
cudaSafeCall(cudaMemcpyToSymbol(ctheight, &theight, sizeof(ctheight)));
}
};
template <typename T>
struct OptLoc<T, OP_MAX>
__device__ void merge(unsigned int tid, unsigned int offset, volatile T* minval, volatile T* maxval,
volatile unsigned int* minloc, volatile unsigned int* maxloc)
{
static __device__ void call(unsigned int tid, unsigned int offset, volatile T* optval, volatile unsigned int* optloc)
T val = minval[tid + offset];
if (val < minval[tid])
{
T val = optval[tid + offset];
if (val > optval[tid])
minval[tid] = val;
minloc[tid] = minloc[tid + offset];
}
val = maxval[tid + offset];
if (val > maxval[tid])
{
opt
val[tid] = val;
optloc[tid] = opt
loc[tid + offset];
max
val[tid] = val;
maxloc[tid] = max
loc[tid + offset];
}
}
};
template <int nthreads, int op, typename T>
__global__ void opt_loc_init_kernel(int cols, int rows, const PtrStep src, PtrStep optval, PtrStep optloc)
template <int nthreads, typename T>
__global__ void min_max_loc_kernel(const DevMem2D src, T* minval, T* maxval,
unsigned int* minloc, unsigned int* maxloc)
{
typedef typename MinMaxTypeTraits<T>::best_type best_type;
__shared__ best_type soptval[nthreads];
__shared__ unsigned int soptloc[nthreads];
__shared__ best_type sminval[nthreads];
__shared__ best_type smaxval[nthreads];
__shared__ unsigned int sminloc[nthreads];
__shared__ unsigned int smaxloc[nthreads];
unsigned int x0 = blockIdx.x * blockDim.x;
unsigned int y0 = blockIdx.y * blockDim.y;
unsigned int x0 = blockIdx.x * blockDim.x
* ctwidth + threadIdx.x
;
unsigned int y0 = blockIdx.y * blockDim.y
* ctheight + threadIdx.y
;
unsigned int tid = threadIdx.y * blockDim.x + threadIdx.x;
if (x0 + threadIdx.x < cols && y0 + threadIdx.y < rows)
T val = ((const T*)src.ptr(0))[0];
T mymin = val, mymax = val;
unsigned int myminloc = 0, mymaxloc = 0;
for (unsigned int y = 0; y < ctheight && y0 + y * blockDim.y < src.rows; ++y)
{
const T* ptr = (const T*)src.ptr(y0 + y * blockDim.y);
for (unsigned int x = 0; x < ctwidth && x0 + x * blockDim.x < src.cols; ++x)
{
soptval[tid] = ((const T*)src.ptr(y0 + threadIdx.y))[x0 + threadIdx.x];
soptloc[tid] = (y0 + threadIdx.y) * cols + x0 + threadIdx.x;
val = ptr[x0 + x * blockDim.x];
if (val < mymin)
{
mymin = val;
myminloc = (y0 + y * blockDim.y) * src.cols + x0 + x * blockDim.x;
}
else
else if (val > mymax)
{
soptval[tid] = ((const T*)src.ptr(y0))[x0];
soptloc[tid] = y0 * cols + x0;
mymax = val;
mymaxloc = (y0 + y * blockDim.y) * src.cols + x0 + x * blockDim.x;
}
}
}
sminval[tid] = mymin;
smaxval[tid] = mymax;
sminloc[tid] = myminloc;
smaxloc[tid] = mymaxloc;
__syncthreads();
if (nthreads >= 512) if (tid < 256) {
OptLoc<best_type, op>::call(tid, 256, soptval, sopt
loc); __syncthreads(); }
if (nthreads >= 256) if (tid < 128) {
OptLoc<best_type, op>::call(tid, 128, soptval, sopt
loc); __syncthreads(); }
if (nthreads >= 128) if (tid < 64) {
OptLoc<best_type, op>::call(tid, 64, soptval, sopt
loc); __syncthreads(); }
