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gpuarithm module for arithmetics operations on matrices

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This commit is contained in:
Vladislav Vinogradov 2013-04-17 17:39:17 +04:00
parent 1b00a3ed54
commit 31c8b527c6
64 changed files with 6425 additions and 4476 deletions
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125
modules/core/include/opencv2/core/cuda/emulation.hpp
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@ -43,6 +43,7 @@
#ifndef OPENCV_GPU_EMULATION_HPP_
#define OPENCV_GPU_EMULATION_HPP_
#include "common.hpp"
#include "warp_reduce.hpp"
namespace cv { namespace gpu { namespace cudev
@ -131,8 +132,130 @@ namespace cv { namespace gpu { namespace cudev
return ::atomicMin(address, val);
#endif
}
}; // struct cmem
struct glob
{
static __device__ __forceinline__ int atomicAdd(int* address, int val)
{
return ::atomicAdd(address, val);
}
static __device__ __forceinline__ unsigned int atomicAdd(unsigned int* address, unsigned int val)
{
return ::atomicAdd(address, val);
}
static __device__ __forceinline__ float atomicAdd(float* address, float val)
{
#if __CUDA_ARCH__ >= 200
return ::atomicAdd(address, val);
#else
int* address_as_i = (int*) address;
int old = *address_as_i, assumed;
do {
assumed = old;
old = ::atomicCAS(address_as_i, assumed,
__float_as_int(val + __int_as_float(assumed)));
} while (assumed != old);
return __int_as_float(old);
#endif
}
static __device__ __forceinline__ double atomicAdd(double* address, double val)
{
#if __CUDA_ARCH__ >= 130
unsigned long long int* address_as_ull = (unsigned long long int*) address;
unsigned long long int old = *address_as_ull, assumed;
do {
assumed = old;
old = ::atomicCAS(address_as_ull, assumed,
__double_as_longlong(val + __longlong_as_double(assumed)));
} while (assumed != old);
return __longlong_as_double(old);
#else
(void) address;
(void) val;
return 0.0;
#endif
}
static __device__ __forceinline__ int atomicMin(int* address, int val)
{
return ::atomicMin(address, val);
}
static __device__ __forceinline__ float atomicMin(float* address, float val)
{
#if __CUDA_ARCH__ >= 120
int* address_as_i = (int*) address;
int old = *address_as_i, assumed;
do {
assumed = old;
old = ::atomicCAS(address_as_i, assumed,
__float_as_int(::fminf(val, __int_as_float(assumed))));
} while (assumed != old);
return __int_as_float(old);
#else
(void) address;
(void) val;
return 0.0f;
#endif
}
static __device__ __forceinline__ double atomicMin(double* address, double val)
{
#if __CUDA_ARCH__ >= 130
unsigned long long int* address_as_ull = (unsigned long long int*) address;
unsigned long long int old = *address_as_ull, assumed;
do {
assumed = old;
old = ::atomicCAS(address_as_ull, assumed,
__double_as_longlong(::fmin(val, __longlong_as_double(assumed))));
} while (assumed != old);
return __longlong_as_double(old);
#else
(void) address;
(void) val;
return 0.0;
#endif
}
static __device__ __forceinline__ int atomicMax(int* address, int val)
{
return ::atomicMax(address, val);
}
static __device__ __forceinline__ float atomicMax(float* address, float val)
{
#if __CUDA_ARCH__ >= 120
int* address_as_i = (int*) address;
int old = *address_as_i, assumed;
do {
assumed = old;
old = ::atomicCAS(address_as_i, assumed,
__float_as_int(::fmaxf(val, __int_as_float(assumed))));
} while (assumed != old);
return __int_as_float(old);
#else
(void) address;
(void) val;
return 0.0f;
#endif
}
static __device__ __forceinline__ double atomicMax(double* address, double val)
{
#if __CUDA_ARCH__ >= 130
unsigned long long int* address_as_ull = (unsigned long long int*) address;
unsigned long long int old = *address_as_ull, assumed;
do {
assumed = old;
old = ::atomicCAS(address_as_ull, assumed,
__double_as_longlong(::fmax(val, __longlong_as_double(assumed))));
} while (assumed != old);
return __longlong_as_double(old);
#else
(void) address;
(void) val;
return 0.0;
#endif
}
};
};
}; //struct Emulation
}}} // namespace cv { namespace gpu { namespace cudev
#endif /* OPENCV_GPU_EMULATION_HPP_ */

6
modules/gpu/CMakeLists.txt
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@ -3,7 +3,7 @@ if(ANDROID OR IOS)
endif()
set(the_description "GPU-accelerated Computer Vision")
ocv_add_module(gpu opencv_imgproc opencv_calib3d opencv_objdetect opencv_video opencv_photo opencv_legacy)
ocv_add_module(gpu opencv_imgproc opencv_calib3d opencv_objdetect opencv_video opencv_photo opencv_legacy opencv_gpuarithm)
ocv_module_include_directories("${CMAKE_CURRENT_SOURCE_DIR}/src/cuda")
@ -58,10 +58,6 @@ if(HAVE_CUDA)
CUDA_ADD_CUFFT_TO_TARGET(${the_module})
endif()
if(HAVE_CUBLAS)
CUDA_ADD_CUBLAS_TO_TARGET(${the_module})
endif()
install(FILES src/nvidia/NPP_staging/NPP_staging.hpp src/nvidia/core/NCV.hpp
DESTINATION ${OPENCV_INCLUDE_INSTALL_PATH}/opencv2/${name}
COMPONENT main)

3
modules/gpu/doc/gpu.rst
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@ -8,10 +8,7 @@ gpu. GPU-accelerated Computer Vision
introduction
initalization_and_information
data_structures
operations_on_matrices
per_element_operations
image_processing
matrix_reductions
object_detection
feature_detection_and_description
image_filtering

22
modules/gpu/doc/image_processing.rst
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@ -414,28 +414,6 @@ The methods support arbitrary permutations of the original channels, including r
gpu::threshold
------------------
Applies a fixed-level threshold to each array element.
.. ocv:function:: double gpu::threshold(const GpuMat& src, GpuMat& dst, double thresh, double maxval, int type, Stream& stream = Stream::Null())
:param src: Source array (single-channel).
:param dst: Destination array with the same size and type as ``src`` .
:param thresh: Threshold value.
:param maxval: Maximum value to use with ``THRESH_BINARY`` and ``THRESH_BINARY_INV`` threshold types.
:param type: Threshold type. For details, see :ocv:func:`threshold` . The ``THRESH_OTSU`` threshold type is not supported.
:param stream: Stream for the asynchronous version.
.. seealso:: :ocv:func:`threshold`
gpu::resize
---------------
Resizes an image.

239
modules/gpu/include/opencv2/gpu.hpp
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@ -50,6 +50,7 @@
#endif
#include "opencv2/core/gpumat.hpp"
#include "opencv2/gpuarithm.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/objdetect.hpp"
#include "opencv2/features2d.hpp"
@ -269,182 +270,8 @@ CV_EXPORTS void GaussianBlur(const GpuMat& src, GpuMat& dst, Size ksize, GpuMat&
//! supports only ksize = 1 and ksize = 3
CV_EXPORTS void Laplacian(const GpuMat& src, GpuMat& dst, int ddepth, int ksize = 1, double scale = 1, int borderType = BORDER_DEFAULT, Stream& stream = Stream::Null());
////////////////////////////// Image processing //////////////////////////////
////////////////////////////// Arithmetics ///////////////////////////////////
//! implements generalized matrix product algorithm GEMM from BLAS
CV_EXPORTS void gemm(const GpuMat& src1, const GpuMat& src2, double alpha,
const GpuMat& src3, double beta, GpuMat& dst, int flags = 0, Stream& stream = Stream::Null());
//! transposes the matrix
//! supports matrix with element size = 1, 4 and 8 bytes (CV_8UC1, CV_8UC4, CV_16UC2, CV_32FC1, etc)
CV_EXPORTS void transpose(const GpuMat& src1, GpuMat& dst, Stream& stream = Stream::Null());
//! reverses the order of the rows, columns or both in a matrix
//! supports 1, 3 and 4 channels images with CV_8U, CV_16U, CV_32S or CV_32F depth
CV_EXPORTS void flip(const GpuMat& a, GpuMat& b, int flipCode, Stream& stream = Stream::Null());
//! 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
CV_EXPORTS void LUT(const GpuMat& src, const Mat& lut, GpuMat& dst, Stream& stream = Stream::Null());
//! makes multi-channel array out of several single-channel arrays
CV_EXPORTS void merge(const GpuMat* src, size_t n, GpuMat& dst, Stream& stream = Stream::Null());
//! makes multi-channel array out of several single-channel arrays
CV_EXPORTS void merge(const std::vector<GpuMat>& src, GpuMat& dst, Stream& stream = Stream::Null());
//! copies each plane of a multi-channel array to a dedicated array
CV_EXPORTS void split(const GpuMat& src, GpuMat* dst, Stream& stream = Stream::Null());
//! copies each plane of a multi-channel array to a dedicated array
CV_EXPORTS void split(const GpuMat& src, std::vector<GpuMat>& dst, Stream& stream = Stream::Null());
//! computes magnitude of complex (x(i).re, x(i).im) vector
//! supports only CV_32FC2 type
CV_EXPORTS void magnitude(const GpuMat& xy, GpuMat& magnitude, Stream& stream = Stream::Null());
//! computes squared magnitude of complex (x(i).re, x(i).im) vector
//! supports only CV_32FC2 type
CV_EXPORTS void magnitudeSqr(const GpuMat& xy, GpuMat& magnitude, Stream& stream = Stream::Null());
//! computes magnitude of each (x(i), y(i)) vector
//! supports only floating-point source
CV_EXPORTS void magnitude(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, Stream& stream = Stream::Null());
//! computes squared magnitude of each (x(i), y(i)) vector
//! supports only floating-point source
CV_EXPORTS void magnitudeSqr(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, Stream& stream = Stream::Null());
//! computes angle (angle(i)) of each (x(i), y(i)) vector
//! supports only floating-point source
CV_EXPORTS void phase(const GpuMat& x, const GpuMat& y, GpuMat& angle, bool angleInDegrees = false, Stream& stream = Stream::Null());
//! converts Cartesian coordinates to polar
//! supports only floating-point source
CV_EXPORTS void cartToPolar(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, GpuMat& angle, bool angleInDegrees = false, Stream& stream = Stream::Null());
//! converts polar coordinates to Cartesian
//! supports only floating-point source
CV_EXPORTS void polarToCart(const GpuMat& magnitude, const GpuMat& angle, GpuMat& x, GpuMat& y, bool angleInDegrees = false, Stream& stream = Stream::Null());
//! scales and shifts array elements so that either the specified norm (alpha) or the minimum (alpha) and maximum (beta) array values get the specified values
CV_EXPORTS void normalize(const GpuMat& src, GpuMat& dst, double alpha = 1, double beta = 0,
int norm_type = NORM_L2, int dtype = -1, const GpuMat& mask = GpuMat());
CV_EXPORTS void normalize(const GpuMat& src, GpuMat& dst, double a, double b,
int norm_type, int dtype, const GpuMat& mask, GpuMat& norm_buf, GpuMat& cvt_buf);
//////////////////////////// Per-element operations ////////////////////////////////////
//! adds one matrix to another (c = a + b)
CV_EXPORTS void add(const GpuMat& a, const GpuMat& b, GpuMat& c, const GpuMat& mask = GpuMat(), int dtype = -1, Stream& stream = Stream::Null());
//! adds scalar to a matrix (c = a + s)
CV_EXPORTS void add(const GpuMat& a, const Scalar& sc, GpuMat& c, const GpuMat& mask = GpuMat(), int dtype = -1, Stream& stream = Stream::Null());
//! subtracts one matrix from another (c = a - b)
CV_EXPORTS void subtract(const GpuMat& a, const GpuMat& b, GpuMat& c, const GpuMat& mask = GpuMat(), int dtype = -1, Stream& stream = Stream::Null());
//! subtracts scalar from a matrix (c = a - s)
CV_EXPORTS void subtract(const GpuMat& a, const Scalar& sc, GpuMat& c, const GpuMat& mask = GpuMat(), int dtype = -1, Stream& stream = Stream::Null());
//! computes element-wise weighted product of the two arrays (c = scale * a * b)
CV_EXPORTS void multiply(const GpuMat& a, const GpuMat& b, GpuMat& c, double scale = 1, int dtype = -1, Stream& stream = Stream::Null());
//! weighted multiplies matrix to a scalar (c = scale * a * s)
CV_EXPORTS void multiply(const GpuMat& a, const Scalar& sc, GpuMat& c, double scale = 1, int dtype = -1, Stream& stream = Stream::Null());
//! computes element-wise weighted quotient of the two arrays (c = a / b)
CV_EXPORTS void divide(const GpuMat& a, const GpuMat& b, GpuMat& c, double scale = 1, int dtype = -1, Stream& stream = Stream::Null());
//! computes element-wise weighted quotient of matrix and scalar (c = a / s)
CV_EXPORTS void divide(const GpuMat& a, const Scalar& sc, GpuMat& c, double scale = 1, int dtype = -1, Stream& stream = Stream::Null());
//! computes element-wise weighted reciprocal of an array (dst = scale/src2)
CV_EXPORTS void divide(double scale, const GpuMat& b, GpuMat& c, int dtype = -1, Stream& stream = Stream::Null());
//! computes the weighted sum of two arrays (dst = alpha*src1 + beta*src2 + gamma)
CV_EXPORTS void addWeighted(const GpuMat& src1, double alpha, const GpuMat& src2, double beta, double gamma, GpuMat& dst,
int dtype = -1, Stream& stream = Stream::Null());
//! adds scaled array to another one (dst = alpha*src1 + src2)
static inline void scaleAdd(const GpuMat& src1, double alpha, const GpuMat& src2, GpuMat& dst, Stream& stream = Stream::Null())
{
addWeighted(src1, alpha, src2, 1.0, 0.0, dst, -1, stream);
}
//! computes element-wise absolute difference of two arrays (c = abs(a - b))
CV_EXPORTS void absdiff(const GpuMat& a, const GpuMat& b, GpuMat& c, Stream& stream = Stream::Null());
//! computes element-wise absolute difference of array and scalar (c = abs(a - s))
CV_EXPORTS void absdiff(const GpuMat& a, const Scalar& s, GpuMat& c, Stream& stream = Stream::Null());
//! computes absolute value of each matrix element
//! supports CV_16S and CV_32F depth
CV_EXPORTS void abs(const GpuMat& src, GpuMat& dst, Stream& stream = Stream::Null());
//! computes square of each pixel in an image
//! supports CV_8U, CV_16U, CV_16S and CV_32F depth
CV_EXPORTS void sqr(const GpuMat& src, GpuMat& dst, Stream& stream = Stream::Null());
//! computes square root of each pixel in an image
//! supports CV_8U, CV_16U, CV_16S and CV_32F depth
CV_EXPORTS void sqrt(const GpuMat& src, GpuMat& dst, Stream& stream = Stream::Null());
//! computes exponent of each matrix element (b = e**a)
//! supports CV_8U, CV_16U, CV_16S and CV_32F depth
CV_EXPORTS void exp(const GpuMat& a, GpuMat& b, Stream& stream = Stream::Null());
//! computes natural logarithm of absolute value of each matrix element: b = log(abs(a))
//! supports CV_8U, CV_16U, CV_16S and CV_32F depth
CV_EXPORTS void log(const GpuMat& a, GpuMat& b, Stream& stream = Stream::Null());
//! computes power of each matrix element:
// (dst(i,j) = pow( src(i,j) , power), if src.type() is integer
// (dst(i,j) = pow(fabs(src(i,j)), power), otherwise
//! supports all, except depth == CV_64F
CV_EXPORTS void pow(const GpuMat& src, double power, GpuMat& dst, Stream& stream = Stream::Null());
//! compares elements of two arrays (c = a <cmpop> b)
CV_EXPORTS void compare(const GpuMat& a, const GpuMat& b, GpuMat& c, int cmpop, Stream& stream = Stream::Null());
CV_EXPORTS void compare(const GpuMat& a, Scalar sc, GpuMat& c, int cmpop, Stream& stream = Stream::Null());
//! performs per-elements bit-wise inversion
CV_EXPORTS void bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask=GpuMat(), Stream& stream = Stream::Null());
//! calculates per-element bit-wise disjunction of two arrays
CV_EXPORTS void bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask=GpuMat(), Stream& stream = Stream::Null());
//! calculates per-element bit-wise disjunction of array and scalar
//! supports 1, 3 and 4 channels images with CV_8U, CV_16U or CV_32S depth
CV_EXPORTS void bitwise_or(const GpuMat& src1, const Scalar& sc, GpuMat& dst, Stream& stream = Stream::Null());
//! calculates per-element bit-wise conjunction of two arrays
CV_EXPORTS void bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask=GpuMat(), Stream& stream = Stream::Null());
//! calculates per-element bit-wise conjunction of array and scalar
//! supports 1, 3 and 4 channels images with CV_8U, CV_16U or CV_32S depth
CV_EXPORTS void bitwise_and(const GpuMat& src1, const Scalar& sc, GpuMat& dst, Stream& stream = Stream::Null());
//! calculates per-element bit-wise "exclusive or" operation
CV_EXPORTS void bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask=GpuMat(), Stream& stream = Stream::Null());
//! calculates per-element bit-wise "exclusive or" of array and scalar
//! supports 1, 3 and 4 channels images with CV_8U, CV_16U or CV_32S depth
CV_EXPORTS void bitwise_xor(const GpuMat& src1, const Scalar& sc, GpuMat& dst, Stream& stream = Stream::Null());
//! pixel by pixel right shift of an image by a constant value
//! supports 1, 3 and 4 channels images with integers elements
CV_EXPORTS void rshift(const GpuMat& src, Scalar_<int> sc, GpuMat& dst, Stream& stream = Stream::Null());
//! pixel by pixel left shift of an image by a constant value
//! supports 1, 3 and 4 channels images with CV_8U, CV_16U or CV_32S depth
CV_EXPORTS void lshift(const GpuMat& src, Scalar_<int> sc, GpuMat& dst, Stream& stream = Stream::Null());
//! computes per-element minimum of two arrays (dst = min(src1, src2))
CV_EXPORTS void min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream = Stream::Null());
//! computes per-element minimum of array and scalar (dst = min(src1, src2))
CV_EXPORTS void min(const GpuMat& src1, double src2, GpuMat& dst, Stream& stream = Stream::Null());
//! computes per-element maximum of two arrays (dst = max(src1, src2))
CV_EXPORTS void max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream = Stream::Null());
//! computes per-element maximum of array and scalar (dst = max(src1, src2))
CV_EXPORTS void max(const GpuMat& src1, double src2, GpuMat& dst, Stream& stream = Stream::Null());
enum { ALPHA_OVER, ALPHA_IN, ALPHA_OUT, ALPHA_ATOP, ALPHA_XOR, ALPHA_PLUS, ALPHA_OVER_PREMUL, ALPHA_IN_PREMUL, ALPHA_OUT_PREMUL,
ALPHA_ATOP_PREMUL, ALPHA_XOR_PREMUL, ALPHA_PLUS_PREMUL, ALPHA_PREMUL};
@ -453,9 +280,6 @@ enum { ALPHA_OVER, ALPHA_IN, ALPHA_OUT, ALPHA_ATOP, ALPHA_XOR, ALPHA_PLUS, ALPHA
//! Supports CV_8UC4, CV_16UC4, CV_32SC4 and CV_32FC4 types
CV_EXPORTS void alphaComp(const GpuMat& img1, const GpuMat& img2, GpuMat& dst, int alpha_op, Stream& stream = Stream::Null());
////////////////////////////// Image processing //////////////////////////////
//! DST[x,y] = SRC[xmap[x,y],ymap[x,y]]
//! supports only CV_32FC1 map type
CV_EXPORTS void remap(const GpuMat& src, GpuMat& dst, const GpuMat& xmap, const GpuMat& ymap,
@ -521,9 +345,6 @@ CV_EXPORTS void swapChannels(GpuMat& image, const int dstOrder[4], Stream& strea
//! Routines for correcting image color gamma
CV_EXPORTS void gammaCorrection(const GpuMat& src, GpuMat& dst, bool forward = true, Stream& stream = Stream::Null());
//! applies fixed threshold to the image
CV_EXPORTS double threshold(const GpuMat& src, GpuMat& dst, double thresh, double maxval, int type, Stream& stream = Stream::Null());
//! resizes the image
//! Supports INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, INTER_AREA
CV_EXPORTS void resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx=0, double fy=0, int interpolation = INTER_LINEAR, Stream& stream = Stream::Null());
@ -794,62 +615,6 @@ private:
CannyBuf cannyBuf_;
};
////////////////////////////// Matrix reductions //////////////////////////////
//! computes mean value and standard deviation of all or selected array elements
//! supports only CV_8UC1 type
CV_EXPORTS void meanStdDev(const GpuMat& mtx, Scalar& mean, Scalar& stddev);
//! buffered version
CV_EXPORTS void meanStdDev(const GpuMat& mtx, Scalar& mean, Scalar& stddev, GpuMat& buf);
//! computes norm of array
//! supports NORM_INF, NORM_L1, NORM_L2
//! supports all matrices except 64F
CV_EXPORTS double norm(const GpuMat& src1, int normType=NORM_L2);
CV_EXPORTS double norm(const GpuMat& src1, int normType, GpuMat& buf);
CV_EXPORTS double norm(const GpuMat& src1, int normType, const GpuMat& mask, GpuMat& buf);
//! computes norm of the difference between two arrays
//! supports NORM_INF, NORM_L1, NORM_L2
//! supports only CV_8UC1 type
CV_EXPORTS double norm(const GpuMat& src1, const GpuMat& src2, int normType=NORM_L2);
//! computes sum of array elements
//! supports only single channel images
CV_EXPORTS Scalar sum(const GpuMat& src);
CV_EXPORTS Scalar sum(const GpuMat& src, GpuMat& buf);
CV_EXPORTS Scalar sum(const GpuMat& src, const GpuMat& mask, GpuMat& buf);
//! computes sum of array elements absolute values
//! supports only single channel images
CV_EXPORTS Scalar absSum(const GpuMat& src);
CV_EXPORTS Scalar absSum(const GpuMat& src, GpuMat& buf);
CV_EXPORTS Scalar absSum(const GpuMat& src, const GpuMat& mask, GpuMat& buf);
//! computes squared sum of array elements
//! supports only single channel images
CV_EXPORTS Scalar sqrSum(const GpuMat& src);
CV_EXPORTS Scalar sqrSum(const GpuMat& src, GpuMat& buf);
CV_EXPORTS Scalar sqrSum(const GpuMat& src, const GpuMat& mask, GpuMat& buf);
//! finds global minimum and maximum array elements and returns their values
CV_EXPORTS void minMax(const GpuMat& src, double* minVal, double* maxVal=0, const GpuMat& mask=GpuMat());
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,
const GpuMat& mask=GpuMat());
CV_EXPORTS void minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc,
const GpuMat& mask, GpuMat& valbuf, GpuMat& locbuf);
//! counts non-zero array elements
CV_EXPORTS int countNonZero(const GpuMat& src);
CV_EXPORTS int countNonZero(const GpuMat& src, GpuMat& buf);
//! reduces a matrix to a vector
CV_EXPORTS void reduce(const GpuMat& mtx, GpuMat& vec, int dim, int reduceOp, int dtype = -1, Stream& stream = Stream::Null());
///////////////////////////// Calibration 3D //////////////////////////////////
CV_EXPORTS void transformPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec,

