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opencv
Commit b2603828 authored by Alexey Spizhevoy's avatar Alexey Spizhevoy
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added masks support into gpu::minMaxLoc

parent 7c4cff99
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Showing with 101 additions and 23 deletions
modules/gpu/include/opencv2/gpu/gpu.hpp
View file @ b2603828
......@@ -431,11 +431,12 @@ namespace cv
CV_EXPORTS void minMax(const GpuMat& src, double* minVal, double* maxVal, const GpuMat& mask, GpuMat& buf);
//! 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);
CV_EXPORTS void minMaxLoc(const GpuMat& src, double* minVal, double* maxVal=0, Point* minLoc=0, Point* maxLoc=0,
const GpuMat& mask=GpuMat());
//! 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);
const GpuMat& mask, GpuMat& valbuf, GpuMat& locbuf);
//! counts non-zero array elements
CV_EXPORTS int countNonZero(const GpuMat& src);
......
modules/gpu/src/arithm.cpp
View file @ b2603828
This diff is collapsed.
modules/gpu/src/cuda/mathfunc.cu
View file @ b2603828
......@@ -248,10 +248,10 @@ namespace cv { namespace gpu { namespace mathfunc
struct Mask8U
{
explicit Mask8U(PtrStep mask): mask(mask) {}
__device__ bool operator()(int y, int x) { return mask.ptr(y)[x]; }
__device__ bool operator()(int y, int x) const { return mask.ptr(y)[x]; }
PtrStep mask;
};
struct MaskTrue { __device__ bool operator()(int y, int x) { return true; } };
struct MaskTrue { __device__ bool operator()(int y, int x) const { return true; } };
// Unary operations
......@@ -788,8 +788,8 @@ namespace cv { namespace gpu { namespace mathfunc
}
template <int nthreads, typename T>
__global__ void min_max_loc_kernel(const DevMem2D src, T* minval, T* maxval,
template <int nthreads, typename T, typename Mask>
__global__ void min_max_loc_kernel(const DevMem2D src, Mask mask, T* minval, T* maxval,
unsigned int* minloc, unsigned int* maxloc)
{
typedef typename MinMaxTypeTraits<T>::best_type best_type;
......@@ -814,16 +814,11 @@ namespace cv { namespace gpu { namespace mathfunc
const T* ptr = (const T*)src.ptr(y);
for (unsigned int x = x0; x < x_end; x += blockDim.x)
{
T val = ptr[x];
if (val <= mymin)
{
mymin = val;
myminloc = y * src.cols + x;
}
if (val >= mymax)
if (mask(y, x))
{
mymax = val;
mymaxloc = y * src.cols + x;
T val = ptr[x];
if (val <= mymin) { mymin = val; myminloc = y * src.cols + x; }
if (val >= mymax) { mymax = val; mymaxloc = y * src.cols + x; }
}
}
}
......@@ -886,6 +881,44 @@ namespace cv { namespace gpu { namespace mathfunc
}
template <typename T>
void min_max_loc_mask_caller(const DevMem2D src, const PtrStep mask, 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);
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);
min_max_loc_kernel<256, T, Mask8U><<<grid, threads>>>(src, Mask8U(mask), 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;
}
template void min_max_loc_mask_caller<unsigned char>(const DevMem2D, const PtrStep, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_mask_caller<char>(const DevMem2D, const PtrStep, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_mask_caller<unsigned short>(const DevMem2D, const PtrStep, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_mask_caller<short>(const DevMem2D, const PtrStep, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_mask_caller<int>(const DevMem2D, const PtrStep, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_mask_caller<float>(const DevMem2D, const PtrStep, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_mask_caller<double>(const DevMem2D, const PtrStep, double*, double*, int[2], int[2], PtrStep, PtrStep);
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)
......@@ -899,7 +932,7 @@ namespace cv { namespace gpu { namespace mathfunc
unsigned int* minloc_buf = (unsigned int*)locbuf.ptr(0);
unsigned int* maxloc_buf = (unsigned int*)locbuf.ptr(1);
min_max_loc_kernel<256, T><<<grid, threads>>>(src, minval_buf, maxval_buf, minloc_buf, maxloc_buf);