if (nthreads >= 512) if (tid < 256) {
merge(tid, 256, sminval, smaxval, sminloc, smax
loc); __syncthreads(); }
if (nthreads >= 256) if (tid < 128) {
merge(tid, 128, sminval, smaxval, sminloc, smax
loc); __syncthreads(); }
if (nthreads >= 128) if (tid < 64) {
merge(tid, 64, sminval, smaxval, sminloc, smax
loc); __syncthreads(); }
if (tid < 32)
{
if (nthreads >= 64)
OptLoc<best_type, op>::call(tid, 32, soptval, sopt
loc);
if (nthreads >= 32)
OptLoc<best_type, op>::call(tid, 16, soptval, sopt
loc);
if (nthreads >= 16)
OptLoc<best_type, op>::call(tid, 8, soptval, sopt
loc);
if (nthreads >= 8)
OptLoc<best_type, op>::call(tid, 4, soptval, sopt
loc);
if (nthreads >= 4)
OptLoc<best_type, op>::call(tid, 2, soptval, sopt
loc);
if (nthreads >= 2)
OptLoc<best_type, op>::call(tid, 1, soptval, sopt
loc);
if (nthreads >= 64)
merge(tid, 32, sminval, smaxval, sminloc, smax
loc);
if (nthreads >= 32)
merge(tid, 16, sminval, smaxval, sminloc, smax
loc);
if (nthreads >= 16)
merge(tid, 8, sminval, smaxval, sminloc, smax
loc);
if (nthreads >= 8)
merge(tid, 4, sminval, smaxval, sminloc, smax
loc);
if (nthreads >= 4)
merge(tid, 2, sminval, smaxval, sminloc, smax
loc);
if (nthreads >= 2)
merge(tid, 1, sminval, smaxval, sminloc, smax
loc);
}
if (tid == 0)
{
((T*)optval.ptr(blockIdx.y))[blockIdx.x] = (T)soptval[0];
((unsigned int*)optloc.ptr(blockIdx.y))[blockIdx.x] = soptloc[0];
}
minval[blockIdx.y * gridDim.x + blockIdx.x] = (T)sminval[0];
maxval[blockIdx.y * gridDim.x + blockIdx.x] = (T)smaxval[0];
minloc[blockIdx.y * gridDim.x + blockIdx.x] = sminloc[0];
maxloc[blockIdx.y * gridDim.x + blockIdx.x] = smaxloc[0];
}
template <int nthreads, int op, typename T>
__global__ void opt_loc_kernel(int cols, int rows, const PtrStep src, const PtrStep loc, PtrStep optval, PtrStep optloc)
{
typedef typename MinMaxTypeTraits<T>::best_type best_type;
__shared__ best_type soptval[nthreads];
__shared__ unsigned int soptloc[nthreads];
unsigned int x0 = blockIdx.x * blockDim.x;
unsigned int y0 = blockIdx.y * blockDim.y;
unsigned int tid = threadIdx.y * blockDim.x + threadIdx.x;
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 110
if (x0 + threadIdx.x < cols && y0 + threadIdx.y < rows)
// Process partial results in the first thread of the last block
if ((gridDim.x > 1 || gridDim.y > 1) && tid == 0)
{
soptval[tid] = ((const T*)src.ptr(y0 + threadIdx.y))[x0 + threadIdx.x];
soptloc[tid] = ((const unsigned int*)loc.ptr(y0 + threadIdx.y))[x0 + threadIdx.x];
}
else
__threadfence();
if (atomicInc(&blocks_finished, gridDim.x * gridDim.y) == gridDim.x * gridDim.y - 1)
{
soptval[tid] = ((const T*)src.ptr(y0))[x0];
soptloc[tid] = ((const unsigned int*)loc.ptr(y0))[x0];
mymin = minval[0];
mymax = maxval[0];
unsigned int imin = 0, imax = 0;
for (unsigned int i = 1; i < gridDim.x * gridDim.y; ++i)
{
val = minval[i]; if (val < mymin) { mymin = val; imin = i; }
val = maxval[i]; if (val > mymax) { mymax = val; imax = i; }
}
minval[0] = mymin;