2636
modules/gpu/src/cuda/element_operations.cu
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1366
modules/gpu/src/cuda/matrix_reductions.cu
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10
modules/gpu/src/cuda/safe_call.hpp
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@ -45,24 +45,20 @@
#include <cuda_runtime_api.h>
#include <cufft.h>
#include <cublas.h>
#include "NCV.hpp"
#if defined(__GNUC__)
#define ncvSafeCall(expr) ___ncvSafeCall(expr, __FILE__, __LINE__, __func__)
#define cufftSafeCall(expr) ___cufftSafeCall(expr, __FILE__, __LINE__, __func__)
#define cublasSafeCall(expr) ___cublasSafeCall(expr, __FILE__, __LINE__, __func__)
#else /* defined(__CUDACC__) || defined(__MSVC__) */
#define ncvSafeCall(expr) ___ncvSafeCall(expr, __FILE__, __LINE__)
#define cufftSafeCall(expr) ___cufftSafeCall(expr, __FILE__, __LINE__)
#define cublasSafeCall(expr) ___cublasSafeCall(expr, __FILE__, __LINE__)
#endif
namespace cv { namespace gpu
{
void ncvError(int err, const char *file, const int line, const char *func = "");
void cufftError(int err, const char *file, const int line, const char *func = "");
void cublasError(int err, const char *file, const int line, const char *func = "");
}}
static inline void ___ncvSafeCall(int err, const char *file, const int line, const char *func = "")
@ -77,10 +73,4 @@ static inline void ___cufftSafeCall(cufftResult_t err, const char *file, const i
cv::gpu::cufftError(err, file, line, func);
}
static inline void ___cublasSafeCall(cublasStatus_t err, const char *file, const int line, const char *func = "")
{
if (CUBLAS_STATUS_SUCCESS != err)
cv::gpu::cublasError(err, file, line, func);
}
#endif /* __OPENCV_CUDA_SAFE_CALL_HPP__ */

23
modules/gpu/src/error.cpp
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@ -142,23 +142,6 @@ namespace
};
const int cufft_error_num = sizeof(cufft_errors) / sizeof(cufft_errors[0]);
//////////////////////////////////////////////////////////////////////////
// CUBLAS errors
const ErrorEntry cublas_errors[] =
{
error_entry( CUBLAS_STATUS_SUCCESS ),
error_entry( CUBLAS_STATUS_NOT_INITIALIZED ),
error_entry( CUBLAS_STATUS_ALLOC_FAILED ),
error_entry( CUBLAS_STATUS_INVALID_VALUE ),
error_entry( CUBLAS_STATUS_ARCH_MISMATCH ),
error_entry( CUBLAS_STATUS_MAPPING_ERROR ),
error_entry( CUBLAS_STATUS_EXECUTION_FAILED ),
error_entry( CUBLAS_STATUS_INTERNAL_ERROR )
};
const int cublas_error_num = sizeof(cublas_errors) / sizeof(cublas_errors[0]);
}
namespace cv
@ -176,12 +159,6 @@ namespace cv
String msg = getErrorString(code, cufft_errors, cufft_error_num);
cv::error(cv::Error::GpuApiCallError, msg, func, file, line);
}
void cublasError(int code, const char* file, const int line, const char* func)
{
String msg = getErrorString(code, cublas_errors, cublas_error_num);
cv::error(cv::Error::GpuApiCallError, msg, func, file, line);
}
}
}

74
modules/gpu/src/imgproc.cpp
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@ -92,6 +92,7 @@ void cv::gpu::Canny(const GpuMat&, const GpuMat&, CannyBuf&, GpuMat&, double, do
void cv::gpu::CannyBuf::create(const Size&, int) { throw_no_cuda(); }
void cv::gpu::CannyBuf::release() { throw_no_cuda(); }
cv::Ptr<cv::gpu::CLAHE> cv::gpu::createCLAHE(double, cv::Size) { throw_no_cuda(); return cv::Ptr<cv::gpu::CLAHE>(); }
void cv::gpu::alphaComp(const GpuMat&, const GpuMat&, GpuMat&, int, Stream&) { throw_no_cuda(); }
#else /* !defined (HAVE_CUDA) */
@ -1672,4 +1673,77 @@ cv::Ptr<cv::gpu::CLAHE> cv::gpu::createCLAHE(double clipLimit, cv::Size tileGrid
return new CLAHE_Impl(clipLimit, tileGridSize.width, tileGridSize.height);
}
////////////////////////////////////////////////////////////////////////
// alphaComp
namespace
{
template <int DEPTH> struct NppAlphaCompFunc
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
typedef NppStatus (*func_t)(const npp_t* pSrc1, int nSrc1Step, const npp_t* pSrc2, int nSrc2Step, npp_t* pDst, int nDstStep, NppiSize oSizeROI, NppiAlphaOp eAlphaOp);
};
template <int DEPTH, typename NppAlphaCompFunc<DEPTH>::func_t func> struct NppAlphaComp
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
static void call(const GpuMat& img1, const GpuMat& img2, GpuMat& dst, NppiAlphaOp eAlphaOp, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize oSizeROI;
oSizeROI.width = img1.cols;
oSizeROI.height = img2.rows;
nppSafeCall( func(img1.ptr<npp_t>(), static_cast<int>(img1.step), img2.ptr<npp_t>(), static_cast<int>(img2.step),
dst.ptr<npp_t>(), static_cast<int>(dst.step), oSizeROI, eAlphaOp) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
}
void cv::gpu::alphaComp(const GpuMat& img1, const GpuMat& img2, GpuMat& dst, int alpha_op, Stream& stream)
{
static const NppiAlphaOp npp_alpha_ops[] = {
NPPI_OP_ALPHA_OVER,
NPPI_OP_ALPHA_IN,
NPPI_OP_ALPHA_OUT,
NPPI_OP_ALPHA_ATOP,
NPPI_OP_ALPHA_XOR,
NPPI_OP_ALPHA_PLUS,
NPPI_OP_ALPHA_OVER_PREMUL,
NPPI_OP_ALPHA_IN_PREMUL,
NPPI_OP_ALPHA_OUT_PREMUL,
NPPI_OP_ALPHA_ATOP_PREMUL,
NPPI_OP_ALPHA_XOR_PREMUL,
NPPI_OP_ALPHA_PLUS_PREMUL,
NPPI_OP_ALPHA_PREMUL
};
typedef void (*func_t)(const GpuMat& img1, const GpuMat& img2, GpuMat& dst, NppiAlphaOp eAlphaOp, cudaStream_t stream);
static const func_t funcs[] =
{
NppAlphaComp<CV_8U, nppiAlphaComp_8u_AC4R>::call,
0,
NppAlphaComp<CV_16U, nppiAlphaComp_16u_AC4R>::call,
0,
NppAlphaComp<CV_32S, nppiAlphaComp_32s_AC4R>::call,
NppAlphaComp<CV_32F, nppiAlphaComp_32f_AC4R>::call
};
CV_Assert( img1.type() == CV_8UC4 || img1.type() == CV_16UC4 || img1.type() == CV_32SC4 || img1.type() == CV_32FC4 );
CV_Assert( img1.size() == img2.size() && img1.type() == img2.type() );
dst.create(img1.size(), img1.type());
const func_t func = funcs[img1.depth()];
func(img1, img2, dst, npp_alpha_ops[alpha_op], StreamAccessor::getStream(stream));
}
#endif /* !defined (HAVE_CUDA) */

4
modules/gpu/src/precomp.hpp
View File

@ -76,10 +76,6 @@
#include <cufft.h>
#endif
#ifdef HAVE_CUBLAS
#include <cublas.h>
#endif
#include "internal_shared.hpp"
#include "opencv2/core/stream_accessor.hpp"

13
modules/gpuarithm/CMakeLists.txt Normal file
View File

@ -0,0 +1,13 @@
if(ANDROID OR IOS)
ocv_module_disable(gpuarithm)
endif()
set(the_description "GPU-accelerated Operations on Matrices")
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wundef -Wmissing-declarations)
ocv_define_module(gpuarithm opencv_core)
if(HAVE_CUBLAS)
CUDA_ADD_CUBLAS_TO_TARGET(${the_module})
endif()

10
modules/gpuarithm/doc/gpuarithm.rst Normal file
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@ -0,0 +1,10 @@
*******************************************
gpu. GPU-accelerated Operations on Matrices
*******************************************
.. toctree::
:maxdepth: 1
operations_on_matrices
per_element_operations
matrix_reductions

0
modules/gpu/doc/matrix_reductions.rst → modules/gpuarithm/doc/matrix_reductions.rst
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0
modules/gpu/doc/operations_on_matrices.rst → modules/gpuarithm/doc/operations_on_matrices.rst
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22
modules/gpu/doc/per_element_operations.rst → modules/gpuarithm/doc/per_element_operations.rst
View File

@ -443,3 +443,25 @@ Computes the per-element maximum of two matrices (or a matrix and a scalar).
:param stream: Stream for the asynchronous version.
.. seealso:: :ocv:func:`max`
gpu::threshold
------------------
Applies a fixed-level threshold to each array element.
.. ocv:function:: double gpu::threshold(const GpuMat& src, GpuMat& dst, double thresh, double maxval, int type, Stream& stream = Stream::Null())
:param src: Source array (single-channel).
:param dst: Destination array with the same size and type as ``src`` .
:param thresh: Threshold value.
:param maxval: Maximum value to use with ``THRESH_BINARY`` and ``THRESH_BINARY_INV`` threshold types.
:param type: Threshold type. For details, see :ocv:func:`threshold` . The ``THRESH_OTSU`` threshold type is not supported.
:param stream: Stream for the asynchronous version.
.. seealso:: :ocv:func:`threshold`

279
modules/gpuarithm/include/opencv2/gpuarithm.hpp Normal file
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@ -0,0 +1,279 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_GPUARITHM_HPP__
#define __OPENCV_GPUARITHM_HPP__
#include "opencv2/core/gpumat.hpp"
namespace cv { namespace gpu {
//! adds one matrix to another (c = a + b)
CV_EXPORTS void add(const GpuMat& a, const GpuMat& b, GpuMat& c, const GpuMat& mask = GpuMat(), int dtype = -1, Stream& stream = Stream::Null());
//! adds scalar to a matrix (c = a + s)
CV_EXPORTS void add(const GpuMat& a, const Scalar& sc, GpuMat& c, const GpuMat& mask = GpuMat(), int dtype = -1, Stream& stream = Stream::Null());
//! subtracts one matrix from another (c = a - b)
CV_EXPORTS void subtract(const GpuMat& a, const GpuMat& b, GpuMat& c, const GpuMat& mask = GpuMat(), int dtype = -1, Stream& stream = Stream::Null());
//! subtracts scalar from a matrix (c = a - s)
CV_EXPORTS void subtract(const GpuMat& a, const Scalar& sc, GpuMat& c, const GpuMat& mask = GpuMat(), int dtype = -1, Stream& stream = Stream::Null());
//! computes element-wise weighted product of the two arrays (c = scale * a * b)
CV_EXPORTS void multiply(const GpuMat& a, const GpuMat& b, GpuMat& c, double scale = 1, int dtype = -1, Stream& stream = Stream::Null());
//! weighted multiplies matrix to a scalar (c = scale * a * s)
CV_EXPORTS void multiply(const GpuMat& a, const Scalar& sc, GpuMat& c, double scale = 1, int dtype = -1, Stream& stream = Stream::Null());
//! computes element-wise weighted quotient of the two arrays (c = a / b)
CV_EXPORTS void divide(const GpuMat& a, const GpuMat& b, GpuMat& c, double scale = 1, int dtype = -1, Stream& stream = Stream::Null());
//! computes element-wise weighted quotient of matrix and scalar (c = a / s)
CV_EXPORTS void divide(const GpuMat& a, const Scalar& sc, GpuMat& c, double scale = 1, int dtype = -1, Stream& stream = Stream::Null());
//! computes element-wise weighted reciprocal of an array (dst = scale/src2)
CV_EXPORTS void divide(double scale, const GpuMat& b, GpuMat& c, int dtype = -1, Stream& stream = Stream::Null());
//! computes the weighted sum of two arrays (dst = alpha*src1 + beta*src2 + gamma)
CV_EXPORTS void addWeighted(const GpuMat& src1, double alpha, const GpuMat& src2, double beta, double gamma, GpuMat& dst,
int dtype = -1, Stream& stream = Stream::Null());
//! adds scaled array to another one (dst = alpha*src1 + src2)
static inline void scaleAdd(const GpuMat& src1, double alpha, const GpuMat& src2, GpuMat& dst, Stream& stream = Stream::Null())
{
addWeighted(src1, alpha, src2, 1.0, 0.0, dst, -1, stream);
}
//! computes element-wise absolute difference of two arrays (c = abs(a - b))
CV_EXPORTS void absdiff(const GpuMat& a, const GpuMat& b, GpuMat& c, Stream& stream = Stream::Null());
//! computes element-wise absolute difference of array and scalar (c = abs(a - s))
CV_EXPORTS void absdiff(const GpuMat& a, const Scalar& s, GpuMat& c, Stream& stream = Stream::Null());
//! computes absolute value of each matrix element
//! supports CV_16S and CV_32F depth
CV_EXPORTS void abs(const GpuMat& src, GpuMat& dst, Stream& stream = Stream::Null());
//! computes square of each pixel in an image
//! supports CV_8U, CV_16U, CV_16S and CV_32F depth
CV_EXPORTS void sqr(const GpuMat& src, GpuMat& dst, Stream& stream = Stream::Null());
//! computes square root of each pixel in an image
//! supports CV_8U, CV_16U, CV_16S and CV_32F depth
CV_EXPORTS void sqrt(const GpuMat& src, GpuMat& dst, Stream& stream = Stream::Null());
//! computes exponent of each matrix element (b = e**a)
//! supports CV_8U, CV_16U, CV_16S and CV_32F depth
CV_EXPORTS void exp(const GpuMat& a, GpuMat& b, Stream& stream = Stream::Null());
//! computes natural logarithm of absolute value of each matrix element: b = log(abs(a))
//! supports CV_8U, CV_16U, CV_16S and CV_32F depth
CV_EXPORTS void log(const GpuMat& a, GpuMat& b, Stream& stream = Stream::Null());
//! computes power of each matrix element:
// (dst(i,j) = pow( src(i,j) , power), if src.type() is integer
// (dst(i,j) = pow(fabs(src(i,j)), power), otherwise
//! supports all, except depth == CV_64F
CV_EXPORTS void pow(const GpuMat& src, double power, GpuMat& dst, Stream& stream = Stream::Null());
//! compares elements of two arrays (c = a <cmpop> b)
CV_EXPORTS void compare(const GpuMat& a, const GpuMat& b, GpuMat& c, int cmpop, Stream& stream = Stream::Null());
CV_EXPORTS void compare(const GpuMat& a, Scalar sc, GpuMat& c, int cmpop, Stream& stream = Stream::Null());
//! performs per-elements bit-wise inversion
CV_EXPORTS void bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask=GpuMat(), Stream& stream = Stream::Null());
//! calculates per-element bit-wise disjunction of two arrays
CV_EXPORTS void bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask=GpuMat(), Stream& stream = Stream::Null());
//! calculates per-element bit-wise disjunction of array and scalar
//! supports 1, 3 and 4 channels images with CV_8U, CV_16U or CV_32S depth
CV_EXPORTS void bitwise_or(const GpuMat& src1, const Scalar& sc, GpuMat& dst, Stream& stream = Stream::Null());
//! calculates per-element bit-wise conjunction of two arrays
CV_EXPORTS void bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask=GpuMat(), Stream& stream = Stream::Null());
//! calculates per-element bit-wise conjunction of array and scalar
//! supports 1, 3 and 4 channels images with CV_8U, CV_16U or CV_32S depth
CV_EXPORTS void bitwise_and(const GpuMat& src1, const Scalar& sc, GpuMat& dst, Stream& stream = Stream::Null());
//! calculates per-element bit-wise "exclusive or" operation
CV_EXPORTS void bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask=GpuMat(), Stream& stream = Stream::Null());
//! calculates per-element bit-wise "exclusive or" of array and scalar
//! supports 1, 3 and 4 channels images with CV_8U, CV_16U or CV_32S depth
CV_EXPORTS void bitwise_xor(const GpuMat& src1, const Scalar& sc, GpuMat& dst, Stream& stream = Stream::Null());
//! pixel by pixel right shift of an image by a constant value
//! supports 1, 3 and 4 channels images with integers elements
CV_EXPORTS void rshift(const GpuMat& src, Scalar_<int> sc, GpuMat& dst, Stream& stream = Stream::Null());
//! pixel by pixel left shift of an image by a constant value
//! supports 1, 3 and 4 channels images with CV_8U, CV_16U or CV_32S depth
CV_EXPORTS void lshift(const GpuMat& src, Scalar_<int> sc, GpuMat& dst, Stream& stream = Stream::Null());
//! computes per-element minimum of two arrays (dst = min(src1, src2))
CV_EXPORTS void min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream = Stream::Null());
//! computes per-element minimum of array and scalar (dst = min(src1, src2))
CV_EXPORTS void min(const GpuMat& src1, double src2, GpuMat& dst, Stream& stream = Stream::Null());
//! computes per-element maximum of two arrays (dst = max(src1, src2))
CV_EXPORTS void max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, Stream& stream = Stream::Null());
//! computes per-element maximum of array and scalar (dst = max(src1, src2))
CV_EXPORTS void max(const GpuMat& src1, double src2, GpuMat& dst, Stream& stream = Stream::Null());
//! implements generalized matrix product algorithm GEMM from BLAS
CV_EXPORTS void gemm(const GpuMat& src1, const GpuMat& src2, double alpha,
const GpuMat& src3, double beta, GpuMat& dst, int flags = 0, Stream& stream = Stream::Null());
//! transposes the matrix
//! supports matrix with element size = 1, 4 and 8 bytes (CV_8UC1, CV_8UC4, CV_16UC2, CV_32FC1, etc)
CV_EXPORTS void transpose(const GpuMat& src1, GpuMat& dst, Stream& stream = Stream::Null());
//! reverses the order of the rows, columns or both in a matrix
//! supports 1, 3 and 4 channels images with CV_8U, CV_16U, CV_32S or CV_32F depth
CV_EXPORTS void flip(const GpuMat& a, GpuMat& b, int flipCode, Stream& stream = Stream::Null());
//! 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
CV_EXPORTS void LUT(const GpuMat& src, const Mat& lut, GpuMat& dst, Stream& stream = Stream::Null());
//! makes multi-channel array out of several single-channel arrays
CV_EXPORTS void merge(const GpuMat* src, size_t n, GpuMat& dst, Stream& stream = Stream::Null());
//! makes multi-channel array out of several single-channel arrays
CV_EXPORTS void merge(const std::vector<GpuMat>& src, GpuMat& dst, Stream& stream = Stream::Null());
//! copies each plane of a multi-channel array to a dedicated array
CV_EXPORTS void split(const GpuMat& src, GpuMat* dst, Stream& stream = Stream::Null());
//! copies each plane of a multi-channel array to a dedicated array
CV_EXPORTS void split(const GpuMat& src, std::vector<GpuMat>& dst, Stream& stream = Stream::Null());
//! computes magnitude of complex (x(i).re, x(i).im) vector
//! supports only CV_32FC2 type
CV_EXPORTS void magnitude(const GpuMat& xy, GpuMat& magnitude, Stream& stream = Stream::Null());
//! computes squared magnitude of complex (x(i).re, x(i).im) vector
//! supports only CV_32FC2 type
CV_EXPORTS void magnitudeSqr(const GpuMat& xy, GpuMat& magnitude, Stream& stream = Stream::Null());
//! computes magnitude of each (x(i), y(i)) vector
//! supports only floating-point source
CV_EXPORTS void magnitude(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, Stream& stream = Stream::Null());
//! computes squared magnitude of each (x(i), y(i)) vector
//! supports only floating-point source
CV_EXPORTS void magnitudeSqr(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, Stream& stream = Stream::Null());
//! computes angle (angle(i)) of each (x(i), y(i)) vector
//! supports only floating-point source
CV_EXPORTS void phase(const GpuMat& x, const GpuMat& y, GpuMat& angle, bool angleInDegrees = false, Stream& stream = Stream::Null());
//! converts Cartesian coordinates to polar
//! supports only floating-point source
CV_EXPORTS void cartToPolar(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, GpuMat& angle, bool angleInDegrees = false, Stream& stream = Stream::Null());
//! converts polar coordinates to Cartesian
//! supports only floating-point source
CV_EXPORTS void polarToCart(const GpuMat& magnitude, const GpuMat& angle, GpuMat& x, GpuMat& y, bool angleInDegrees = false, Stream& stream = Stream::Null());
//! scales and shifts array elements so that either the specified norm (alpha) or the minimum (alpha) and maximum (beta) array values get the specified values
CV_EXPORTS void normalize(const GpuMat& src, GpuMat& dst, double alpha = 1, double beta = 0,
int norm_type = NORM_L2, int dtype = -1, const GpuMat& mask = GpuMat());
CV_EXPORTS void normalize(const GpuMat& src, GpuMat& dst, double a, double b,
int norm_type, int dtype, const GpuMat& mask, GpuMat& norm_buf, GpuMat& cvt_buf);
//! computes mean value and standard deviation of all or selected array elements
//! supports only CV_8UC1 type
CV_EXPORTS void meanStdDev(const GpuMat& mtx, Scalar& mean, Scalar& stddev);
//! buffered version
CV_EXPORTS void meanStdDev(const GpuMat& mtx, Scalar& mean, Scalar& stddev, GpuMat& buf);
//! computes norm of array
//! supports NORM_INF, NORM_L1, NORM_L2
//! supports all matrices except 64F
CV_EXPORTS double norm(const GpuMat& src1, int normType=NORM_L2);
CV_EXPORTS double norm(const GpuMat& src1, int normType, GpuMat& buf);
CV_EXPORTS double norm(const GpuMat& src1, int normType, const GpuMat& mask, GpuMat& buf);
//! computes norm of the difference between two arrays
//! supports NORM_INF, NORM_L1, NORM_L2
//! supports only CV_8UC1 type
CV_EXPORTS double norm(const GpuMat& src1, const GpuMat& src2, int normType=NORM_L2);
//! computes sum of array elements
//! supports only single channel images
CV_EXPORTS Scalar sum(const GpuMat& src);
CV_EXPORTS Scalar sum(const GpuMat& src, GpuMat& buf);
CV_EXPORTS Scalar sum(const GpuMat& src, const GpuMat& mask, GpuMat& buf);
//! computes sum of array elements absolute values
//! supports only single channel images
CV_EXPORTS Scalar absSum(const GpuMat& src);
CV_EXPORTS Scalar absSum(const GpuMat& src, GpuMat& buf);
CV_EXPORTS Scalar absSum(const GpuMat& src, const GpuMat& mask, GpuMat& buf);
//! computes squared sum of array elements
//! supports only single channel images
CV_EXPORTS Scalar sqrSum(const GpuMat& src);
CV_EXPORTS Scalar sqrSum(const GpuMat& src, GpuMat& buf);
CV_EXPORTS Scalar sqrSum(const GpuMat& src, const GpuMat& mask, GpuMat& buf);
//! finds global minimum and maximum array elements and returns their values
CV_EXPORTS void minMax(const GpuMat& src, double* minVal, double* maxVal=0, const GpuMat& mask=GpuMat());
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,
const GpuMat& mask=GpuMat());
CV_EXPORTS void minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc,
const GpuMat& mask, GpuMat& valbuf, GpuMat& locbuf);
//! counts non-zero array elements
CV_EXPORTS int countNonZero(const GpuMat& src);
CV_EXPORTS int countNonZero(const GpuMat& src, GpuMat& buf);
//! reduces a matrix to a vector
CV_EXPORTS void reduce(const GpuMat& mtx, GpuMat& vec, int dim, int reduceOp, int dtype = -1, Stream& stream = Stream::Null());
//! applies fixed threshold to the image
CV_EXPORTS double threshold(const GpuMat& src, GpuMat& dst, double thresh, double maxval, int type, Stream& stream = Stream::Null());
}} // namespace cv { namespace gpu {
#endif /* __OPENCV_GPUARITHM_HPP__ */