min_max_loc_kernel<256, T, MaskTrue><<<grid, threads>>>(src, MaskTrue(), minval_buf, maxval_buf, minloc_buf, maxloc_buf);
cudaSafeCall(cudaThreadSynchronize());
T minval_, maxval_;
......@@ -956,9 +989,47 @@ namespace cv { namespace gpu { namespace mathfunc
}
template <typename T>
void min_max_loc_mask_multipass_caller(const DevMem2D src, const PtrStep mask, 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);
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);
min_max_loc_kernel<256, T, Mask8U><<<grid, threads>>>(src, Mask8U(mask), minval_buf, maxval_buf, minloc_buf, maxloc_buf);
min_max_loc_pass2_kernel<256, T><<<1, 256>>>(minval_buf, maxval_buf, minloc_buf, maxloc_buf, grid.x * grid.y);
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;
}
template void min_max_loc_mask_multipass_caller<unsigned char>(const DevMem2D, const PtrStep, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_mask_multipass_caller<char>(const DevMem2D, const PtrStep, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_mask_multipass_caller<unsigned short>(const DevMem2D, const PtrStep, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_mask_multipass_caller<short>(const DevMem2D, const PtrStep, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_mask_multipass_caller<int>(const DevMem2D, const PtrStep, double*, double*, int[2], int[2], PtrStep, PtrStep);
template void min_max_loc_mask_multipass_caller<float>(const DevMem2D, const PtrStep, double*, double*, int[2], int[2], PtrStep, PtrStep);
template <typename T>
void min_max_loc_multipass_caller(const DevMem2D src, double* minval, double* maxval,
int minloc[2], int maxloc[2], PtrStep valbuf, PtrStep locbuf)
int minloc[2], int maxloc[2], PtrStep valbuf, PtrStep locbuf)
{
dim3 threads, grid;
estimate_thread_cfg(threads, grid);
......@@ -969,7 +1040,7 @@ namespace cv { namespace gpu { namespace mathfunc
unsigned int* minloc_buf = (unsigned int*)locbuf.ptr(0);
unsigned int* maxloc_buf = (unsigned int*)locbuf.ptr(1);
min_max_loc_kernel<256, T><<<grid, threads>>>(src, minval_buf, maxval_buf, minloc_buf, maxloc_buf);
min_max_loc_kernel<256, T, MaskTrue><<<grid, threads>>>(src, MaskTrue(), minval_buf, maxval_buf, minloc_buf, maxloc_buf);
min_max_loc_pass2_kernel<256, T><<<1, 256>>>(minval_buf, maxval_buf, minloc_buf, maxloc_buf, grid.x * grid.y);
cudaSafeCall(cudaThreadSynchronize());
......
tests/gpu/src/arithm.cpp
View file @ b2603828
......@@ -684,7 +684,7 @@ struct CV_GpuMinMaxTest: public CvTest
if (cv::gpu::hasNativeDoubleSupport(cv::gpu::getDevice())) depth_end = CV_64F; else depth_end = CV_32F;
for (int depth = CV_8U; depth <= depth_end; ++depth)
{
for (int i = 0; i < 1; ++i)
for (int i = 0; i < 3; ++i)
{
int rows = 1 + rand() % 1000;
int cols = 1 + rand() % 1000;
......@@ -829,11 +829,14 @@ struct CV_GpuMinMaxLocTest: public CvTest
rng.fill(row, RNG::UNIFORM, Scalar(0), Scalar(256));
}
cv::Mat mask(src.size(), CV_8U);
rng.fill(mask, RNG::UNIFORM, Scalar(0), Scalar(2));
double minVal, maxVal;
cv::Point minLoc, maxLoc;
if (depth != CV_8S)
cv::minMaxLoc(src, &minVal, &maxVal, &minLoc, &maxLoc);
cv::minMaxLoc(src, &minVal, &maxVal, &minLoc, &maxLoc, mask);
else
{
// OpenCV's minMaxLoc doesn't support CV_8S type
......@@ -843,14 +846,17 @@ struct CV_GpuMinMaxLocTest: public CvTest
for (int j = 0; j < src.cols; ++j)
{
char val = src.at<char>(i, j);
if (val < minVal) { minVal = val; minLoc = cv::Point(j, i); }
if (val > maxVal) { maxVal = val; maxLoc = cv::Point(j, i); }
if (mask.at<unsigned char>(i, j))
{
if (val < minVal) { minVal = val; minLoc = cv::Point(j, i); }
if (val > maxVal) { maxVal = val; maxLoc = cv::Point(j, i); }
}
}
}
double minVal_, maxVal_;
cv::Point minLoc_, maxLoc_;
cv::gpu::minMaxLoc(cv::gpu::GpuMat(src), &minVal_, &maxVal_, &minLoc_, &maxLoc_, valbuf, locbuf);
cv::gpu::minMaxLoc(cv::gpu::GpuMat(src), &minVal_, &maxVal_, &minLoc_, &maxLoc_, cv::gpu::GpuMat(mask), valbuf, locbuf);
CHECK(minVal == minVal_, CvTS::FAIL_INVALID_OUTPUT);
CHECK(maxVal == maxVal_, CvTS::FAIL_INVALID_OUTPUT);
......
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