maxval[0] = mymax;
minloc[0] = minloc[imin];
maxloc[0] = maxloc[imax];
}
}
#endif
}
__syncthreads();
if (nthreads >= 512) if (tid < 256) { OptLoc<best_type, op>::call(tid, 256, soptval, soptloc); __syncthreads(); }
if (nthreads >= 256) if (tid < 128) { OptLoc<best_type, op>::call(tid, 128, soptval, soptloc); __syncthreads(); }
if (nthreads >= 128) if (tid < 64) { OptLoc<best_type, op>::call(tid, 64, soptval, soptloc); __syncthreads(); }
if (tid < 32)
template <typename T>
void min_max_loc_caller(const DevMem2D src, double* minval, double* maxval,
int minloc[2], int maxloc[2], PtrStep valbuf, PtrStep locbuf)
{
if (nthreads >= 64) OptLoc<best_type, op>::call(tid, 32, soptval, soptloc);
if (nthreads >= 32) OptLoc<best_type, op>::call(tid, 16, soptval, soptloc);
if (nthreads >= 16) OptLoc<best_type, op>::call(tid, 8, soptval, soptloc);
if (nthreads >= 8) OptLoc<best_type, op>::call(tid, 4, soptval, soptloc);
if (nthreads >= 4) OptLoc<best_type, op>::call(tid, 2, soptval, soptloc);
if (nthreads >= 2) OptLoc<best_type, op>::call(tid, 1, soptval, soptloc);
dim3 threads, grid;
estimate_thread_cfg(threads, grid);
estimate_kernel_consts(src.cols, src.rows, threads, grid);
T* minval_buf = (T*)valbuf.ptr(0);
T* maxval_buf = (T*)valbuf.ptr(1);
unsigned int* minloc_buf = (unsigned int*)locbuf.ptr(0);
unsigned int* maxloc_buf = (unsigned int*)locbuf.ptr(1);
cudaSafeCall(cudaMemcpyToSymbol(blocks_finished, &czero, sizeof(blocks_finished)));
min_max_loc_kernel<256, T><<<grid, threads>>>(src, minval_buf, maxval_buf, minloc_buf, maxloc_buf);
cudaSafeCall(cudaThreadSynchronize());
T minval_, maxval_;
cudaSafeCall(cudaMemcpy(&minval_, minval_buf, sizeof(T), cudaMemcpyDeviceToHost));
cudaSafeCall(cudaMemcpy(&maxval_, maxval_buf, sizeof(T), cudaMemcpyDeviceToHost));
*minval = minval_;
*maxval = maxval_;
unsigned int minloc_, maxloc_;
cudaSafeCall(cudaMemcpy(&minloc_, minloc_buf, sizeof(int), cudaMemcpyDeviceToHost));
cudaSafeCall(cudaMemcpy(&maxloc_, maxloc_buf, sizeof(int), cudaMemcpyDeviceToHost));
minloc[1] = minloc_ / src.cols; minloc[0] = minloc_ - minloc[1] * src.cols;
maxloc[1] = maxloc_ / src.cols; maxloc[0] = maxloc_ - maxloc[1] * src.cols;
}
if (tid == 0)
template void min_max_loc_caller<unsigned char>(const DevMem2D, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_caller<signed char>(const DevMem2D, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_caller<unsigned short>(const DevMem2D, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_caller<signed short>(const DevMem2D, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_caller<int>(const DevMem2D, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_caller<float>(const DevMem2D, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_caller<double>(const DevMem2D, double*, double*, int[2], int[2], PtrStep, PtrStep);
// This kernel will be used only when compute capability is 1.0
template <typename T>