0
modules/gpu/perf/perf_core.cpp → modules/gpuarithm/perf/perf_core.cpp
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47
modules/gpuarithm/perf/perf_main.cpp Normal file
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@ -0,0 +1,47 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "perf_precomp.hpp"
using namespace perf;
CV_PERF_TEST_MAIN(gpuarithm, printCudaInfo())

43
modules/gpuarithm/perf/perf_precomp.cpp Normal file
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@ -0,0 +1,43 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "perf_precomp.hpp"

64
modules/gpuarithm/perf/perf_precomp.hpp Normal file
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@ -0,0 +1,64 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifdef __GNUC__
# pragma GCC diagnostic ignored "-Wmissing-declarations"
# if defined __clang__ || defined __APPLE__
# pragma GCC diagnostic ignored "-Wmissing-prototypes"
# pragma GCC diagnostic ignored "-Wextra"
# endif
#endif
#ifndef __OPENCV_PERF_PRECOMP_HPP__
#define __OPENCV_PERF_PRECOMP_HPP__
#include "opencv2/ts.hpp"
#include "opencv2/ts/gpu_perf.hpp"
#include "opencv2/core.hpp"
#include "opencv2/gpuarithm.hpp"
#ifdef GTEST_CREATE_SHARED_LIBRARY
#error no modules except ts should have GTEST_CREATE_SHARED_LIBRARY defined
#endif
#endif

86
modules/gpu/src/arithm.cpp → modules/gpuarithm/src/arithm.cpp
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@ -66,6 +66,61 @@ void cv::gpu::normalize(const GpuMat&, GpuMat&, double, double, int, int, const
////////////////////////////////////////////////////////////////////////
// gemm
#ifdef HAVE_CUBLAS
namespace
{
#define error_entry(entry) { entry, #entry }
struct ErrorEntry
{
int code;
const char* str;
};
struct ErrorEntryComparer
{
int code;
ErrorEntryComparer(int code_) : code(code_) {}
bool operator()(const ErrorEntry& e) const { return e.code == code; }
};
const ErrorEntry cublas_errors[] =
{
error_entry( CUBLAS_STATUS_SUCCESS ),
error_entry( CUBLAS_STATUS_NOT_INITIALIZED ),
error_entry( CUBLAS_STATUS_ALLOC_FAILED ),
error_entry( CUBLAS_STATUS_INVALID_VALUE ),
error_entry( CUBLAS_STATUS_ARCH_MISMATCH ),
error_entry( CUBLAS_STATUS_MAPPING_ERROR ),
error_entry( CUBLAS_STATUS_EXECUTION_FAILED ),
error_entry( CUBLAS_STATUS_INTERNAL_ERROR )
};
const size_t cublas_error_num = sizeof(cublas_errors) / sizeof(cublas_errors[0]);
static inline void ___cublasSafeCall(cublasStatus_t err, const char* file, const int line, const char* func)
{
if (CUBLAS_STATUS_SUCCESS != err)
{
size_t idx = std::find_if(cublas_errors, cublas_errors + cublas_error_num, ErrorEntryComparer(err)) - cublas_errors;
const char* msg = (idx != cublas_error_num) ? cublas_errors[idx].str : "Unknown error code";
String str = cv::format("%s [Code = %d]", msg, err);
cv::error(cv::Error::GpuApiCallError, str, func, file, line);
}
}
}
#if defined(__GNUC__)
#define cublasSafeCall(expr) ___cublasSafeCall(expr, __FILE__, __LINE__, __func__)
#else /* defined(__CUDACC__) || defined(__MSVC__) */
#define cublasSafeCall(expr) ___cublasSafeCall(expr, __FILE__, __LINE__, "")
#endif
#endif
void cv::gpu::gemm(const GpuMat& src1, const GpuMat& src2, double alpha, const GpuMat& src3, double beta, GpuMat& dst, int flags, Stream& stream)
{
#ifndef HAVE_CUBLAS
@ -200,9 +255,14 @@ void cv::gpu::gemm(const GpuMat& src1, const GpuMat& src2, double alpha, const G
////////////////////////////////////////////////////////////////////////
// transpose
namespace arithm
{
template <typename T> void transpose(PtrStepSz<T> src, PtrStepSz<T> dst, cudaStream_t stream);
}
void cv::gpu::transpose(const GpuMat& src, GpuMat& dst, Stream& s)
{
CV_Assert(src.elemSize() == 1 || src.elemSize() == 4 || src.elemSize() == 8);
CV_Assert( src.elemSize() == 1 || src.elemSize() == 4 || src.elemSize() == 8 );
dst.create( src.cols, src.rows, src.type() );
@ -218,35 +278,21 @@ void cv::gpu::transpose(const GpuMat& src, GpuMat& dst, Stream& s)
nppSafeCall( nppiTranspose_8u_C1R(src.ptr<Npp8u>(), static_cast<int>(src.step),
dst.ptr<Npp8u>(), static_cast<int>(dst.step), sz) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
else if (src.elemSize() == 4)
{
NppStStreamHandler h(stream);
NcvSize32u sz;
sz.width = src.cols;
sz.height = src.rows;
ncvSafeCall( nppiStTranspose_32u_C1R(const_cast<Ncv32u*>(src.ptr<Ncv32u>()), static_cast<int>(src.step),
dst.ptr<Ncv32u>(), static_cast<int>(dst.step), sz) );
arithm::transpose<int>(src, dst, stream);
}
else // if (src.elemSize() == 8)
{
if (!deviceSupports(NATIVE_DOUBLE))
CV_Error(cv::Error::StsUnsupportedFormat, "The device doesn't support double");
NppStStreamHandler h(stream);
NcvSize32u sz;
sz.width = src.cols;
sz.height = src.rows;
ncvSafeCall( nppiStTranspose_64u_C1R(const_cast<Ncv64u*>(src.ptr<Ncv64u>()), static_cast<int>(src.step),
dst.ptr<Ncv64u>(), static_cast<int>(dst.step), sz) );
arithm::transpose<double>(src, dst, stream);
}
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
////////////////////////////////////////////////////////////////////////

147
modules/gpuarithm/src/cuda/absdiff_mat.cu Normal file
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@ -0,0 +1,147 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/simd_functions.hpp"
#include "arithm_func_traits.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace arithm
{
struct VAbsDiff4 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vabsdiff4(a, b);
}
__device__ __forceinline__ VAbsDiff4() {}
__device__ __forceinline__ VAbsDiff4(const VAbsDiff4& other) {}
};
struct VAbsDiff2 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vabsdiff2(a, b);
}
__device__ __forceinline__ VAbsDiff2() {}
__device__ __forceinline__ VAbsDiff2(const VAbsDiff2& other) {}
};
__device__ __forceinline__ int _abs(int a)
{
return ::abs(a);
}
__device__ __forceinline__ float _abs(float a)
{
return ::fabsf(a);
}
__device__ __forceinline__ double _abs(double a)
{
return ::fabs(a);
}
template <typename T> struct AbsDiffMat : binary_function<T, T, T>
{
__device__ __forceinline__ T operator ()(T a, T b) const
{
return saturate_cast<T>(_abs(a - b));
}
__device__ __forceinline__ AbsDiffMat() {}
__device__ __forceinline__ AbsDiffMat(const AbsDiffMat& other) {}
};
}
namespace cv { namespace gpu { namespace cudev
{
template <> struct TransformFunctorTraits< arithm::VAbsDiff4 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
{
};
template <> struct TransformFunctorTraits< arithm::VAbsDiff2 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
{
};
template <typename T> struct TransformFunctorTraits< arithm::AbsDiffMat<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
}}}
namespace arithm
{
void absDiffMat_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
{
cudev::transform(src1, src2, dst, VAbsDiff4(), WithOutMask(), stream);
}
void absDiffMat_v2(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
{
cudev::transform(src1, src2, dst, VAbsDiff2(), WithOutMask(), stream);
}
template <typename T>
void absDiffMat(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream)
{
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<T>) dst, AbsDiffMat<T>(), WithOutMask(), stream);
}
template void absDiffMat<uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffMat<schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffMat<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffMat<short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffMat<int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffMat<float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffMat<double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
}
#endif // CUDA_DISABLER

98
modules/gpuarithm/src/cuda/absdiff_scalar.cu Normal file
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@ -0,0 +1,98 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/simd_functions.hpp"
#include "arithm_func_traits.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace arithm
{
template <typename T, typename S> struct AbsDiffScalar : unary_function<T, T>
{
S val;
explicit AbsDiffScalar(S val_) : val(val_) {}
__device__ __forceinline__ T operator ()(T a) const
{
abs_func<S> f;
return saturate_cast<T>(f(a - val));
}
};
}
namespace cv { namespace gpu { namespace cudev
{
template <typename T, typename S> struct TransformFunctorTraits< arithm::AbsDiffScalar<T, S> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
}}}
namespace arithm
{
template <typename T, typename S>
void absDiffScalar(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream)
{
AbsDiffScalar<T, S> op(static_cast<S>(val));
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) dst, op, WithOutMask(), stream);
}
template void absDiffScalar<uchar, float>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffScalar<schar, float>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffScalar<ushort, float>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffScalar<short, float>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffScalar<int, float>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffScalar<float, float>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void absDiffScalar<double, double>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
}
#endif // CUDA_DISABLER

185
modules/gpuarithm/src/cuda/add_mat.cu Normal file
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@ -0,0 +1,185 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/simd_functions.hpp"
#include "arithm_func_traits.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace arithm
{
struct VAdd4 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vadd4(a, b);
}
__device__ __forceinline__ VAdd4() {}
__device__ __forceinline__ VAdd4(const VAdd4& other) {}
};
struct VAdd2 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vadd2(a, b);
}
__device__ __forceinline__ VAdd2() {}
__device__ __forceinline__ VAdd2(const VAdd2& other) {}
};
template <typename T, typename D> struct AddMat : binary_function<T, T, D>
{
__device__ __forceinline__ D operator ()(T a, T b) const
{
return saturate_cast<D>(a + b);
}
__device__ __forceinline__ AddMat() {}
__device__ __forceinline__ AddMat(const AddMat& other) {}
};
}
namespace cv { namespace gpu { namespace cudev
{
template <> struct TransformFunctorTraits< arithm::VAdd4 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
{
};
template <> struct TransformFunctorTraits< arithm::VAdd2 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
{
};
template <typename T, typename D> struct TransformFunctorTraits< arithm::AddMat<T, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
{
};
}}}
namespace arithm
{
void addMat_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
{
cudev::transform(src1, src2, dst, VAdd4(), WithOutMask(), stream);
}
void addMat_v2(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
{
cudev::transform(src1, src2, dst, VAdd2(), WithOutMask(), stream);
}
template <typename T, typename D>
void addMat(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream)
{
if (mask.data)
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<D>) dst, AddMat<T, D>(), mask, stream);
else
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<D>) dst, AddMat<T, D>(), WithOutMask(), stream);
}
template void addMat<uchar, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<uchar, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<uchar, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<uchar, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<uchar, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<uchar, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<uchar, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<schar, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<schar, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<schar, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<schar, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<schar, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<schar, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<schar, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addMat<ushort, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addMat<ushort, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<ushort, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<ushort, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<ushort, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<ushort, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<ushort, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addMat<short, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addMat<short, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<short, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<short, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<short, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<short, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<short, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addMat<int, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addMat<int, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addMat<int, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addMat<int, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<int, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<int, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<int, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addMat<float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addMat<float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addMat<float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addMat<float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addMat<float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<float, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addMat<double, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addMat<double, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addMat<double, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addMat<double, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addMat<double, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addMat<double, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addMat<double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
}
#endif // CUDA_DISABLER

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/simd_functions.hpp"
#include "arithm_func_traits.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace arithm
{
template <typename T, typename S, typename D> struct AddScalar : unary_function<T, D>
{
S val;
explicit AddScalar(S val_) : val(val_) {}
__device__ __forceinline__ D operator ()(T a) const
{
return saturate_cast<D>(a + val);
}
};
}
namespace cv { namespace gpu { namespace cudev
{
template <typename T, typename S, typename D> struct TransformFunctorTraits< arithm::AddScalar<T, S, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
{
};
}}}
namespace arithm
{
template <typename T, typename S, typename D>
void addScalar(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream)
{
AddScalar<T, S, D> op(static_cast<S>(val));
if (mask.data)
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<D>) dst, op, mask, stream);
else
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
}
template void addScalar<uchar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<uchar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<uchar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<uchar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<uchar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<uchar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<uchar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<schar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<schar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<schar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<schar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<schar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<schar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<schar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addScalar<ushort, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addScalar<ushort, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<ushort, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<ushort, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<ushort, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<ushort, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<ushort, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addScalar<short, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addScalar<short, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<short, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<short, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<short, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<short, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<short, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addScalar<int, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addScalar<int, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addScalar<int, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addScalar<int, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<int, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<int, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<int, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addScalar<float, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addScalar<float, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addScalar<float, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addScalar<float, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addScalar<float, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<float, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<float, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addScalar<double, double, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addScalar<double, double, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addScalar<double, double, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addScalar<double, double, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addScalar<double, double, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void addScalar<double, double, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void addScalar<double, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
}
#endif // CUDA_DISABLER

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "arithm_func_traits.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace arithm
{
template <typename T> struct UseDouble_
{
enum {value = 0};
};
template <> struct UseDouble_<double>
{
enum {value = 1};
};
template <typename T1, typename T2, typename D> struct UseDouble
{
enum {value = (UseDouble_<T1>::value || UseDouble_<T2>::value || UseDouble_<D>::value)};
};
template <typename T1, typename T2, typename D, bool useDouble> struct AddWeighted_;
template <typename T1, typename T2, typename D> struct AddWeighted_<T1, T2, D, false> : binary_function<T1, T2, D>
{
float alpha;
float beta;
float gamma;
AddWeighted_(double alpha_, double beta_, double gamma_) : alpha(static_cast<float>(alpha_)), beta(static_cast<float>(beta_)), gamma(static_cast<float>(gamma_)) {}
__device__ __forceinline__ D operator ()(T1 a, T2 b) const
{
return saturate_cast<D>(a * alpha + b * beta + gamma);
}
};
template <typename T1, typename T2, typename D> struct AddWeighted_<T1, T2, D, true> : binary_function<T1, T2, D>
{
double alpha;
double beta;
double gamma;
AddWeighted_(double alpha_, double beta_, double gamma_) : alpha(alpha_), beta(beta_), gamma(gamma_) {}
__device__ __forceinline__ D operator ()(T1 a, T2 b) const
{
return saturate_cast<D>(a * alpha + b * beta + gamma);
}
};
template <typename T1, typename T2, typename D> struct AddWeighted : AddWeighted_<T1, T2, D, UseDouble<T1, T2, D>::value>
{
AddWeighted(double alpha_, double beta_, double gamma_) : AddWeighted_<T1, T2, D, UseDouble<T1, T2, D>::value>(alpha_, beta_, gamma_) {}
};
}
namespace cv { namespace gpu { namespace cudev
{
template <typename T1, typename T2, typename D, size_t src1_size, size_t src2_size, size_t dst_size> struct AddWeightedTraits : DefaultTransformFunctorTraits< arithm::AddWeighted<T1, T2, D> >
{
};
template <typename T1, typename T2, typename D, size_t src_size, size_t dst_size> struct AddWeightedTraits<T1, T2, D, src_size, src_size, dst_size> : arithm::ArithmFuncTraits<src_size, dst_size>
{
};
template <typename T1, typename T2, typename D> struct TransformFunctorTraits< arithm::AddWeighted<T1, T2, D> > : AddWeightedTraits<T1, T2, D, sizeof(T1), sizeof(T2), sizeof(D)>
{
};
}}}
namespace arithm
{
template <typename T1, typename T2, typename D>
void addWeighted(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream)
{
AddWeighted<T1, T2, D> op(alpha, beta, gamma);
cudev::transform((PtrStepSz<T1>) src1, (PtrStepSz<T2>) src2, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
}
template void addWeighted<uchar, uchar, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, uchar, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, uchar, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, uchar, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, uchar, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, uchar, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, uchar, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, schar, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, schar, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, schar, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, schar, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, schar, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, schar, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, schar, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, ushort, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, ushort, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, ushort, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, ushort, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, ushort, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, ushort, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, ushort, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, short, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, short, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, short, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, short, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, short, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, short, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, short, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, int, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, int, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, int, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, int, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, int, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, int, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, int, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, float, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, float, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, float, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, float, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, float, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, float, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, float, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, double, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, double, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, double, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, double, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, double, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, double, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<uchar, double, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, schar, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, schar, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, schar, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, schar, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, schar, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, schar, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, schar, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, ushort, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, ushort, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, ushort, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, ushort, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, ushort, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, ushort, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, ushort, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, short, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, short, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, short, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, short, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, short, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, short, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, short, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, int, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, int, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, int, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, int, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, int, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, int, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, int, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, float, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, float, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, float, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, float, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, float, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, float, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, float, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, double, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, double, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, double, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, double, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, double, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, double, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<schar, double, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, ushort, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, ushort, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, ushort, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, ushort, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, ushort, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, ushort, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, ushort, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, short, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, short, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, short, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, short, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, short, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, short, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, short, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, int, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, int, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, int, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, int, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, int, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, int, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, int, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, float, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, float, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, float, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, float, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, float, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, float, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, float, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, double, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, double, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, double, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, double, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, double, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, double, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<ushort, double, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, short, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, short, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, short, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, short, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, short, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, short, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, short, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, int, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, int, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, int, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, int, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, int, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, int, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, int, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, float, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, float, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, float, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, float, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, float, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, float, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, float, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, double, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, double, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, double, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, double, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, double, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, double, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<short, double, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, int, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, int, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, int, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, int, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, int, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, int, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, int, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, float, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, float, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, float, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, float, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, float, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, float, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, float, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, double, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, double, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, double, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, double, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, double, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, double, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<int, double, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<float, float, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<float, float, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<float, float, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<float, float, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<float, float, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<float, float, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<float, float, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<float, double, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<float, double, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<float, double, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<float, double, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<float, double, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<float, double, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<float, double, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<double, double, uchar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<double, double, schar>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<double, double, ushort>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<double, double, short>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<double, double, int>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<double, double, float>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
template void addWeighted<double, double, double>(PtrStepSzb src1, double alpha, PtrStepSzb src2, double beta, double gamma, PtrStepSzb dst, cudaStream_t stream);
}
#endif /* CUDA_DISABLER */

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __ARITHM_FUNC_TRAITS_HPP__
#define __ARITHM_FUNC_TRAITS_HPP__
#include <cstddef>
namespace arithm
{
template <size_t src_size, size_t dst_size> struct ArithmFuncTraits
{
enum { simple_block_dim_x = 32 };
enum { simple_block_dim_y = 8 };
enum { smart_block_dim_x = 32 };
enum { smart_block_dim_y = 8 };
enum { smart_shift = 1 };
};
template <> struct ArithmFuncTraits<1, 1>
{
enum { simple_block_dim_x = 32 };
enum { simple_block_dim_y = 8 };
enum { smart_block_dim_x = 32 };
enum { smart_block_dim_y = 8 };
enum { smart_shift = 4 };
};
template <> struct ArithmFuncTraits<1, 2>
{
enum { simple_block_dim_x = 32 };
enum { simple_block_dim_y = 8 };
enum { smart_block_dim_x = 32 };
enum { smart_block_dim_y = 8 };
enum { smart_shift = 4 };
};
template <> struct ArithmFuncTraits<1, 4>
{
enum { simple_block_dim_x = 32 };
enum { simple_block_dim_y = 8 };
enum { smart_block_dim_x = 32 };
enum { smart_block_dim_y = 8 };
enum { smart_shift = 4 };
};
template <> struct ArithmFuncTraits<2, 1>
{
enum { simple_block_dim_x = 32 };
enum { simple_block_dim_y = 8 };
enum { smart_block_dim_x = 32 };
enum { smart_block_dim_y = 8 };
enum { smart_shift = 4 };
};
template <> struct ArithmFuncTraits<2, 2>
{
enum { simple_block_dim_x = 32 };
enum { simple_block_dim_y = 8 };
enum { smart_block_dim_x = 32 };
enum { smart_block_dim_y = 8 };
enum { smart_shift = 4 };
};
template <> struct ArithmFuncTraits<2, 4>
{
enum { simple_block_dim_x = 32 };
enum { simple_block_dim_y = 8 };
enum { smart_block_dim_x = 32 };
enum { smart_block_dim_y = 8 };
enum { smart_shift = 4 };
};
template <> struct ArithmFuncTraits<4, 1>
{
enum { simple_block_dim_x = 32 };
enum { simple_block_dim_y = 8 };
enum { smart_block_dim_x = 32 };
enum { smart_block_dim_y = 8 };
enum { smart_shift = 4 };
};
template <> struct ArithmFuncTraits<4, 2>
{
enum { simple_block_dim_x = 32 };
enum { simple_block_dim_y = 8 };
enum { smart_block_dim_x = 32 };
enum { smart_block_dim_y = 8 };
enum { smart_shift = 4 };
};
template <> struct ArithmFuncTraits<4, 4>
{
enum { simple_block_dim_x = 32 };
enum { simple_block_dim_y = 8 };
enum { smart_block_dim_x = 32 };
enum { smart_block_dim_y = 8 };
enum { smart_shift = 4 };
};
}
#endif // __ARITHM_FUNC_TRAITS_HPP__

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/simd_functions.hpp"
#include "arithm_func_traits.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace cv { namespace gpu { namespace cudev
{
template <typename T> struct TransformFunctorTraits< bit_not<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
template <typename T> struct TransformFunctorTraits< bit_and<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
template <typename T> struct TransformFunctorTraits< bit_or<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
template <typename T> struct TransformFunctorTraits< bit_xor<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
}}}
namespace arithm
{
template <typename T> void bitMatNot(PtrStepSzb src, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream)
{
if (mask.data)
cudev::transform((PtrStepSz<T>) src, (PtrStepSz<T>) dst, bit_not<T>(), mask, stream);
else
cudev::transform((PtrStepSz<T>) src, (PtrStepSz<T>) dst, bit_not<T>(), WithOutMask(), stream);
}
template <typename T> void bitMatAnd(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream)
{
if (mask.data)
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<T>) dst, bit_and<T>(), mask, stream);
else
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<T>) dst, bit_and<T>(), WithOutMask(), stream);
}
template <typename T> void bitMatOr(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream)
{
if (mask.data)
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<T>) dst, bit_or<T>(), mask, stream);
else
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<T>) dst, bit_or<T>(), WithOutMask(), stream);
}
template <typename T> void bitMatXor(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream)
{
if (mask.data)
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<T>) dst, bit_xor<T>(), mask, stream);
else
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<T>) dst, bit_xor<T>(), WithOutMask(), stream);
}
template void bitMatNot<uchar>(PtrStepSzb src, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void bitMatNot<ushort>(PtrStepSzb src, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void bitMatNot<uint>(PtrStepSzb src, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void bitMatAnd<uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void bitMatAnd<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void bitMatAnd<uint>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void bitMatOr<uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void bitMatOr<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void bitMatOr<uint>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void bitMatXor<uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void bitMatXor<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void bitMatXor<uint>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
}
#endif // CUDA_DISABLER

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/simd_functions.hpp"
#include "arithm_func_traits.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace cv { namespace gpu { namespace cudev
{
template <typename T> struct TransformFunctorTraits< binder2nd< bit_and<T> > > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
template <typename T> struct TransformFunctorTraits< binder2nd< bit_or<T> > > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
template <typename T> struct TransformFunctorTraits< binder2nd< bit_xor<T> > > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
}}}
namespace arithm
{
template <typename T> void bitScalarAnd(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream)
{
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) dst, cv::gpu::cudev::bind2nd(bit_and<T>(), src2), WithOutMask(), stream);
}
template <typename T> void bitScalarOr(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream)
{
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) dst, cv::gpu::cudev::bind2nd(bit_or<T>(), src2), WithOutMask(), stream);
}
template <typename T> void bitScalarXor(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream)
{
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) dst, cv::gpu::cudev::bind2nd(bit_xor<T>(), src2), WithOutMask(), stream);
}
template void bitScalarAnd<uchar>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
template void bitScalarAnd<ushort>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
template void bitScalarAnd<int>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
template void bitScalarAnd<unsigned int>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
template void bitScalarOr<uchar>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
template void bitScalarOr<ushort>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
template void bitScalarOr<int>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
template void bitScalarOr<unsigned int>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
template void bitScalarXor<uchar>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
template void bitScalarXor<ushort>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
template void bitScalarXor<int>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
template void bitScalarXor<unsigned int>(PtrStepSzb src1, uint src2, PtrStepSzb dst, cudaStream_t stream);
}
#endif // CUDA_DISABLER

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/simd_functions.hpp"
#include "arithm_func_traits.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace arithm
{
struct VCmpEq4 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vcmpeq4(a, b);
}
__device__ __forceinline__ VCmpEq4() {}
__device__ __forceinline__ VCmpEq4(const VCmpEq4& other) {}
};
struct VCmpNe4 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vcmpne4(a, b);
}
__device__ __forceinline__ VCmpNe4() {}
__device__ __forceinline__ VCmpNe4(const VCmpNe4& other) {}
};
struct VCmpLt4 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vcmplt4(a, b);
}
__device__ __forceinline__ VCmpLt4() {}
__device__ __forceinline__ VCmpLt4(const VCmpLt4& other) {}
};
struct VCmpLe4 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vcmple4(a, b);
}
__device__ __forceinline__ VCmpLe4() {}
__device__ __forceinline__ VCmpLe4(const VCmpLe4& other) {}
};
template <class Op, typename T>
struct Cmp : binary_function<T, T, uchar>
{
__device__ __forceinline__ uchar operator()(T a, T b) const
{
Op op;
return -op(a, b);
}
};
}
namespace cv { namespace gpu { namespace cudev
{
template <> struct TransformFunctorTraits< arithm::VCmpEq4 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
{
};
template <> struct TransformFunctorTraits< arithm::VCmpNe4 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
{
};
template <> struct TransformFunctorTraits< arithm::VCmpLt4 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
{
};
template <> struct TransformFunctorTraits< arithm::VCmpLe4 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
{
};
template <class Op, typename T> struct TransformFunctorTraits< arithm::Cmp<Op, T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(uchar)>
{
};
}}}
namespace arithm
{
void cmpMatEq_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
{
cudev::transform(src1, src2, dst, VCmpEq4(), WithOutMask(), stream);
}
void cmpMatNe_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
{
cudev::transform(src1, src2, dst, VCmpNe4(), WithOutMask(), stream);
}
void cmpMatLt_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
{
cudev::transform(src1, src2, dst, VCmpLt4(), WithOutMask(), stream);
}
void cmpMatLe_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
{
cudev::transform(src1, src2, dst, VCmpLe4(), WithOutMask(), stream);
}
template <template <typename> class Op, typename T>
void cmpMat(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream)
{
Cmp<Op<T>, T> op;
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, dst, op, WithOutMask(), stream);
}
template <typename T> void cmpMatEq(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream)
{
cmpMat<equal_to, T>(src1, src2, dst, stream);
}
template <typename T> void cmpMatNe(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream)
{
cmpMat<not_equal_to, T>(src1, src2, dst, stream);
}
template <typename T> void cmpMatLt(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream)
{
cmpMat<less, T>(src1, src2, dst, stream);
}
template <typename T> void cmpMatLe(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream)
{
cmpMat<less_equal, T>(src1, src2, dst, stream);
}
template void cmpMatEq<uchar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatEq<schar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatEq<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatEq<short >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatEq<int >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatEq<float >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatEq<double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatNe<uchar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatNe<schar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatNe<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatNe<short >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatNe<int >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatNe<float >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatNe<double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatLt<uchar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatLt<schar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatLt<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatLt<short >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatLt<int >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatLt<float >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatLt<double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatLe<uchar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatLe<schar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatLe<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatLe<short >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatLe<int >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatLe<float >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void cmpMatLe<double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
}
#endif // CUDA_DISABLER

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/simd_functions.hpp"
#include "opencv2/core/cuda/vec_math.hpp"
#include "arithm_func_traits.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace arithm
{
template <class Op, typename T>
struct Cmp : binary_function<T, T, uchar>
{
__device__ __forceinline__ uchar operator()(T a, T b) const
{
Op op;
return -op(a, b);
}
};
#define TYPE_VEC(type, cn) typename TypeVec<type, cn>::vec_type
template <class Op, typename T, int cn> struct CmpScalar;
template <class Op, typename T>
struct CmpScalar<Op, T, 1> : unary_function<T, uchar>
{
const T val;
__host__ explicit CmpScalar(T val_) : val(val_) {}
__device__ __forceinline__ uchar operator()(T src) const
{
Cmp<Op, T> op;
return op(src, val);
}
};
template <class Op, typename T>
struct CmpScalar<Op, T, 2> : unary_function<TYPE_VEC(T, 2), TYPE_VEC(uchar, 2)>
{
const TYPE_VEC(T, 2) val;
__host__ explicit CmpScalar(TYPE_VEC(T, 2) val_) : val(val_) {}
__device__ __forceinline__ TYPE_VEC(uchar, 2) operator()(const TYPE_VEC(T, 2) & src) const
{
Cmp<Op, T> op;
return VecTraits<TYPE_VEC(uchar, 2)>::make(op(src.x, val.x), op(src.y, val.y));
}
};
template <class Op, typename T>
struct CmpScalar<Op, T, 3> : unary_function<TYPE_VEC(T, 3), TYPE_VEC(uchar, 3)>
{
const TYPE_VEC(T, 3) val;
__host__ explicit CmpScalar(TYPE_VEC(T, 3) val_) : val(val_) {}
__device__ __forceinline__ TYPE_VEC(uchar, 3) operator()(const TYPE_VEC(T, 3) & src) const
{
Cmp<Op, T> op;
return VecTraits<TYPE_VEC(uchar, 3)>::make(op(src.x, val.x), op(src.y, val.y), op(src.z, val.z));
}
};
template <class Op, typename T>
struct CmpScalar<Op, T, 4> : unary_function<TYPE_VEC(T, 4), TYPE_VEC(uchar, 4)>
{
const TYPE_VEC(T, 4) val;
__host__ explicit CmpScalar(TYPE_VEC(T, 4) val_) : val(val_) {}
__device__ __forceinline__ TYPE_VEC(uchar, 4) operator()(const TYPE_VEC(T, 4) & src) const
{
Cmp<Op, T> op;
return VecTraits<TYPE_VEC(uchar, 4)>::make(op(src.x, val.x), op(src.y, val.y), op(src.z, val.z), op(src.w, val.w));
}
};
#undef TYPE_VEC
}
namespace cv { namespace gpu { namespace cudev
{
template <class Op, typename T> struct TransformFunctorTraits< arithm::CmpScalar<Op, T, 1> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(uchar)>
{
};
}}}
namespace arithm
{
template <template <typename> class Op, typename T, int cn>
void cmpScalar(PtrStepSzb src, double val[4], PtrStepSzb dst, cudaStream_t stream)
{
typedef typename TypeVec<T, cn>::vec_type src_t;
typedef typename TypeVec<uchar, cn>::vec_type dst_t;
T sval[] = {static_cast<T>(val[0]), static_cast<T>(val[1]), static_cast<T>(val[2]), static_cast<T>(val[3])};
src_t val1 = VecTraits<src_t>::make(sval);
CmpScalar<Op<T>, T, cn> op(val1);
cudev::transform((PtrStepSz<src_t>) src, (PtrStepSz<dst_t>) dst, op, WithOutMask(), stream);
}
template <typename T> void cmpScalarEq(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream)
{
typedef void (*func_t)(PtrStepSzb src, double val[4], PtrStepSzb dst, cudaStream_t stream);
static const func_t funcs[] =
{
0,
cmpScalar<equal_to, T, 1>,
cmpScalar<equal_to, T, 2>,
cmpScalar<equal_to, T, 3>,
cmpScalar<equal_to, T, 4>
};
funcs[cn](src, val, dst, stream);
}
template <typename T> void cmpScalarNe(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream)
{
typedef void (*func_t)(PtrStepSzb src, double val[4], PtrStepSzb dst, cudaStream_t stream);
static const func_t funcs[] =
{
0,
cmpScalar<not_equal_to, T, 1>,
cmpScalar<not_equal_to, T, 2>,
cmpScalar<not_equal_to, T, 3>,
cmpScalar<not_equal_to, T, 4>
};
funcs[cn](src, val, dst, stream);
}
template <typename T> void cmpScalarLt(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream)
{
typedef void (*func_t)(PtrStepSzb src, double val[4], PtrStepSzb dst, cudaStream_t stream);
static const func_t funcs[] =
{
0,
cmpScalar<less, T, 1>,
cmpScalar<less, T, 2>,
cmpScalar<less, T, 3>,
cmpScalar<less, T, 4>
};
funcs[cn](src, val, dst, stream);
}
template <typename T> void cmpScalarLe(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream)
{
typedef void (*func_t)(PtrStepSzb src, double val[4], PtrStepSzb dst, cudaStream_t stream);
static const func_t funcs[] =
{
0,
cmpScalar<less_equal, T, 1>,
cmpScalar<less_equal, T, 2>,
cmpScalar<less_equal, T, 3>,
cmpScalar<less_equal, T, 4>
};
funcs[cn](src, val, dst, stream);
}
template <typename T> void cmpScalarGt(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream)
{
typedef void (*func_t)(PtrStepSzb src, double val[4], PtrStepSzb dst, cudaStream_t stream);
static const func_t funcs[] =
{
0,
cmpScalar<greater, T, 1>,
cmpScalar<greater, T, 2>,
cmpScalar<greater, T, 3>,
cmpScalar<greater, T, 4>
};
funcs[cn](src, val, dst, stream);
}
template <typename T> void cmpScalarGe(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream)
{
typedef void (*func_t)(PtrStepSzb src, double val[4], PtrStepSzb dst, cudaStream_t stream);
static const func_t funcs[] =
{
0,
cmpScalar<greater_equal, T, 1>,
cmpScalar<greater_equal, T, 2>,
cmpScalar<greater_equal, T, 3>,
cmpScalar<greater_equal, T, 4>
};
funcs[cn](src, val, dst, stream);
}
template void cmpScalarEq<uchar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarEq<schar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarEq<ushort>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarEq<short >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarEq<int >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarEq<float >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarEq<double>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarNe<uchar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarNe<schar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarNe<ushort>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarNe<short >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarNe<int >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarNe<float >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarNe<double>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarLt<uchar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarLt<schar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarLt<ushort>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarLt<short >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarLt<int >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarLt<float >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarLt<double>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarLe<uchar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarLe<schar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarLe<ushort>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarLe<short >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarLe<int >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarLe<float >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarLe<double>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarGt<uchar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarGt<schar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarGt<ushort>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarGt<short >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarGt<int >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarGt<float >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarGt<double>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarGe<uchar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarGe<schar >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarGe<ushort>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarGe<short >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarGe<int >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarGe<float >(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
template void cmpScalarGe<double>(PtrStepSzb src, int cn, double val[4], PtrStepSzb dst, cudaStream_t stream);
}
#endif // CUDA_DISABLER