__global__ void min_max_loc_kernel_2ndstep(T* minval, T* maxval, unsigned int* minloc, unsigned int* maxloc, int size)
{
((T*)optval.ptr(blockIdx.y))[blockIdx.x] = (T)soptval[0];
((unsigned int*)optloc.ptr(blockIdx.y))[blockIdx.x] = soptloc[0];
T val;
T mymin = minval[0];
T mymax = maxval[0];
unsigned int imin = 0, imax = 0;
for (unsigned int i = 1; i < size; ++i)
{
val = minval[i]; if (val < mymin) { mymin = val; imin = i; }
val = maxval[i]; if (val > mymax) { mymax = val; imax = i; }
}
minval[0] = mymin;
maxval[0] = mymax;
minloc[0] = minloc[imin];
maxloc[0] = maxloc[imax];
}
template <typename T>
void min_max_loc_caller(const DevMem2D src, double* minval, double* maxval, int* minlocx, int* minlocy,
int* maxlocx, int* maxlocy)
{
dim3 threads(32, 8);
// Allocate memory for aux. buffers
DevMem2D minval_buf[2];
minval_buf[0].cols = divUp(src.cols, threads.x);
minval_buf[0].rows = divUp(src.rows, threads.y);
minval_buf[1].cols = divUp(minval_buf[0].cols, threads.x);
minval_buf[1].rows = divUp(minval_buf[0].rows, threads.y);
cudaSafeCall(cudaMallocPitch(&minval_buf[0].data, &minval_buf[0].step, minval_buf[0].cols * sizeof(T), minval_buf[0].rows));
cudaSafeCall(cudaMallocPitch(&minval_buf[1].data, &minval_buf[1].step, minval_buf[1].cols * sizeof(T), minval_buf[1].rows));
DevMem2D maxval_buf[2];
maxval_buf[0].cols = divUp(src.cols, threads.x);
maxval_buf[0].rows = divUp(src.rows, threads.y);
maxval_buf[1].cols = divUp(maxval_buf[0].cols, threads.x);
maxval_buf[1].rows = divUp(maxval_buf[0].rows, threads.y);
cudaSafeCall(cudaMallocPitch(&maxval_buf[0].data, &maxval_buf[0].step, maxval_buf[0].cols * sizeof(T), maxval_buf[0].rows));
cudaSafeCall(cudaMallocPitch(&maxval_buf[1].data, &maxval_buf[1].step, maxval_buf[1].cols * sizeof(T), maxval_buf[1].rows));
DevMem2D minloc_buf[2];
minloc_buf[0].cols = divUp(src.cols, threads.x);
minloc_buf[0].rows = divUp(src.rows, threads.y);
minloc_buf[1].cols = divUp(minloc_buf[0].cols, threads.x);
minloc_buf[1].rows = divUp(minloc_buf[0].rows, threads.y);
cudaSafeCall(cudaMallocPitch(&minloc_buf[0].data, &minloc_buf[0].step, minloc_buf[0].cols * sizeof(int), minloc_buf[0].rows));
cudaSafeCall(cudaMallocPitch(&minloc_buf[1].data, &minloc_buf[1].step, minloc_buf[1].cols * sizeof(int), minloc_buf[1].rows));
DevMem2D maxloc_buf[2];
maxloc_buf[0].cols = divUp(src.cols, threads.x);
maxloc_buf[0].rows = divUp(src.rows, threads.y);
maxloc_buf[1].cols = divUp(maxloc_buf[0].cols, threads.x);
maxloc_buf[1].rows = divUp(maxloc_buf[0].rows, threads.y);
cudaSafeCall(cudaMallocPitch(&maxloc_buf[0].data, &maxloc_buf[0].step, maxloc_buf[0].cols * sizeof(int), maxloc_buf[0].rows));
cudaSafeCall(cudaMallocPitch(&maxloc_buf[1].data, &maxloc_buf[1].step, maxloc_buf[1].cols * sizeof(int), maxloc_buf[1].rows));
int curbuf = 0;
dim3 cursize(src.cols, src.rows);
dim3 grid(divUp(cursize.x, threads.x), divUp(cursize.y, threads.y));
opt_loc_init_kernel<256, OP_MIN, T><<<grid, threads>>>(cursize.x, cursize.y, src, minval_buf[curbuf], minloc_buf[curbuf]);