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/vec_traits.hpp"
#include "opencv2/core/cuda/vec_math.hpp"
#include "opencv2/core/cuda/reduce.hpp"
#include "opencv2/core/cuda/emulation.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace countNonZero
{
__device__ unsigned int blocks_finished = 0;
template <int BLOCK_SIZE, typename T>
__global__ void kernel(const PtrStepSz<T> src, unsigned int* count, const int twidth, const int theight)
{
__shared__ unsigned int scount[BLOCK_SIZE];
const int x0 = blockIdx.x * blockDim.x * twidth + threadIdx.x;
const int y0 = blockIdx.y * blockDim.y * theight + threadIdx.y;
const int tid = threadIdx.y * blockDim.x + threadIdx.x;
unsigned int mycount = 0;
for (int i = 0, y = y0; i < theight && y < src.rows; ++i, y += blockDim.y)
{
const T* ptr = src.ptr(y);
for (int j = 0, x = x0; j < twidth && x < src.cols; ++j, x += blockDim.x)
{
const T srcVal = ptr[x];
mycount += (srcVal != 0);
}
}
cudev::reduce<BLOCK_SIZE>(scount, mycount, tid, plus<unsigned int>());
#if __CUDA_ARCH__ >= 200
if (tid == 0)
::atomicAdd(count, mycount);
#else
__shared__ bool is_last;
const int bid = blockIdx.y * gridDim.x + blockIdx.x;
if (tid == 0)
{
count[bid] = mycount;
__threadfence();
unsigned int ticket = ::atomicInc(&blocks_finished, gridDim.x * gridDim.y);
is_last = (ticket == gridDim.x * gridDim.y - 1);
}
__syncthreads();
if (is_last)
{
mycount = tid < gridDim.x * gridDim.y ? count[tid] : 0;
cudev::reduce<BLOCK_SIZE>(scount, mycount, tid, plus<unsigned int>());
if (tid == 0)
{
count[0] = mycount;
blocks_finished = 0;
}
}
#endif
}
const int threads_x = 32;
const int threads_y = 8;
void getLaunchCfg(int cols, int rows, dim3& block, dim3& grid)
{
block = dim3(threads_x, threads_y);
grid = dim3(divUp(cols, block.x * block.y),
divUp(rows, block.y * block.x));
grid.x = ::min(grid.x, block.x);
grid.y = ::min(grid.y, block.y);
}
void getBufSize(int cols, int rows, int& bufcols, int& bufrows)
{
dim3 block, grid;
getLaunchCfg(cols, rows, block, grid);
bufcols = grid.x * grid.y * sizeof(int);
bufrows = 1;
}
template <typename T>
int run(const PtrStepSzb src, PtrStep<unsigned int> buf)
{
dim3 block, grid;
getLaunchCfg(src.cols, src.rows, block, grid);
const int twidth = divUp(divUp(src.cols, grid.x), block.x);
const int theight = divUp(divUp(src.rows, grid.y), block.y);
unsigned int* count_buf = buf.ptr(0);
cudaSafeCall( cudaMemset(count_buf, 0, sizeof(unsigned int)) );
kernel<threads_x * threads_y><<<grid, block>>>((PtrStepSz<T>) src, count_buf, twidth, theight);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaDeviceSynchronize() );
unsigned int count;
cudaSafeCall(cudaMemcpy(&count, count_buf, sizeof(unsigned int), cudaMemcpyDeviceToHost));
return count;
}
template int run<uchar >(const PtrStepSzb src, PtrStep<unsigned int> buf);
template int run<schar >(const PtrStepSzb src, PtrStep<unsigned int> buf);
template int run<ushort>(const PtrStepSzb src, PtrStep<unsigned int> buf);
template int run<short >(const PtrStepSzb src, PtrStep<unsigned int> buf);
template int run<int >(const PtrStepSzb src, PtrStep<unsigned int> buf);
template int run<float >(const PtrStepSzb src, PtrStep<unsigned int> buf);
template int run<double>(const PtrStepSzb src, PtrStep<unsigned int> buf);
}
#endif // CUDA_DISABLER

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/simd_functions.hpp"
#include "arithm_func_traits.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace arithm
{
template <typename T, typename S, typename D> struct DivInv : unary_function<T, D>
{
S val;
explicit DivInv(S val_) : val(val_) {}
__device__ __forceinline__ D operator ()(T a) const
{
return a != 0 ? saturate_cast<D>(val / a) : 0;
}
};
}
namespace cv { namespace gpu { namespace cudev
{
template <typename T, typename S, typename D> struct TransformFunctorTraits< arithm::DivInv<T, S, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
{
};
}}}
namespace arithm
{
template <typename T, typename S, typename D>
void divInv(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream)
{
DivInv<T, S, D> op(static_cast<S>(val));
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
}
template void divInv<uchar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<uchar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<uchar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<uchar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<uchar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<uchar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<uchar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<schar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<schar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<schar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<schar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<schar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<schar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<schar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divInv<ushort, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divInv<ushort, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<ushort, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<ushort, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<ushort, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<ushort, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<ushort, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divInv<short, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divInv<short, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<short, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<short, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<short, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<short, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<short, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divInv<int, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divInv<int, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divInv<int, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divInv<int, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<int, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<int, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<int, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divInv<float, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divInv<float, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divInv<float, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divInv<float, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divInv<float, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<float, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<float, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divInv<double, double, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divInv<double, double, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divInv<double, double, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divInv<double, double, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divInv<double, double, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divInv<double, double, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divInv<double, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
}
#endif // CUDA_DISABLER

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/simd_functions.hpp"
#include "arithm_func_traits.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace arithm
{
struct Div_8uc4_32f : binary_function<uint, float, uint>
{
__device__ __forceinline__ uint operator ()(uint a, float b) const
{
uint res = 0;
if (b != 0)
{
b = 1.0f / b;
res |= (saturate_cast<uchar>((0xffu & (a )) * b) );
res |= (saturate_cast<uchar>((0xffu & (a >> 8)) * b) << 8);
res |= (saturate_cast<uchar>((0xffu & (a >> 16)) * b) << 16);
res |= (saturate_cast<uchar>((0xffu & (a >> 24)) * b) << 24);
}
return res;
}
};
struct Div_16sc4_32f : binary_function<short4, float, short4>
{
__device__ __forceinline__ short4 operator ()(short4 a, float b) const
{
return b != 0 ? make_short4(saturate_cast<short>(a.x / b), saturate_cast<short>(a.y / b),
saturate_cast<short>(a.z / b), saturate_cast<short>(a.w / b))
: make_short4(0,0,0,0);
}
};
template <typename T, typename D> struct Div : binary_function<T, T, D>
{
__device__ __forceinline__ D operator ()(T a, T b) const
{
return b != 0 ? saturate_cast<D>(a / b) : 0;
}
__device__ __forceinline__ Div() {}
__device__ __forceinline__ Div(const Div& other) {}
};
template <typename T> struct Div<T, float> : binary_function<T, T, float>
{
__device__ __forceinline__ float operator ()(T a, T b) const
{
return b != 0 ? static_cast<float>(a) / b : 0;
}
__device__ __forceinline__ Div() {}
__device__ __forceinline__ Div(const Div& other) {}
};
template <typename T> struct Div<T, double> : binary_function<T, T, double>
{
__device__ __forceinline__ double operator ()(T a, T b) const
{
return b != 0 ? static_cast<double>(a) / b : 0;
}
__device__ __forceinline__ Div() {}
__device__ __forceinline__ Div(const Div& other) {}
};
template <typename T, typename S, typename D> struct DivScale : binary_function<T, T, D>
{
S scale;
explicit DivScale(S scale_) : scale(scale_) {}
__device__ __forceinline__ D operator ()(T a, T b) const
{
return b != 0 ? saturate_cast<D>(scale * a / b) : 0;
}
};
}
namespace cv { namespace gpu { namespace cudev
{
template <> struct TransformFunctorTraits<arithm::Div_8uc4_32f> : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
{
};
template <typename T, typename D> struct TransformFunctorTraits< arithm::Div<T, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
{
};
template <typename T, typename S, typename D> struct TransformFunctorTraits< arithm::DivScale<T, S, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
{
};
}}}
namespace arithm
{
void divMat_8uc4_32f(PtrStepSz<uint> src1, PtrStepSzf src2, PtrStepSz<uint> dst, cudaStream_t stream)
{
cudev::transform(src1, src2, dst, Div_8uc4_32f(), WithOutMask(), stream);
}
void divMat_16sc4_32f(PtrStepSz<short4> src1, PtrStepSzf src2, PtrStepSz<short4> dst, cudaStream_t stream)
{
cudev::transform(src1, src2, dst, Div_16sc4_32f(), WithOutMask(), stream);
}
template <typename T, typename S, typename D>
void divMat(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream)
{
if (scale == 1)
{
Div<T, D> op;
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
}
else
{
DivScale<T, S, D> op(static_cast<S>(scale));
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
}
}
template void divMat<uchar, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<uchar, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<uchar, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<uchar, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<uchar, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<uchar, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<uchar, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<schar, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<schar, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<schar, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<schar, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<schar, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<schar, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<schar, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void divMat<ushort, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void divMat<ushort, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<ushort, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<ushort, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<ushort, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<ushort, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<ushort, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void divMat<short, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void divMat<short, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<short, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<short, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<short, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<short, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<short, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void divMat<int, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void divMat<int, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void divMat<int, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void divMat<int, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<int, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<int, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<int, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void divMat<float, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void divMat<float, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void divMat<float, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void divMat<float, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void divMat<float, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<float, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<float, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void divMat<double, double, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void divMat<double, double, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void divMat<double, double, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void divMat<double, double, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void divMat<double, double, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void divMat<double, double, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void divMat<double, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
}
#endif // CUDA_DISABLER

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/simd_functions.hpp"
#include "arithm_func_traits.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace arithm
{
template <typename T, typename S, typename D> struct DivScalar : unary_function<T, D>
{
S val;
explicit DivScalar(S val_) : val(val_) {}
__device__ __forceinline__ D operator ()(T a) const
{
return saturate_cast<D>(a / val);
}
};
}
namespace cv { namespace gpu { namespace cudev
{
template <typename T, typename S, typename D> struct TransformFunctorTraits< arithm::DivScalar<T, S, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
{
};
}}}
namespace arithm
{
template <typename T, typename S, typename D>
void divScalar(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream)
{
DivScalar<T, S, D> op(static_cast<S>(val));
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
}
template void divScalar<uchar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<uchar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<uchar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<uchar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<uchar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<uchar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<uchar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<schar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<schar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<schar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<schar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<schar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<schar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<schar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divScalar<ushort, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divScalar<ushort, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<ushort, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<ushort, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<ushort, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<ushort, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<ushort, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divScalar<short, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divScalar<short, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<short, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<short, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<short, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<short, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<short, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divScalar<int, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divScalar<int, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divScalar<int, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divScalar<int, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<int, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<int, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<int, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divScalar<float, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divScalar<float, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divScalar<float, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divScalar<float, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divScalar<float, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<float, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<float, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divScalar<double, double, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divScalar<double, double, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divScalar<double, double, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divScalar<double, double, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divScalar<double, double, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void divScalar<double, double, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void divScalar<double, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
}
#endif // CUDA_DISABLER

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/simd_functions.hpp"
#include "opencv2/core/cuda/limits.hpp"
#include "opencv2/core/cuda/type_traits.hpp"
#include "arithm_func_traits.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
//////////////////////////////////////////////////////////////////////////
// absMat
namespace cv { namespace gpu { namespace cudev
{
template <typename T> struct TransformFunctorTraits< abs_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
}}}
namespace arithm
{
template <typename T>
void absMat(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream)
{
cudev::transform((PtrStepSz<T>) src, (PtrStepSz<T>) dst, abs_func<T>(), WithOutMask(), stream);
}
template void absMat<uchar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void absMat<schar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void absMat<ushort>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void absMat<short>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void absMat<int>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void absMat<float>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void absMat<double>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
}
//////////////////////////////////////////////////////////////////////////
// sqrMat
namespace arithm
{
template <typename T> struct Sqr : unary_function<T, T>
{
__device__ __forceinline__ T operator ()(T x) const
{
return saturate_cast<T>(x * x);
}
__device__ __forceinline__ Sqr() {}
__device__ __forceinline__ Sqr(const Sqr& other) {}
};
}
namespace cv { namespace gpu { namespace cudev
{
template <typename T> struct TransformFunctorTraits< arithm::Sqr<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
}}}
namespace arithm
{
template <typename T>
void sqrMat(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream)
{
cudev::transform((PtrStepSz<T>) src, (PtrStepSz<T>) dst, Sqr<T>(), WithOutMask(), stream);
}
template void sqrMat<uchar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void sqrMat<schar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void sqrMat<ushort>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void sqrMat<short>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void sqrMat<int>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void sqrMat<float>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void sqrMat<double>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
}
//////////////////////////////////////////////////////////////////////////
// sqrtMat
namespace cv { namespace gpu { namespace cudev
{
template <typename T> struct TransformFunctorTraits< sqrt_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
}}}
namespace arithm
{
template <typename T>
void sqrtMat(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream)
{
cudev::transform((PtrStepSz<T>) src, (PtrStepSz<T>) dst, sqrt_func<T>(), WithOutMask(), stream);
}
template void sqrtMat<uchar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void sqrtMat<schar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void sqrtMat<ushort>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void sqrtMat<short>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void sqrtMat<int>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void sqrtMat<float>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void sqrtMat<double>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
}
//////////////////////////////////////////////////////////////////////////
// logMat
namespace cv { namespace gpu { namespace cudev
{
template <typename T> struct TransformFunctorTraits< log_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
}}}
namespace arithm
{
template <typename T>
void logMat(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream)
{
cudev::transform((PtrStepSz<T>) src, (PtrStepSz<T>) dst, log_func<T>(), WithOutMask(), stream);
}
template void logMat<uchar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void logMat<schar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void logMat<ushort>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void logMat<short>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void logMat<int>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void logMat<float>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void logMat<double>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
}
//////////////////////////////////////////////////////////////////////////
// expMat
namespace arithm
{
template <typename T> struct Exp : unary_function<T, T>
{
__device__ __forceinline__ T operator ()(T x) const
{
exp_func<T> f;
return saturate_cast<T>(f(x));
}
__device__ __forceinline__ Exp() {}
__device__ __forceinline__ Exp(const Exp& other) {}
};
}
namespace cv { namespace gpu { namespace cudev
{
template <typename T> struct TransformFunctorTraits< arithm::Exp<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
}}}
namespace arithm
{
template <typename T>
void expMat(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream)
{
cudev::transform((PtrStepSz<T>) src, (PtrStepSz<T>) dst, Exp<T>(), WithOutMask(), stream);
}
template void expMat<uchar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void expMat<schar>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void expMat<ushort>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void expMat<short>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void expMat<int>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void expMat<float>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
template void expMat<double>(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream);
}
//////////////////////////////////////////////////////////////////////////
// pow
namespace arithm
{
template<typename T, bool Signed = numeric_limits<T>::is_signed> struct PowOp : unary_function<T, T>
{
float power;
PowOp(double power_) : power(static_cast<float>(power_)) {}
__device__ __forceinline__ T operator()(T e) const
{
return saturate_cast<T>(__powf((float)e, power));
}
};
template<typename T> struct PowOp<T, true> : unary_function<T, T>
{
float power;
PowOp(double power_) : power(static_cast<float>(power_)) {}
__device__ __forceinline__ T operator()(T e) const
{
T res = saturate_cast<T>(__powf((float)e, power));
if ((e < 0) && (1 & static_cast<int>(power)))
res *= -1;
return res;
}
};
template<> struct PowOp<float> : unary_function<float, float>
{
const float power;
PowOp(double power_) : power(static_cast<float>(power_)) {}
__device__ __forceinline__ float operator()(float e) const
{
return __powf(::fabs(e), power);
}
};
template<> struct PowOp<double> : unary_function<double, double>
{
double power;
PowOp(double power_) : power(power_) {}
__device__ __forceinline__ double operator()(double e) const
{
return ::pow(::fabs(e), power);
}
};
}
namespace cv { namespace gpu { namespace cudev
{
template <typename T> struct TransformFunctorTraits< arithm::PowOp<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
}}}
namespace arithm
{
template<typename T>
void pow(PtrStepSzb src, double power, PtrStepSzb dst, cudaStream_t stream)
{
cudev::transform((PtrStepSz<T>) src, (PtrStepSz<T>) dst, PowOp<T>(power), WithOutMask(), stream);
}
template void pow<uchar>(PtrStepSzb src, double power, PtrStepSzb dst, cudaStream_t stream);
template void pow<schar>(PtrStepSzb src, double power, PtrStepSzb dst, cudaStream_t stream);
template void pow<short>(PtrStepSzb src, double power, PtrStepSzb dst, cudaStream_t stream);
template void pow<ushort>(PtrStepSzb src, double power, PtrStepSzb dst, cudaStream_t stream);
template void pow<int>(PtrStepSzb src, double power, PtrStepSzb dst, cudaStream_t stream);
template void pow<float>(PtrStepSzb src, double power, PtrStepSzb dst, cudaStream_t stream);
template void pow<double>(PtrStepSzb src, double power, PtrStepSzb dst, cudaStream_t stream);
}
#endif // CUDA_DISABLER

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/vec_traits.hpp"
#include "opencv2/core/cuda/vec_math.hpp"
#include "opencv2/core/cuda/reduce.hpp"
#include "opencv2/core/cuda/emulation.hpp"
#include "opencv2/core/cuda/limits.hpp"
#include "opencv2/core/cuda/utility.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace minMax
{
__device__ unsigned int blocks_finished = 0;
// To avoid shared bank conflicts we convert each value into value of
// appropriate type (32 bits minimum)
template <typename T> struct MinMaxTypeTraits;
template <> struct MinMaxTypeTraits<uchar> { typedef int best_type; };
template <> struct MinMaxTypeTraits<schar> { typedef int best_type; };
template <> struct MinMaxTypeTraits<ushort> { typedef int best_type; };
template <> struct MinMaxTypeTraits<short> { typedef int best_type; };
template <> struct MinMaxTypeTraits<int> { typedef int best_type; };
template <> struct MinMaxTypeTraits<float> { typedef float best_type; };
template <> struct MinMaxTypeTraits<double> { typedef double best_type; };
template <int BLOCK_SIZE, typename R>
struct GlobalReduce
{
static __device__ void run(R& mymin, R& mymax, R* minval, R* maxval, int tid, int bid, R* sminval, R* smaxval)
{
#if __CUDA_ARCH__ >= 200
if (tid == 0)
{
Emulation::glob::atomicMin(minval, mymin);
Emulation::glob::atomicMax(maxval, mymax);
}
#else
__shared__ bool is_last;
if (tid == 0)
{
minval[bid] = mymin;
maxval[bid] = mymax;
__threadfence();
unsigned int ticket = ::atomicAdd(&blocks_finished, 1);
is_last = (ticket == gridDim.x * gridDim.y - 1);
}
__syncthreads();
if (is_last)
{
int idx = ::min(tid, gridDim.x * gridDim.y - 1);
mymin = minval[idx];
mymax = maxval[idx];
const minimum<R> minOp;
const maximum<R> maxOp;
cudev::reduce<BLOCK_SIZE>(smem_tuple(sminval, smaxval), thrust::tie(mymin, mymax), tid, thrust::make_tuple(minOp, maxOp));
if (tid == 0)
{
minval[0] = mymin;
maxval[0] = mymax;
blocks_finished = 0;
}
}
#endif
}
};
template <int BLOCK_SIZE, typename T, typename R, class Mask>
__global__ void kernel(const PtrStepSz<T> src, const Mask mask, R* minval, R* maxval, const int twidth, const int theight)
{
__shared__ R sminval[BLOCK_SIZE];
__shared__ R smaxval[BLOCK_SIZE];
const int x0 = blockIdx.x * blockDim.x * twidth + threadIdx.x;
const int y0 = blockIdx.y * blockDim.y * theight + threadIdx.y;
const int tid = threadIdx.y * blockDim.x + threadIdx.x;
const int bid = blockIdx.y * gridDim.x + blockIdx.x;
R mymin = numeric_limits<R>::max();
R mymax = -numeric_limits<R>::max();
const minimum<R> minOp;
const maximum<R> maxOp;
for (int i = 0, y = y0; i < theight && y < src.rows; ++i, y += blockDim.y)
{
const T* ptr = src.ptr(y);
for (int j = 0, x = x0; j < twidth && x < src.cols; ++j, x += blockDim.x)
{
if (mask(y, x))
{
const R srcVal = ptr[x];
mymin = minOp(mymin, srcVal);
mymax = maxOp(mymax, srcVal);
}
}
}
cudev::reduce<BLOCK_SIZE>(smem_tuple(sminval, smaxval), thrust::tie(mymin, mymax), tid, thrust::make_tuple(minOp, maxOp));
GlobalReduce<BLOCK_SIZE, R>::run(mymin, mymax, minval, maxval, tid, bid, sminval, smaxval);
}
const int threads_x = 32;
const int threads_y = 8;
void getLaunchCfg(int cols, int rows, dim3& block, dim3& grid)
{
block = dim3(threads_x, threads_y);
grid = dim3(divUp(cols, block.x * block.y),
divUp(rows, block.y * block.x));
grid.x = ::min(grid.x, block.x);
grid.y = ::min(grid.y, block.y);
}
void getBufSize(int cols, int rows, int& bufcols, int& bufrows)
{
dim3 block, grid;
getLaunchCfg(cols, rows, block, grid);
bufcols = grid.x * grid.y * sizeof(double);
bufrows = 2;
}
__global__ void setDefaultKernel(int* minval_buf, int* maxval_buf)
{
*minval_buf = numeric_limits<int>::max();
*maxval_buf = numeric_limits<int>::min();
}
__global__ void setDefaultKernel(float* minval_buf, float* maxval_buf)
{
*minval_buf = numeric_limits<float>::max();
*maxval_buf = -numeric_limits<float>::max();
}
__global__ void setDefaultKernel(double* minval_buf, double* maxval_buf)
{
*minval_buf = numeric_limits<double>::max();
*maxval_buf = -numeric_limits<double>::max();
}
template <typename R>
void setDefault(R* minval_buf, R* maxval_buf)
{
setDefaultKernel<<<1, 1>>>(minval_buf, maxval_buf);
}
template <typename T>
void run(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf)
{
typedef typename MinMaxTypeTraits<T>::best_type R;
dim3 block, grid;
getLaunchCfg(src.cols, src.rows, block, grid);
const int twidth = divUp(divUp(src.cols, grid.x), block.x);
const int theight = divUp(divUp(src.rows, grid.y), block.y);
R* minval_buf = (R*) buf.ptr(0);
R* maxval_buf = (R*) buf.ptr(1);
setDefault(minval_buf, maxval_buf);
if (mask.data)
kernel<threads_x * threads_y><<<grid, block>>>((PtrStepSz<T>) src, SingleMask(mask), minval_buf, maxval_buf, twidth, theight);
else
kernel<threads_x * threads_y><<<grid, block>>>((PtrStepSz<T>) src, WithOutMask(), minval_buf, maxval_buf, twidth, theight);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaDeviceSynchronize() );
R minval_, maxval_;
cudaSafeCall( cudaMemcpy(&minval_, minval_buf, sizeof(R), cudaMemcpyDeviceToHost) );
cudaSafeCall( cudaMemcpy(&maxval_, maxval_buf, sizeof(R), cudaMemcpyDeviceToHost) );
*minval = minval_;
*maxval = maxval_;
}
template void run<uchar >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
template void run<schar >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
template void run<ushort>(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
template void run<short >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
template void run<int >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
template void run<float >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
template void run<double>(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, PtrStepb buf);
}
#endif // CUDA_DISABLER

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/simd_functions.hpp"
#include "arithm_func_traits.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
//////////////////////////////////////////////////////////////////////////
// min
namespace arithm
{
struct VMin4 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vmin4(a, b);
}
__device__ __forceinline__ VMin4() {}
__device__ __forceinline__ VMin4(const VMin4& other) {}
};
struct VMin2 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vmin2(a, b);
}
__device__ __forceinline__ VMin2() {}
__device__ __forceinline__ VMin2(const VMin2& other) {}
};
}
namespace cv { namespace gpu { namespace cudev
{
template <> struct TransformFunctorTraits< arithm::VMin4 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
{
};
template <> struct TransformFunctorTraits< arithm::VMin2 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
{
};
template <typename T> struct TransformFunctorTraits< minimum<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
template <typename T> struct TransformFunctorTraits< binder2nd< minimum<T> > > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
}}}
namespace arithm
{
void minMat_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
{
cudev::transform(src1, src2, dst, VMin4(), WithOutMask(), stream);
}
void minMat_v2(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
{
cudev::transform(src1, src2, dst, VMin2(), WithOutMask(), stream);
}
template <typename T> void minMat(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream)
{
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<T>) dst, minimum<T>(), WithOutMask(), stream);
}
template void minMat<uchar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void minMat<schar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void minMat<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void minMat<short >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void minMat<int >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void minMat<float >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void minMat<double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template <typename T> void minScalar(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream)
{
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) dst, cv::gpu::cudev::bind2nd(minimum<T>(), src2), WithOutMask(), stream);
}
template void minScalar<uchar >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void minScalar<schar >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void minScalar<ushort>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void minScalar<short >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void minScalar<int >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void minScalar<float >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void minScalar<double>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
}
//////////////////////////////////////////////////////////////////////////
// max
namespace arithm
{
struct VMax4 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vmax4(a, b);
}
__device__ __forceinline__ VMax4() {}
__device__ __forceinline__ VMax4(const VMax4& other) {}
};
struct VMax2 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vmax2(a, b);
}
__device__ __forceinline__ VMax2() {}
__device__ __forceinline__ VMax2(const VMax2& other) {}
};
}
namespace cv { namespace gpu { namespace cudev
{
template <> struct TransformFunctorTraits< arithm::VMax4 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
{
};
template <> struct TransformFunctorTraits< arithm::VMax2 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
{
};
template <typename T> struct TransformFunctorTraits< maximum<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
template <typename T> struct TransformFunctorTraits< binder2nd< maximum<T> > > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
}}}
namespace arithm
{
void maxMat_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
{
cudev::transform(src1, src2, dst, VMax4(), WithOutMask(), stream);
}
void maxMat_v2(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
{
cudev::transform(src1, src2, dst, VMax2(), WithOutMask(), stream);
}
template <typename T> void maxMat(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream)
{
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<T>) dst, maximum<T>(), WithOutMask(), stream);
}
template void maxMat<uchar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void maxMat<schar >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void maxMat<ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void maxMat<short >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void maxMat<int >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void maxMat<float >(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template void maxMat<double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template <typename T> void maxScalar(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream)
{
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) dst, cv::gpu::cudev::bind2nd(maximum<T>(), src2), WithOutMask(), stream);
}
template void maxScalar<uchar >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void maxScalar<schar >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void maxScalar<ushort>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void maxScalar<short >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void maxScalar<int >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void maxScalar<float >(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
template void maxScalar<double>(PtrStepSzb src1, double src2, PtrStepSzb dst, cudaStream_t stream);
}
#endif // CUDA_DISABLER

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/vec_traits.hpp"
#include "opencv2/core/cuda/vec_math.hpp"
#include "opencv2/core/cuda/reduce.hpp"
#include "opencv2/core/cuda/emulation.hpp"
#include "opencv2/core/cuda/limits.hpp"
#include "opencv2/core/cuda/utility.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace minMaxLoc
{
// To avoid shared bank conflicts we convert each value into value of
// appropriate type (32 bits minimum)
template <typename T> struct MinMaxTypeTraits;
template <> struct MinMaxTypeTraits<unsigned char> { typedef int best_type; };
template <> struct MinMaxTypeTraits<signed char> { typedef int best_type; };
template <> struct MinMaxTypeTraits<unsigned short> { typedef int best_type; };
template <> struct MinMaxTypeTraits<short> { typedef int best_type; };
template <> struct MinMaxTypeTraits<int> { typedef int best_type; };
template <> struct MinMaxTypeTraits<float> { typedef float best_type; };
template <> struct MinMaxTypeTraits<double> { typedef double best_type; };
template <int BLOCK_SIZE, typename T, class Mask>
__global__ void kernel_pass_1(const PtrStepSz<T> src, const Mask mask, T* minval, T* maxval, unsigned int* minloc, unsigned int* maxloc, const int twidth, const int theight)
{
typedef typename MinMaxTypeTraits<T>::best_type work_type;
__shared__ work_type sminval[BLOCK_SIZE];
__shared__ work_type smaxval[BLOCK_SIZE];
__shared__ unsigned int sminloc[BLOCK_SIZE];
__shared__ unsigned int smaxloc[BLOCK_SIZE];
const int x0 = blockIdx.x * blockDim.x * twidth + threadIdx.x;
const int y0 = blockIdx.y * blockDim.y * theight + threadIdx.y;
const int tid = threadIdx.y * blockDim.x + threadIdx.x;
const int bid = blockIdx.y * gridDim.x + blockIdx.x;
work_type mymin = numeric_limits<work_type>::max();
work_type mymax = -numeric_limits<work_type>::max();
unsigned int myminloc = 0;
unsigned int mymaxloc = 0;
for (int i = 0, y = y0; i < theight && y < src.rows; ++i, y += blockDim.y)
{
const T* ptr = src.ptr(y);
for (int j = 0, x = x0; j < twidth && x < src.cols; ++j, x += blockDim.x)
{
if (mask(y, x))
{
const work_type srcVal = ptr[x];
if (srcVal < mymin)
{
mymin = srcVal;
myminloc = y * src.cols + x;
}
if (srcVal > mymax)
{
mymax = srcVal;
mymaxloc = y * src.cols + x;
}
}
}
}
reduceKeyVal<BLOCK_SIZE>(smem_tuple(sminval, smaxval), thrust::tie(mymin, mymax),
smem_tuple(sminloc, smaxloc), thrust::tie(myminloc, mymaxloc),
tid,
thrust::make_tuple(less<work_type>(), greater<work_type>()));
if (tid == 0)
{
minval[bid] = (T) mymin;
maxval[bid] = (T) mymax;
minloc[bid] = myminloc;
maxloc[bid] = mymaxloc;
}
}
template <int BLOCK_SIZE, typename T>
__global__ void kernel_pass_2(T* minval, T* maxval, unsigned int* minloc, unsigned int* maxloc, int count)
{
typedef typename MinMaxTypeTraits<T>::best_type work_type;
__shared__ work_type sminval[BLOCK_SIZE];
__shared__ work_type smaxval[BLOCK_SIZE];
__shared__ unsigned int sminloc[BLOCK_SIZE];
__shared__ unsigned int smaxloc[BLOCK_SIZE];
unsigned int idx = ::min(threadIdx.x, count - 1);
work_type mymin = minval[idx];
work_type mymax = maxval[idx];
unsigned int myminloc = minloc[idx];
unsigned int mymaxloc = maxloc[idx];
reduceKeyVal<BLOCK_SIZE>(smem_tuple(sminval, smaxval), thrust::tie(mymin, mymax),
smem_tuple(sminloc, smaxloc), thrust::tie(myminloc, mymaxloc),
threadIdx.x,
thrust::make_tuple(less<work_type>(), greater<work_type>()));
if (threadIdx.x == 0)
{
minval[0] = (T) mymin;
maxval[0] = (T) mymax;
minloc[0] = myminloc;
maxloc[0] = mymaxloc;
}
}
const int threads_x = 32;
const int threads_y = 8;
void getLaunchCfg(int cols, int rows, dim3& block, dim3& grid)
{
block = dim3(threads_x, threads_y);
grid = dim3(divUp(cols, block.x * block.y),
divUp(rows, block.y * block.x));
grid.x = ::min(grid.x, block.x);
grid.y = ::min(grid.y, block.y);
}
void getBufSize(int cols, int rows, size_t elem_size, int& b1cols, int& b1rows, int& b2cols, int& b2rows)
{
dim3 block, grid;
getLaunchCfg(cols, rows, block, grid);
// For values
b1cols = (int)(grid.x * grid.y * elem_size);
b1rows = 2;
// For locations
b2cols = grid.x * grid.y * sizeof(int);
b2rows = 2;
}
template <typename T>
void run(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf)
{
dim3 block, grid;
getLaunchCfg(src.cols, src.rows, block, grid);
const int twidth = divUp(divUp(src.cols, grid.x), block.x);
const int theight = divUp(divUp(src.rows, grid.y), block.y);
T* minval_buf = (T*) valbuf.ptr(0);
T* maxval_buf = (T*) valbuf.ptr(1);
unsigned int* minloc_buf = locbuf.ptr(0);
unsigned int* maxloc_buf = locbuf.ptr(1);
if (mask.data)
kernel_pass_1<threads_x * threads_y><<<grid, block>>>((PtrStepSz<T>) src, SingleMask(mask), minval_buf, maxval_buf, minloc_buf, maxloc_buf, twidth, theight);
else
kernel_pass_1<threads_x * threads_y><<<grid, block>>>((PtrStepSz<T>) src, WithOutMask(), minval_buf, maxval_buf, minloc_buf, maxloc_buf, twidth, theight);
cudaSafeCall( cudaGetLastError() );
kernel_pass_2<threads_x * threads_y><<<1, threads_x * threads_y>>>(minval_buf, maxval_buf, minloc_buf, maxloc_buf, grid.x * grid.y);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaDeviceSynchronize() );
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(unsigned int), cudaMemcpyDeviceToHost) );
cudaSafeCall( cudaMemcpy(&maxloc_, maxloc_buf, sizeof(unsigned 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 run<unsigned char >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf);
template void run<signed char >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf);
template void run<unsigned short>(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf);
template void run<short >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf);
template void run<int >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf);
template void run<float >(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf);
template void run<double>(const PtrStepSzb src, const PtrStepb mask, double* minval, double* maxval, int* minloc, int* maxloc, PtrStepb valbuf, PtrStep<unsigned int> locbuf);
}
#endif // CUDA_DISABLER

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/simd_functions.hpp"
#include "arithm_func_traits.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace arithm
{
struct Mul_8uc4_32f : binary_function<uint, float, uint>
{
__device__ __forceinline__ uint operator ()(uint a, float b) const
{
uint res = 0;
res |= (saturate_cast<uchar>((0xffu & (a )) * b) );
res |= (saturate_cast<uchar>((0xffu & (a >> 8)) * b) << 8);
res |= (saturate_cast<uchar>((0xffu & (a >> 16)) * b) << 16);
res |= (saturate_cast<uchar>((0xffu & (a >> 24)) * b) << 24);
return res;
}
__device__ __forceinline__ Mul_8uc4_32f() {}
__device__ __forceinline__ Mul_8uc4_32f(const Mul_8uc4_32f& other) {}
};
struct Mul_16sc4_32f : binary_function<short4, float, short4>
{
__device__ __forceinline__ short4 operator ()(short4 a, float b) const
{
return make_short4(saturate_cast<short>(a.x * b), saturate_cast<short>(a.y * b),
saturate_cast<short>(a.z * b), saturate_cast<short>(a.w * b));
}
__device__ __forceinline__ Mul_16sc4_32f() {}
__device__ __forceinline__ Mul_16sc4_32f(const Mul_16sc4_32f& other) {}
};
template <typename T, typename D> struct Mul : binary_function<T, T, D>
{
__device__ __forceinline__ D operator ()(T a, T b) const
{
return saturate_cast<D>(a * b);
}
__device__ __forceinline__ Mul() {}
__device__ __forceinline__ Mul(const Mul& other) {}
};
template <typename T, typename S, typename D> struct MulScale : binary_function<T, T, D>
{
S scale;
explicit MulScale(S scale_) : scale(scale_) {}
__device__ __forceinline__ D operator ()(T a, T b) const
{
return saturate_cast<D>(scale * a * b);
}
};
}
namespace cv { namespace gpu { namespace cudev
{
template <> struct TransformFunctorTraits<arithm::Mul_8uc4_32f> : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
{
};
template <typename T, typename D> struct TransformFunctorTraits< arithm::Mul<T, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
{
};
template <typename T, typename S, typename D> struct TransformFunctorTraits< arithm::MulScale<T, S, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
{
};
}}}
namespace arithm
{
void mulMat_8uc4_32f(PtrStepSz<uint> src1, PtrStepSzf src2, PtrStepSz<uint> dst, cudaStream_t stream)
{
cudev::transform(src1, src2, dst, Mul_8uc4_32f(), WithOutMask(), stream);
}
void mulMat_16sc4_32f(PtrStepSz<short4> src1, PtrStepSzf src2, PtrStepSz<short4> dst, cudaStream_t stream)
{
cudev::transform(src1, src2, dst, Mul_16sc4_32f(), WithOutMask(), stream);
}
template <typename T, typename S, typename D>
void mulMat(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream)
{
if (scale == 1)
{
Mul<T, D> op;
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
}
else
{
MulScale<T, S, D> op(static_cast<S>(scale));
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
}
}
template void mulMat<uchar, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<uchar, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<uchar, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<uchar, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<uchar, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<uchar, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<uchar, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<schar, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<schar, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<schar, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<schar, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<schar, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<schar, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<schar, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void mulMat<ushort, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void mulMat<ushort, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<ushort, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<ushort, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<ushort, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<ushort, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<ushort, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void mulMat<short, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void mulMat<short, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<short, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<short, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<short, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<short, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<short, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void mulMat<int, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void mulMat<int, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void mulMat<int, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void mulMat<int, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<int, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<int, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<int, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void mulMat<float, float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void mulMat<float, float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void mulMat<float, float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void mulMat<float, float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void mulMat<float, float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<float, float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<float, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void mulMat<double, double, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void mulMat<double, double, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void mulMat<double, double, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void mulMat<double, double, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void mulMat<double, double, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
//template void mulMat<double, double, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
template void mulMat<double, double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, double scale, cudaStream_t stream);
}
#endif // CUDA_DISABLER

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/simd_functions.hpp"
#include "arithm_func_traits.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace arithm
{
template <typename T, typename S, typename D> struct MulScalar : unary_function<T, D>
{
S val;
explicit MulScalar(S val_) : val(val_) {}
__device__ __forceinline__ D operator ()(T a) const
{
return saturate_cast<D>(a * val);
}
};
}
namespace cv { namespace gpu { namespace cudev
{
template <typename T, typename S, typename D> struct TransformFunctorTraits< arithm::MulScalar<T, S, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
{
};
}}}
namespace arithm
{
template <typename T, typename S, typename D>
void mulScalar(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream)
{
MulScalar<T, S, D> op(static_cast<S>(val));
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
}
template void mulScalar<uchar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<uchar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<uchar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<uchar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<uchar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<uchar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<uchar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<schar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<schar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<schar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<schar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<schar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<schar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<schar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void mulScalar<ushort, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void mulScalar<ushort, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<ushort, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<ushort, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<ushort, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<ushort, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<ushort, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void mulScalar<short, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void mulScalar<short, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<short, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<short, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<short, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<short, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<short, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void mulScalar<int, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void mulScalar<int, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void mulScalar<int, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void mulScalar<int, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<int, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<int, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<int, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void mulScalar<float, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void mulScalar<float, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void mulScalar<float, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void mulScalar<float, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void mulScalar<float, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<float, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<float, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void mulScalar<double, double, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void mulScalar<double, double, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void mulScalar<double, double, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void mulScalar<double, double, short>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void mulScalar<double, double, int>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
//template void mulScalar<double, double, float>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
template void mulScalar<double, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, cudaStream_t stream);
}
#endif // CUDA_DISABLER