opt_loc_init_kernel<256, OP_MAX, T><<<grid, threads>>>(cursize.x, cursize.y, src, maxval_buf[curbuf], maxloc_buf[curbuf]);
cursize = grid;
while (cursize.x > 1 || cursize.y > 1)
{
grid.x = divUp(cursize.x, threads.x);
grid.y = divUp(cursize.y, threads.y);
opt_loc_kernel<256, OP_MIN, T><<<grid, threads>>>(cursize.x, cursize.y, minval_buf[curbuf], minloc_buf[curbuf],
minval_buf[1 - curbuf], minloc_buf[1 - curbuf]);
opt_loc_kernel<256, OP_MAX, T><<<grid, threads>>>(cursize.x, cursize.y, maxval_buf[curbuf], maxloc_buf[curbuf],
maxval_buf[1 - curbuf], maxloc_buf[1 - curbuf]);
curbuf = 1 - curbuf;
cursize = grid;
}
void min_max_loc_caller_2steps(const DevMem2D src, double* minval, double* maxval,
int minloc[2], int maxloc[2], PtrStep valbuf, PtrStep locbuf)
{
dim3 threads, grid;
estimate_thread_cfg(threads, grid);
estimate_kernel_consts(src.cols, src.rows, threads, grid);
cudaSafeCall(cudaThreadSynchronize());
T* minval_buf = (T*)valbuf.ptr(0);
T* maxval_buf = (T*)valbuf.ptr(1);
unsigned int* minloc_buf = (unsigned int*)locbuf.ptr(0);
unsigned int* maxloc_buf = (unsigned int*)locbuf.ptr(1);
// Copy results from device to host
cudaSafeCall(cudaMemcpyToSymbol(blocks_finished, &czero, sizeof(blocks_finished)));
min_max_loc_kernel<256, T><<<grid, threads>>>(src, minval_buf, maxval_buf, minloc_buf, maxloc_buf);
min_max_loc_kernel_2ndstep<T><<<1, 1>>>(minval_buf, maxval_buf, minloc_buf, maxloc_buf, grid.x * grid.y);
cudaSafeCall(cudaThreadSynchronize());
T minval_, maxval_;
cudaSafeCall(cudaMemcpy(&minval_, minval_buf
[curbuf].ptr(0)
, sizeof(T), cudaMemcpyDeviceToHost));
cudaSafeCall(cudaMemcpy(&maxval_, maxval_buf
[curbuf].ptr(0)
, sizeof(T), cudaMemcpyDeviceToHost));
cudaSafeCall(cudaMemcpy(&minval_, minval_buf, sizeof(T), cudaMemcpyDeviceToHost));
cudaSafeCall(cudaMemcpy(&maxval_, maxval_buf, sizeof(T), cudaMemcpyDeviceToHost));
*minval = minval_;
*maxval = maxval_;
unsigned int minloc, maxloc;
cudaSafeCall(cudaMemcpy(&minloc, minloc_buf[curbuf].ptr(0), sizeof(int), cudaMemcpyDeviceToHost));
cudaSafeCall(cudaMemcpy(&maxloc, maxloc_buf[curbuf].ptr(0), sizeof(int), cudaMemcpyDeviceToHost));
*minlocy = minloc / src.cols; *minlocx = minloc - *minlocy * src.cols;
*maxlocy = maxloc / src.cols; *maxlocx = maxloc - *maxlocy * src.cols;
// Release aux. buffers
cudaSafeCall(cudaFree(minval_buf[0].data));
cudaSafeCall(cudaFree(minval_buf[1].data));
cudaSafeCall(cudaFree(maxval_buf[0].data));
cudaSafeCall(cudaFree(maxval_buf[1].data));
cudaSafeCall(cudaFree(minloc_buf[0].data));
cudaSafeCall(cudaFree(minloc_buf[1].data));
cudaSafeCall(cudaFree(maxloc_buf[0].data));
cudaSafeCall(cudaFree(maxloc_buf[1].data));
}
template void min_max_loc_caller<unsigned char>(const DevMem2D, double*, double*, int*, int*, int*, int*);
template void min_max_loc_caller<signed char>(const DevMem2D, double*, double*, int*, int*, int*, int*);