0
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330
modules/gpuarithm/src/cuda/reduce.cu Normal file
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/vec_traits.hpp"
#include "opencv2/core/cuda/vec_math.hpp"
#include "opencv2/core/cuda/reduce.hpp"
#include "opencv2/core/cuda/limits.hpp"
#include "unroll_detail.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace reduce
{
struct Sum
{
template <typename T>
__device__ __forceinline__ T startValue() const
{
return VecTraits<T>::all(0);
}
template <typename T>
__device__ __forceinline__ T operator ()(T a, T b) const
{
return a + b;
}
template <typename T>
__device__ __forceinline__ T result(T r, double) const
{
return r;
}
__device__ __forceinline__ Sum() {}
__device__ __forceinline__ Sum(const Sum&) {}
};
struct Avg
{
template <typename T>
__device__ __forceinline__ T startValue() const
{
return VecTraits<T>::all(0);
}
template <typename T>
__device__ __forceinline__ T operator ()(T a, T b) const
{
return a + b;
}
template <typename T>
__device__ __forceinline__ typename TypeVec<double, VecTraits<T>::cn>::vec_type result(T r, double sz) const
{
return r / sz;
}
__device__ __forceinline__ Avg() {}
__device__ __forceinline__ Avg(const Avg&) {}
};
struct Min
{
template <typename T>
__device__ __forceinline__ T startValue() const
{
return VecTraits<T>::all(numeric_limits<typename VecTraits<T>::elem_type>::max());
}
template <typename T>
__device__ __forceinline__ T operator ()(T a, T b) const
{
minimum<T> minOp;
return minOp(a, b);
}
template <typename T>
__device__ __forceinline__ T result(T r, double) const
{
return r;
}
__device__ __forceinline__ Min() {}
__device__ __forceinline__ Min(const Min&) {}
};
struct Max
{
template <typename T>
__device__ __forceinline__ T startValue() const
{
return VecTraits<T>::all(-numeric_limits<typename VecTraits<T>::elem_type>::max());
}
template <typename T>
__device__ __forceinline__ T operator ()(T a, T b) const
{
maximum<T> maxOp;
return maxOp(a, b);
}
template <typename T>
__device__ __forceinline__ T result(T r, double) const
{
return r;
}
__device__ __forceinline__ Max() {}
__device__ __forceinline__ Max(const Max&) {}
};
///////////////////////////////////////////////////////////
template <typename T, typename S, typename D, class Op>
__global__ void rowsKernel(const PtrStepSz<T> src, D* dst, const Op op)
{
__shared__ S smem[16 * 16];
const int x = blockIdx.x * 16 + threadIdx.x;
S myVal = op.template startValue<S>();
if (x < src.cols)
{
for (int y = threadIdx.y; y < src.rows; y += 16)
{
S srcVal = src(y, x);
myVal = op(myVal, srcVal);
}
}
smem[threadIdx.x * 16 + threadIdx.y] = myVal;
__syncthreads();
volatile S* srow = smem + threadIdx.y * 16;
myVal = srow[threadIdx.x];
cudev::reduce<16>(srow, myVal, threadIdx.x, op);
if (threadIdx.x == 0)
srow[0] = myVal;
__syncthreads();
if (threadIdx.y == 0 && x < src.cols)
dst[x] = (D) op.result(smem[threadIdx.x * 16], src.rows);
}
template <typename T, typename S, typename D, class Op>
void rowsCaller(PtrStepSz<T> src, D* dst, cudaStream_t stream)
{
const dim3 block(16, 16);
const dim3 grid(divUp(src.cols, block.x));
Op op;
rowsKernel<T, S, D, Op><<<grid, block, 0, stream>>>(src, dst, op);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
template <typename T, typename S, typename D>
void rows(PtrStepSzb src, void* dst, int op, cudaStream_t stream)
{
typedef void (*func_t)(PtrStepSz<T> src, D* dst, cudaStream_t stream);
static const func_t funcs[] =
{
rowsCaller<T, S, D, Sum>,
rowsCaller<T, S, D, Avg>,
rowsCaller<T, S, D, Max>,
rowsCaller<T, S, D, Min>
};
funcs[op]((PtrStepSz<T>) src, (D*) dst, stream);
}
template void rows<unsigned char, int, unsigned char>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
template void rows<unsigned char, int, int>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
template void rows<unsigned char, float, float>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
template void rows<unsigned char, double, double>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
template void rows<unsigned short, int, unsigned short>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
template void rows<unsigned short, int, int>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
template void rows<unsigned short, float, float>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
template void rows<unsigned short, double, double>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
template void rows<short, int, short>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
template void rows<short, int, int>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
template void rows<short, float, float>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
template void rows<short, double, double>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
template void rows<int, int, int>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
template void rows<int, float, float>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
template void rows<int, double, double>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
template void rows<float, float, float>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
template void rows<float, double, double>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
template void rows<double, double, double>(PtrStepSzb src, void* dst, int op, cudaStream_t stream);
///////////////////////////////////////////////////////////
template <int BLOCK_SIZE, typename T, typename S, typename D, int cn, class Op>
__global__ void colsKernel(const PtrStepSz<typename TypeVec<T, cn>::vec_type> src, typename TypeVec<D, cn>::vec_type* dst, const Op op)
{
typedef typename TypeVec<T, cn>::vec_type src_type;
typedef typename TypeVec<S, cn>::vec_type work_type;
typedef typename TypeVec<D, cn>::vec_type dst_type;
__shared__ S smem[BLOCK_SIZE * cn];
const int y = blockIdx.x;
const src_type* srcRow = src.ptr(y);
work_type myVal = op.template startValue<work_type>();
for (int x = threadIdx.x; x < src.cols; x += BLOCK_SIZE)
myVal = op(myVal, saturate_cast<work_type>(srcRow[x]));
cudev::reduce<BLOCK_SIZE>(detail::Unroll<cn>::template smem_tuple<BLOCK_SIZE>(smem), detail::Unroll<cn>::tie(myVal), threadIdx.x, detail::Unroll<cn>::op(op));
if (threadIdx.x == 0)
dst[y] = saturate_cast<dst_type>(op.result(myVal, src.cols));
}
template <typename T, typename S, typename D, int cn, class Op> void colsCaller(PtrStepSzb src, void* dst, cudaStream_t stream)
{
const int BLOCK_SIZE = 256;
const dim3 block(BLOCK_SIZE);
const dim3 grid(src.rows);
Op op;
colsKernel<BLOCK_SIZE, T, S, D, cn, Op><<<grid, block, 0, stream>>>((PtrStepSz<typename TypeVec<T, cn>::vec_type>) src, (typename TypeVec<D, cn>::vec_type*) dst, op);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
template <typename T, typename S, typename D> void cols(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream)
{
typedef void (*func_t)(PtrStepSzb src, void* dst, cudaStream_t stream);
static const func_t funcs[5][4] =
{
{0,0,0,0},
{colsCaller<T, S, D, 1, Sum>, colsCaller<T, S, D, 1, Avg>, colsCaller<T, S, D, 1, Max>, colsCaller<T, S, D, 1, Min>},
{colsCaller<T, S, D, 2, Sum>, colsCaller<T, S, D, 2, Avg>, colsCaller<T, S, D, 2, Max>, colsCaller<T, S, D, 2, Min>},
{colsCaller<T, S, D, 3, Sum>, colsCaller<T, S, D, 3, Avg>, colsCaller<T, S, D, 3, Max>, colsCaller<T, S, D, 3, Min>},
{colsCaller<T, S, D, 4, Sum>, colsCaller<T, S, D, 4, Avg>, colsCaller<T, S, D, 4, Max>, colsCaller<T, S, D, 4, Min>},
};
funcs[cn][op](src, dst, stream);
}
template void cols<unsigned char, int, unsigned char>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
template void cols<unsigned char, int, int>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
template void cols<unsigned char, float, float>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
template void cols<unsigned char, double, double>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
template void cols<unsigned short, int, unsigned short>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
template void cols<unsigned short, int, int>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
template void cols<unsigned short, float, float>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
template void cols<unsigned short, double, double>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
template void cols<short, int, short>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
template void cols<short, int, int>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
template void cols<short, float, float>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
template void cols<short, double, double>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
template void cols<int, int, int>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
template void cols<int, float, float>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
template void cols<int, double, double>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
template void cols<float, float, float>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
template void cols<float, double, double>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
template void cols<double, double, double>(PtrStepSzb src, void* dst, int cn, int op, cudaStream_t stream);
}
#endif /* CUDA_DISABLER */

0
modules/gpu/src/cuda/split_merge.cu → modules/gpuarithm/src/cuda/split_merge.cu
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185
modules/gpuarithm/src/cuda/sub_mat.cu Normal file
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@ -0,0 +1,185 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/simd_functions.hpp"
#include "arithm_func_traits.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace arithm
{
struct VSub4 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vsub4(a, b);
}
__device__ __forceinline__ VSub4() {}
__device__ __forceinline__ VSub4(const VSub4& other) {}
};
struct VSub2 : binary_function<uint, uint, uint>
{
__device__ __forceinline__ uint operator ()(uint a, uint b) const
{
return vsub2(a, b);
}
__device__ __forceinline__ VSub2() {}
__device__ __forceinline__ VSub2(const VSub2& other) {}
};
template <typename T, typename D> struct SubMat : binary_function<T, T, D>
{
__device__ __forceinline__ D operator ()(T a, T b) const
{
return saturate_cast<D>(a - b);
}
__device__ __forceinline__ SubMat() {}
__device__ __forceinline__ SubMat(const SubMat& other) {}
};
}
namespace cv { namespace gpu { namespace cudev
{
template <> struct TransformFunctorTraits< arithm::VSub4 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
{
};
template <> struct TransformFunctorTraits< arithm::VSub2 > : arithm::ArithmFuncTraits<sizeof(uint), sizeof(uint)>
{
};
template <typename T, typename D> struct TransformFunctorTraits< arithm::SubMat<T, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
{
};
}}}
namespace arithm
{
void subMat_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
{
cudev::transform(src1, src2, dst, VSub4(), WithOutMask(), stream);
}
void subMat_v2(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream)
{
cudev::transform(src1, src2, dst, VSub2(), WithOutMask(), stream);
}
template <typename T, typename D>
void subMat(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream)
{
if (mask.data)
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<D>) dst, SubMat<T, D>(), mask, stream);
else
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<T>) src2, (PtrStepSz<D>) dst, SubMat<T, D>(), WithOutMask(), stream);
}
template void subMat<uchar, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<uchar, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<uchar, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<uchar, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<uchar, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<uchar, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<uchar, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<schar, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<schar, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<schar, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<schar, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<schar, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<schar, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<schar, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subMat<ushort, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subMat<ushort, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<ushort, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<ushort, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<ushort, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<ushort, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<ushort, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subMat<short, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subMat<short, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<short, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<short, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<short, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<short, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<short, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subMat<int, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subMat<int, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subMat<int, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subMat<int, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<int, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<int, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<int, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subMat<float, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subMat<float, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subMat<float, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subMat<float, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subMat<float, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<float, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<float, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subMat<double, uchar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subMat<double, schar>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subMat<double, ushort>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subMat<double, short>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subMat<double, int>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subMat<double, float>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subMat<double, double>(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
}
#endif // CUDA_DISABLER

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modules/gpuarithm/src/cuda/sub_scalar.cu Normal file
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/simd_functions.hpp"
#include "arithm_func_traits.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace arithm
{
template <typename T, typename S, typename D> struct SubScalar : unary_function<T, D>
{
S val;
explicit SubScalar(S val_) : val(val_) {}
__device__ __forceinline__ D operator ()(T a) const
{
return saturate_cast<D>(a - val);
}
};
}
namespace cv { namespace gpu { namespace cudev
{
template <typename T, typename S, typename D> struct TransformFunctorTraits< arithm::SubScalar<T, S, D> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(D)>
{
};
}}}
namespace arithm
{
template <typename T, typename S, typename D>
void subScalar(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream)
{
SubScalar<T, S, D> op(static_cast<S>(val));
if (mask.data)
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<D>) dst, op, mask, stream);
else
cudev::transform((PtrStepSz<T>) src1, (PtrStepSz<D>) dst, op, WithOutMask(), stream);
}
template void subScalar<uchar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<uchar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<uchar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<uchar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<uchar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<uchar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<uchar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<schar, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<schar, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<schar, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<schar, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<schar, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<schar, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<schar, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subScalar<ushort, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subScalar<ushort, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<ushort, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<ushort, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<ushort, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<ushort, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<ushort, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subScalar<short, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subScalar<short, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<short, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<short, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<short, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<short, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<short, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subScalar<int, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subScalar<int, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subScalar<int, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subScalar<int, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<int, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<int, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<int, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subScalar<float, float, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subScalar<float, float, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subScalar<float, float, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subScalar<float, float, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subScalar<float, float, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<float, float, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<float, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subScalar<double, double, uchar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subScalar<double, double, schar>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subScalar<double, double, ushort>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subScalar<double, double, short>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subScalar<double, double, int>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
//template void subScalar<double, double, float>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
template void subScalar<double, double, double>(PtrStepSzb src1, double val, PtrStepSzb dst, PtrStepb mask, cudaStream_t stream);
}
#endif // CUDA_DISABLER

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/vec_traits.hpp"
#include "opencv2/core/cuda/vec_math.hpp"
#include "opencv2/core/cuda/reduce.hpp"
#include "opencv2/core/cuda/emulation.hpp"
#include "opencv2/core/cuda/utility.hpp"
#include "unroll_detail.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace sum
{
__device__ unsigned int blocks_finished = 0;
template <typename R, int cn> struct AtomicAdd;
template <typename R> struct AtomicAdd<R, 1>
{
static __device__ void run(R* ptr, R val)
{
Emulation::glob::atomicAdd(ptr, val);
}
};
template <typename R> struct AtomicAdd<R, 2>
{
typedef typename TypeVec<R, 2>::vec_type val_type;
static __device__ void run(R* ptr, val_type val)
{
Emulation::glob::atomicAdd(ptr, val.x);
Emulation::glob::atomicAdd(ptr + 1, val.y);
}
};
template <typename R> struct AtomicAdd<R, 3>
{
typedef typename TypeVec<R, 3>::vec_type val_type;
static __device__ void run(R* ptr, val_type val)
{
Emulation::glob::atomicAdd(ptr, val.x);
Emulation::glob::atomicAdd(ptr + 1, val.y);
Emulation::glob::atomicAdd(ptr + 2, val.z);
}
};
template <typename R> struct AtomicAdd<R, 4>
{
typedef typename TypeVec<R, 4>::vec_type val_type;
static __device__ void run(R* ptr, val_type val)
{
Emulation::glob::atomicAdd(ptr, val.x);
Emulation::glob::atomicAdd(ptr + 1, val.y);
Emulation::glob::atomicAdd(ptr + 2, val.z);
Emulation::glob::atomicAdd(ptr + 3, val.w);
}
};
template <int BLOCK_SIZE, typename R, int cn>
struct GlobalReduce
{
typedef typename TypeVec<R, cn>::vec_type result_type;
static __device__ void run(result_type& sum, result_type* result, int tid, int bid, R* smem)
{
#if __CUDA_ARCH__ >= 200
if (tid == 0)
AtomicAdd<R, cn>::run((R*) result, sum);
#else
__shared__ bool is_last;
if (tid == 0)
{
result[bid] = sum;
__threadfence();
unsigned int ticket = ::atomicAdd(&blocks_finished, 1);
is_last = (ticket == gridDim.x * gridDim.y - 1);
}
__syncthreads();
if (is_last)
{
sum = tid < gridDim.x * gridDim.y ? result[tid] : VecTraits<result_type>::all(0);
cudev::reduce<BLOCK_SIZE>(detail::Unroll<cn>::template smem_tuple<BLOCK_SIZE>(smem), detail::Unroll<cn>::tie(sum), tid, detail::Unroll<cn>::op(plus<R>()));
if (tid == 0)
{
result[0] = sum;
blocks_finished = 0;
}
}
#endif
}
};
template <int BLOCK_SIZE, typename src_type, typename result_type, class Mask, class Op>
__global__ void kernel(const PtrStepSz<src_type> src, result_type* result, const Mask mask, const Op op, const int twidth, const int theight)
{
typedef typename VecTraits<src_type>::elem_type T;
typedef typename VecTraits<result_type>::elem_type R;
const int cn = VecTraits<src_type>::cn;
__shared__ R smem[BLOCK_SIZE * cn];
const int x0 = blockIdx.x * blockDim.x * twidth + threadIdx.x;
const int y0 = blockIdx.y * blockDim.y * theight + threadIdx.y;
const int tid = threadIdx.y * blockDim.x + threadIdx.x;
const int bid = blockIdx.y * gridDim.x + blockIdx.x;
result_type sum = VecTraits<result_type>::all(0);
for (int i = 0, y = y0; i < theight && y < src.rows; ++i, y += blockDim.y)
{
const src_type* ptr = src.ptr(y);
for (int j = 0, x = x0; j < twidth && x < src.cols; ++j, x += blockDim.x)
{
if (mask(y, x))
{
const src_type srcVal = ptr[x];
sum = sum + op(saturate_cast<result_type>(srcVal));
}
}
}
cudev::reduce<BLOCK_SIZE>(detail::Unroll<cn>::template smem_tuple<BLOCK_SIZE>(smem), detail::Unroll<cn>::tie(sum), tid, detail::Unroll<cn>::op(plus<R>()));
GlobalReduce<BLOCK_SIZE, R, cn>::run(sum, result, tid, bid, smem);
}
const int threads_x = 32;
const int threads_y = 8;
void getLaunchCfg(int cols, int rows, dim3& block, dim3& grid)
{
block = dim3(threads_x, threads_y);
grid = dim3(divUp(cols, block.x * block.y),
divUp(rows, block.y * block.x));
grid.x = ::min(grid.x, block.x);
grid.y = ::min(grid.y, block.y);
}
void getBufSize(int cols, int rows, int cn, int& bufcols, int& bufrows)
{
dim3 block, grid;
getLaunchCfg(cols, rows, block, grid);
bufcols = grid.x * grid.y * sizeof(double) * cn;
bufrows = 1;
}
template <typename T, typename R, int cn, template <typename> class Op>
void caller(PtrStepSzb src_, void* buf_, double* out, PtrStepSzb mask)
{
typedef typename TypeVec<T, cn>::vec_type src_type;
typedef typename TypeVec<R, cn>::vec_type result_type;
PtrStepSz<src_type> src(src_);
result_type* buf = (result_type*) buf_;
dim3 block, grid;
getLaunchCfg(src.cols, src.rows, block, grid);
const int twidth = divUp(divUp(src.cols, grid.x), block.x);
const int theight = divUp(divUp(src.rows, grid.y), block.y);
Op<result_type> op;
if (mask.data)
kernel<threads_x * threads_y><<<grid, block>>>(src, buf, SingleMask(mask), op, twidth, theight);
else
kernel<threads_x * threads_y><<<grid, block>>>(src, buf, WithOutMask(), op, twidth, theight);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaDeviceSynchronize() );
R result[4] = {0, 0, 0, 0};
cudaSafeCall( cudaMemcpy(&result, buf, sizeof(result_type), cudaMemcpyDeviceToHost) );
out[0] = result[0];
out[1] = result[1];
out[2] = result[2];
out[3] = result[3];
}
template <typename T> struct SumType;
template <> struct SumType<uchar> { typedef unsigned int R; };
template <> struct SumType<schar> { typedef int R; };
template <> struct SumType<ushort> { typedef unsigned int R; };
template <> struct SumType<short> { typedef int R; };
template <> struct SumType<int> { typedef int R; };
template <> struct SumType<float> { typedef float R; };
template <> struct SumType<double> { typedef double R; };
template <typename T, int cn>
void run(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask)
{
typedef typename SumType<T>::R R;
caller<T, R, cn, identity>(src, buf, out, mask);
}
template void run<uchar, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<uchar, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<uchar, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<uchar, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<schar, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<schar, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<schar, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<schar, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<ushort, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<ushort, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<ushort, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<ushort, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<short, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<short, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<short, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<short, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<int, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<int, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<int, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<int, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<float, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<float, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<float, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<float, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<double, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<double, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<double, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void run<double, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template <typename T, int cn>
void runAbs(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask)
{
typedef typename SumType<T>::R R;
caller<T, R, cn, abs_func>(src, buf, out, mask);
}
template void runAbs<uchar, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<uchar, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<uchar, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<uchar, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<schar, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<schar, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<schar, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<schar, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<ushort, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<ushort, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<ushort, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<ushort, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<short, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<short, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<short, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<short, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<int, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<int, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<int, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<int, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<float, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<float, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<float, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<float, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<double, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<double, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<double, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runAbs<double, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template <typename T> struct Sqr : unary_function<T, T>
{
__device__ __forceinline__ T operator ()(T x) const
{
return x * x;
}
};
template <typename T, int cn>
void runSqr(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask)
{
caller<T, double, cn, Sqr>(src, buf, out, mask);
}
template void runSqr<uchar, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<uchar, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<uchar, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<uchar, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<schar, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<schar, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<schar, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<schar, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<ushort, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<ushort, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<ushort, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<ushort, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<short, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<short, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<short, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<short, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<int, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<int, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<int, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<int, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<float, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<float, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<float, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<float, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<double, 1>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<double, 2>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<double, 3>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
template void runSqr<double, 4>(PtrStepSzb src, void* buf, double* out, PtrStepSzb mask);
}
#endif // CUDA_DISABLER