template void min_max_loc_caller<unsigned short>(const DevMem2D, double*, double*, int*, int*, int*, int*);
template void min_max_loc_caller<signed short>(const DevMem2D, double*, double*, int*, int*, int*, int*);
template void min_max_loc_caller<int>(const DevMem2D, double*, double*, int*, int*, int*, int*);
template void min_max_loc_caller<float>(const DevMem2D, double*, double*, int*, int*, int*, int*);
template void min_max_loc_caller<double>(const DevMem2D, double*, double*, int*, int*, int*, int*);
unsigned int minloc_, maxloc_;
cudaSafeCall(cudaMemcpy(&minloc_, minloc_buf, sizeof(int), cudaMemcpyDeviceToHost));
cudaSafeCall(cudaMemcpy(&maxloc_, maxloc_buf, sizeof(int), cudaMemcpyDeviceToHost));
minloc[1] = minloc_ / src.cols; minloc[0] = minloc_ - minloc[1] * src.cols;
maxloc[1] = maxloc_ / src.cols; maxloc[0] = maxloc_ - maxloc[1] * src.cols;
}
template void min_max_loc_caller_2steps<unsigned char>(const DevMem2D, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_caller_2steps<signed char>(const DevMem2D, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_caller_2steps<unsigned short>(const DevMem2D, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_caller_2steps<signed short>(const DevMem2D, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_caller_2steps<int>(const DevMem2D, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_caller_2steps<float>(const DevMem2D, double*, double*, int[2], int[2], PtrStep, PtrStep);
} // namespace minmaxloc
...
...
tests/gpu/src/arithm.cpp
View file @
bdaad9e1
...
...
@@ -683,7 +683,7 @@ struct CV_GpuMinMaxTest: public CvTest
int
depth_end
;
int
major
,
minor
;
cv
::
gpu
::
getComputeCapability
(
getDevice
(),
major
,
minor
);
minor
=
0
;
if
(
minor
>=
1
)
depth_end
=
CV_64F
;
else
depth_end
=
CV_32F
;
for
(
int
cn
=
1
;
cn
<=
4
;
++
cn
)
...
...
@@ -757,11 +757,14 @@ struct CV_GpuMinMaxLocTest: public CvTest
{
CV_GpuMinMaxLocTest
()
:
CvTest
(
"GPU-MinMaxLocTest"
,
"minMaxLoc"
)
{}
GpuMat
valbuf
,
locbuf
;
void
run
(
int
)
{
int
depth_end
;
int
major
,
minor
;
cv
::
gpu
::
getComputeCapability
(
getDevice
(),
major
,
minor
);
if
(
minor
>=
1
)
depth_end
=
CV_64F
;
else
depth_end
=
CV_32F
;
for
(
int
depth
=
CV_8U
;
depth
<=
depth_end
;
++
depth
)
{
...
...
@@ -807,7 +810,7 @@ struct CV_GpuMinMaxLocTest: public CvTest
double
minVal_
,
maxVal_
;
cv
::
Point
minLoc_
,
maxLoc_
;
cv
::
gpu
::
minMaxLoc
(
cv
::
gpu
::
GpuMat
(
src
),
&
minVal_
,
&
maxVal_
,
&
minLoc_
,
&
maxLoc_
);
cv
::
gpu
::
minMaxLoc
(
cv
::
gpu
::
GpuMat
(
src
),
&
minVal_
,
&
maxVal_
,
&
minLoc_
,
&
maxLoc_
,
valbuf
,
locbuf
);
CHECK
(
minVal
==
minVal_
,
CvTS
::
FAIL_INVALID_OUTPUT
);
CHECK
(
maxVal
==
maxVal_
,
CvTS
::
FAIL_INVALID_OUTPUT
);
...
...
tests/gpu/src/gputest_main.cpp
View file @
bdaad9e1
...
...
@@ -54,6 +54,7 @@ const char* blacklist[] =
};
int
main
(
int
argc
,
char
**
argv
)
{
return
test_system
.
run
(
argc
,
argv
,
blacklist
);
}
...
...
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