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/simd_functions.hpp"
#include "arithm_func_traits.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace cv { namespace gpu { namespace cudev
{
template <typename T> struct TransformFunctorTraits< thresh_binary_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
template <typename T> struct TransformFunctorTraits< thresh_binary_inv_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
template <typename T> struct TransformFunctorTraits< thresh_trunc_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
template <typename T> struct TransformFunctorTraits< thresh_to_zero_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
template <typename T> struct TransformFunctorTraits< thresh_to_zero_inv_func<T> > : arithm::ArithmFuncTraits<sizeof(T), sizeof(T)>
{
};
}}}
namespace arithm
{
template <template <typename> class Op, typename T>
void threshold_caller(PtrStepSz<T> src, PtrStepSz<T> dst, T thresh, T maxVal, cudaStream_t stream)
{
Op<T> op(thresh, maxVal);
cudev::transform(src, dst, op, WithOutMask(), stream);
}
template <typename T>
void threshold(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream)
{
typedef void (*caller_t)(PtrStepSz<T> src, PtrStepSz<T> dst, T thresh, T maxVal, cudaStream_t stream);
static const caller_t callers[] =
{
threshold_caller<thresh_binary_func, T>,
threshold_caller<thresh_binary_inv_func, T>,
threshold_caller<thresh_trunc_func, T>,
threshold_caller<thresh_to_zero_func, T>,
threshold_caller<thresh_to_zero_inv_func, T>
};
callers[type]((PtrStepSz<T>) src, (PtrStepSz<T>) dst, static_cast<T>(thresh), static_cast<T>(maxVal), stream);
}
template void threshold<uchar>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
template void threshold<schar>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
template void threshold<ushort>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
template void threshold<short>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
template void threshold<int>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
template void threshold<float>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
template void threshold<double>(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
}
#endif // CUDA_DISABLER

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace arithm
{
const int TRANSPOSE_TILE_DIM = 16;
const int TRANSPOSE_BLOCK_ROWS = 16;
template <typename T>
__global__ void transposeKernel(const PtrStepSz<T> src, PtrStep<T> dst)
{
__shared__ T tile[TRANSPOSE_TILE_DIM][TRANSPOSE_TILE_DIM + 1];
int blockIdx_x, blockIdx_y;
// do diagonal reordering
if (gridDim.x == gridDim.y)
{
blockIdx_y = blockIdx.x;
blockIdx_x = (blockIdx.x + blockIdx.y) % gridDim.x;
}
else
{
int bid = blockIdx.x + gridDim.x * blockIdx.y;
blockIdx_y = bid % gridDim.y;
blockIdx_x = ((bid / gridDim.y) + blockIdx_y) % gridDim.x;
}
int xIndex = blockIdx_x * TRANSPOSE_TILE_DIM + threadIdx.x;
int yIndex = blockIdx_y * TRANSPOSE_TILE_DIM + threadIdx.y;
if (xIndex < src.cols)
{
for (int i = 0; i < TRANSPOSE_TILE_DIM; i += TRANSPOSE_BLOCK_ROWS)
{
if (yIndex + i < src.rows)
{
tile[threadIdx.y + i][threadIdx.x] = src(yIndex + i, xIndex);
}
}
}
__syncthreads();
xIndex = blockIdx_y * TRANSPOSE_TILE_DIM + threadIdx.x;
yIndex = blockIdx_x * TRANSPOSE_TILE_DIM + threadIdx.y;
if (xIndex < src.rows)
{
for (int i = 0; i < TRANSPOSE_TILE_DIM; i += TRANSPOSE_BLOCK_ROWS)
{
if (yIndex + i < src.cols)
{
dst(yIndex + i, xIndex) = tile[threadIdx.x][threadIdx.y + i];
}
}
}
}
template <typename T> void transpose(PtrStepSz<T> src, PtrStepSz<T> dst, cudaStream_t stream)
{
const dim3 block(TRANSPOSE_TILE_DIM, TRANSPOSE_TILE_DIM);
const dim3 grid(divUp(src.cols, block.x), divUp(src.rows, block.y));
transposeKernel<<<grid, block, 0, stream>>>(src, dst);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
template void transpose<int>(PtrStepSz<int> src, PtrStepSz<int> dst, cudaStream_t stream);
template void transpose<double>(PtrStepSz<double> src, PtrStepSz<double> dst, cudaStream_t stream);
}
#endif // CUDA_DISABLER

135
modules/gpuarithm/src/cuda/unroll_detail.hpp Normal file
View File

@ -0,0 +1,135 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __UNROLL_DETAIL_HPP__
#define __UNROLL_DETAIL_HPP__
#include <thrust/tuple.h>
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/vec_traits.hpp"
namespace detail
{
template <int cn> struct Unroll;
template <> struct Unroll<1>
{
template <int BLOCK_SIZE, typename R>
static __device__ __forceinline__ volatile R* smem_tuple(R* smem)
{
return smem;
}
template <typename R>
static __device__ __forceinline__ R& tie(R& val)
{
return val;
}
template <class Op>
static __device__ __forceinline__ const Op& op(const Op& op)
{
return op;
}
};
template <> struct Unroll<2>
{
template <int BLOCK_SIZE, typename R>
static __device__ __forceinline__ thrust::tuple<volatile R*, volatile R*> smem_tuple(R* smem)
{
return cv::gpu::cudev::smem_tuple(smem, smem + BLOCK_SIZE);
}
template <typename R>
static __device__ __forceinline__ thrust::tuple<typename cv::gpu::cudev::VecTraits<R>::elem_type&, typename cv::gpu::cudev::VecTraits<R>::elem_type&> tie(R& val)
{
return thrust::tie(val.x, val.y);
}
template <class Op>
static __device__ __forceinline__ const thrust::tuple<Op, Op> op(const Op& op)
{
return thrust::make_tuple(op, op);
}
};
template <> struct Unroll<3>
{
template <int BLOCK_SIZE, typename R>
static __device__ __forceinline__ thrust::tuple<volatile R*, volatile R*, volatile R*> smem_tuple(R* smem)
{
return cv::gpu::cudev::smem_tuple(smem, smem + BLOCK_SIZE, smem + 2 * BLOCK_SIZE);
}
template <typename R>
static __device__ __forceinline__ thrust::tuple<typename cv::gpu::cudev::VecTraits<R>::elem_type&, typename cv::gpu::cudev::VecTraits<R>::elem_type&, typename cv::gpu::cudev::VecTraits<R>::elem_type&> tie(R& val)
{
return thrust::tie(val.x, val.y, val.z);
}
template <class Op>
static __device__ __forceinline__ const thrust::tuple<Op, Op, Op> op(const Op& op)
{
return thrust::make_tuple(op, op, op);
}
};
template <> struct Unroll<4>
{
template <int BLOCK_SIZE, typename R>
static __device__ __forceinline__ thrust::tuple<volatile R*, volatile R*, volatile R*, volatile R*> smem_tuple(R* smem)
{
return cv::gpu::cudev::smem_tuple(smem, smem + BLOCK_SIZE, smem + 2 * BLOCK_SIZE, smem + 3 * BLOCK_SIZE);
}
template <typename R>
static __device__ __forceinline__ thrust::tuple<typename cv::gpu::cudev::VecTraits<R>::elem_type&, typename cv::gpu::cudev::VecTraits<R>::elem_type&, typename cv::gpu::cudev::VecTraits<R>::elem_type&, typename cv::gpu::cudev::VecTraits<R>::elem_type&> tie(R& val)
{
return thrust::tie(val.x, val.y, val.z, val.w);
}
template <class Op>
static __device__ __forceinline__ const thrust::tuple<Op, Op, Op, Op> op(const Op& op)
{
return thrust::make_tuple(op, op, op, op);
}
};
}
#endif // __UNROLL_DETAIL_HPP__

218
modules/gpu/src/element_operations.cpp → modules/gpuarithm/src/element_operations.cpp
View File

@ -78,10 +78,9 @@ void cv::gpu::min(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_no_cud
void cv::gpu::min(const GpuMat&, double, GpuMat&, Stream&) { throw_no_cuda(); }
void cv::gpu::max(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_no_cuda(); }
void cv::gpu::max(const GpuMat&, double, GpuMat&, Stream&) { throw_no_cuda(); }
double cv::gpu::threshold(const GpuMat&, GpuMat&, double, double, int, Stream&) {throw_no_cuda(); return 0.0;}
void cv::gpu::pow(const GpuMat&, double, GpuMat&, Stream&) { throw_no_cuda(); }
void cv::gpu::alphaComp(const GpuMat&, const GpuMat&, GpuMat&, int, Stream&) { throw_no_cuda(); }
void cv::gpu::addWeighted(const GpuMat&, double, const GpuMat&, double, double, GpuMat&, int, Stream&) { throw_no_cuda(); }
double cv::gpu::threshold(const GpuMat&, GpuMat&, double, double, int, Stream&) {throw_no_cuda(); return 0.0;}
#else
@ -1793,10 +1792,10 @@ void cv::gpu::exp(const GpuMat& src, GpuMat& dst, Stream& stream)
namespace arithm
{
void cmpMatEq_v4(PtrStepSz<unsigned int> src1, PtrStepSz<unsigned int> src2, PtrStepSz<unsigned int> dst, cudaStream_t stream);
void cmpMatNe_v4(PtrStepSz<unsigned int> src1, PtrStepSz<unsigned int> src2, PtrStepSz<unsigned int> dst, cudaStream_t stream);
void cmpMatLt_v4(PtrStepSz<unsigned int> src1, PtrStepSz<unsigned int> src2, PtrStepSz<unsigned int> dst, cudaStream_t stream);
void cmpMatLe_v4(PtrStepSz<unsigned int> src1, PtrStepSz<unsigned int> src2, PtrStepSz<unsigned int> dst, cudaStream_t stream);
void cmpMatEq_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream);
void cmpMatNe_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream);
void cmpMatLt_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream);
void cmpMatLe_v4(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream);
template <typename T> void cmpMatEq(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
template <typename T> void cmpMatNe(PtrStepSzb src1, PtrStepSzb src2, PtrStepSzb dst, cudaStream_t stream);
@ -1820,7 +1819,7 @@ void cv::gpu::compare(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, int c
{cmpMatEq<double> , cmpMatNe<double> , cmpMatLt<double> , cmpMatLe<double> }
};
typedef void (*func_v4_t)(PtrStepSz<unsigned int> src1, PtrStepSz<unsigned int> src2, PtrStepSz<unsigned int> dst, cudaStream_t stream);
typedef void (*func_v4_t)(PtrStepSz<uint> src1, PtrStepSz<uint> src2, PtrStepSz<uint> dst, cudaStream_t stream);
static const func_v4_t funcs_v4[] =
{
cmpMatEq_v4, cmpMatNe_v4, cmpMatLt_v4, cmpMatLe_v4
@ -2670,72 +2669,6 @@ void cv::gpu::max(const GpuMat& src, double val, GpuMat& dst, Stream& stream)
funcs[depth](src, cast_func[depth](val), dst, StreamAccessor::getStream(stream));
}
////////////////////////////////////////////////////////////////////////
// threshold
namespace arithm
{
template <typename T>
void threshold(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
}
double cv::gpu::threshold(const GpuMat& src, GpuMat& dst, double thresh, double maxVal, int type, Stream& s)
{
const int depth = src.depth();
CV_Assert( src.channels() == 1 && depth <= CV_64F );
CV_Assert( type <= THRESH_TOZERO_INV );
if (depth == CV_64F)
{
if (!deviceSupports(NATIVE_DOUBLE))
CV_Error(cv::Error::StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src.size(), src.type());
cudaStream_t stream = StreamAccessor::getStream(s);
if (src.type() == CV_32FC1 && type == THRESH_TRUNC)
{
NppStreamHandler h(stream);
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
nppSafeCall( nppiThreshold_32f_C1R(src.ptr<Npp32f>(), static_cast<int>(src.step),
dst.ptr<Npp32f>(), static_cast<int>(dst.step), sz, static_cast<Npp32f>(thresh), NPP_CMP_GREATER) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
else
{
typedef void (*func_t)(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
static const func_t funcs[] =
{
arithm::threshold<unsigned char>,
arithm::threshold<signed char>,
arithm::threshold<unsigned short>,
arithm::threshold<short>,
arithm::threshold<int>,
arithm::threshold<float>,
arithm::threshold<double>
};
if (depth != CV_32F && depth != CV_64F)
{
thresh = cvFloor(thresh);
maxVal = cvRound(maxVal);
}
funcs[depth](src, dst, thresh, maxVal, type, stream);
}
return thresh;
}
////////////////////////////////////////////////////////////////////////
// pow
@ -2777,79 +2710,6 @@ void cv::gpu::pow(const GpuMat& src, double power, GpuMat& dst, Stream& stream)
funcs[depth](src_, power, dst_, StreamAccessor::getStream(stream));
}
////////////////////////////////////////////////////////////////////////
// alphaComp
namespace
{
template <int DEPTH> struct NppAlphaCompFunc
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
typedef NppStatus (*func_t)(const npp_t* pSrc1, int nSrc1Step, const npp_t* pSrc2, int nSrc2Step, npp_t* pDst, int nDstStep, NppiSize oSizeROI, NppiAlphaOp eAlphaOp);
};
template <int DEPTH, typename NppAlphaCompFunc<DEPTH>::func_t func> struct NppAlphaComp
{
typedef typename NppTypeTraits<DEPTH>::npp_t npp_t;
static void call(const GpuMat& img1, const GpuMat& img2, GpuMat& dst, NppiAlphaOp eAlphaOp, cudaStream_t stream)
{
NppStreamHandler h(stream);
NppiSize oSizeROI;
oSizeROI.width = img1.cols;
oSizeROI.height = img2.rows;
nppSafeCall( func(img1.ptr<npp_t>(), static_cast<int>(img1.step), img2.ptr<npp_t>(), static_cast<int>(img2.step),
dst.ptr<npp_t>(), static_cast<int>(dst.step), oSizeROI, eAlphaOp) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
}
void cv::gpu::alphaComp(const GpuMat& img1, const GpuMat& img2, GpuMat& dst, int alpha_op, Stream& stream)
{
static const NppiAlphaOp npp_alpha_ops[] = {
NPPI_OP_ALPHA_OVER,
NPPI_OP_ALPHA_IN,
NPPI_OP_ALPHA_OUT,
NPPI_OP_ALPHA_ATOP,
NPPI_OP_ALPHA_XOR,
NPPI_OP_ALPHA_PLUS,
NPPI_OP_ALPHA_OVER_PREMUL,
NPPI_OP_ALPHA_IN_PREMUL,
NPPI_OP_ALPHA_OUT_PREMUL,
NPPI_OP_ALPHA_ATOP_PREMUL,
NPPI_OP_ALPHA_XOR_PREMUL,
NPPI_OP_ALPHA_PLUS_PREMUL,
NPPI_OP_ALPHA_PREMUL
};
typedef void (*func_t)(const GpuMat& img1, const GpuMat& img2, GpuMat& dst, NppiAlphaOp eAlphaOp, cudaStream_t stream);
static const func_t funcs[] =
{
NppAlphaComp<CV_8U, nppiAlphaComp_8u_AC4R>::call,
0,
NppAlphaComp<CV_16U, nppiAlphaComp_16u_AC4R>::call,
0,
NppAlphaComp<CV_32S, nppiAlphaComp_32s_AC4R>::call,
NppAlphaComp<CV_32F, nppiAlphaComp_32f_AC4R>::call
};
CV_Assert( img1.type() == CV_8UC4 || img1.type() == CV_16UC4 || img1.type() == CV_32SC4 || img1.type() == CV_32FC4 );
CV_Assert( img1.size() == img2.size() && img1.type() == img2.type() );
dst.create(img1.size(), img1.type());
const func_t func = funcs[img1.depth()];
func(img1, img2, dst, npp_alpha_ops[alpha_op], StreamAccessor::getStream(stream));
}
////////////////////////////////////////////////////////////////////////
// addWeighted
@ -3357,4 +3217,70 @@ void cv::gpu::addWeighted(const GpuMat& src1, double alpha, const GpuMat& src2,
func(src1_, alpha, src2_, beta, gamma, dst_, StreamAccessor::getStream(stream));
}
////////////////////////////////////////////////////////////////////////
// threshold
namespace arithm
{
template <typename T>
void threshold(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
}
double cv::gpu::threshold(const GpuMat& src, GpuMat& dst, double thresh, double maxVal, int type, Stream& s)
{
const int depth = src.depth();
CV_Assert( src.channels() == 1 && depth <= CV_64F );
CV_Assert( type <= 4/*THRESH_TOZERO_INV*/ );
if (depth == CV_64F)
{
if (!deviceSupports(NATIVE_DOUBLE))
CV_Error(cv::Error::StsUnsupportedFormat, "The device doesn't support double");
}
dst.create(src.size(), src.type());
cudaStream_t stream = StreamAccessor::getStream(s);
if (src.type() == CV_32FC1 && type == 2/*THRESH_TRUNC*/)
{
NppStreamHandler h(stream);
NppiSize sz;
sz.width = src.cols;
sz.height = src.rows;
nppSafeCall( nppiThreshold_32f_C1R(src.ptr<Npp32f>(), static_cast<int>(src.step),
dst.ptr<Npp32f>(), static_cast<int>(dst.step), sz, static_cast<Npp32f>(thresh), NPP_CMP_GREATER) );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
else
{
typedef void (*func_t)(PtrStepSzb src, PtrStepSzb dst, double thresh, double maxVal, int type, cudaStream_t stream);
static const func_t funcs[] =
{
arithm::threshold<unsigned char>,
arithm::threshold<signed char>,
arithm::threshold<unsigned short>,
arithm::threshold<short>,
arithm::threshold<int>,
arithm::threshold<float>,
arithm::threshold<double>
};
if (depth != CV_32F && depth != CV_64F)
{
thresh = cvFloor(thresh);
maxVal = cvRound(maxVal);
}
funcs[depth](src, dst, thresh, maxVal, type, stream);
}
return thresh;
}
#endif

0
modules/gpu/src/matrix_reductions.cpp → modules/gpuarithm/src/matrix_reductions.cpp
View File

43
modules/gpuarithm/src/precomp.cpp Normal file
View File

@ -0,0 +1,43 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"

58
modules/gpuarithm/src/precomp.hpp Normal file
View File

@ -0,0 +1,58 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_PRECOMP_H__
#define __OPENCV_PRECOMP_H__
#include <limits>
#include "opencv2/gpuarithm.hpp"
#include "opencv2/core/utility.hpp"
#include "opencv2/core/core_c.h"
#include "opencv2/core/gpu_private.hpp"
#ifdef HAVE_CUBLAS
#include <cublas.h>
#endif
#endif /* __OPENCV_PRECOMP_H__ */

0
modules/gpu/src/split_merge.cpp → modules/gpuarithm/src/split_merge.cpp
View File

0
modules/gpu/test/test_core.cpp → modules/gpuarithm/test/test_core.cpp
View File

120
modules/gpuarithm/test/test_main.cpp Normal file
View File

@ -0,0 +1,120 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "test_precomp.hpp"
#ifdef HAVE_CUDA
using namespace std;
using namespace cv;
using namespace cv::gpu;
using namespace cvtest;
using namespace testing;
int main(int argc, char** argv)
{
try
{
const std::string keys =
"{ h help ? | | Print help}"
"{ i info | | Print information about system and exit }"
"{ device | -1 | Device on which tests will be executed (-1 means all devices) }"
;
CommandLineParser cmd(argc, (const char**)argv, keys);
if (cmd.has("help"))
{
cmd.printMessage();
return 0;
}
printCudaInfo();
if (cmd.has("info"))
{
return 0;
}
int device = cmd.get<int>("device");
if (device < 0)
{
DeviceManager::instance().loadAll();
cout << "Run tests on all supported devices \n" << endl;
}
else
{
DeviceManager::instance().load(device);
DeviceInfo info(device);
cout << "Run tests on device " << device << " [" << info.name() << "] \n" << endl;
}
TS::ptr()->init("gpu");
InitGoogleTest(&argc, argv);
return RUN_ALL_TESTS();
}
catch (const exception& e)
{
cerr << e.what() << endl;
return -1;
}
catch (...)
{
cerr << "Unknown error" << endl;
return -1;
}
return 0;
}
#else // HAVE_CUDA
int main()
{
printf("OpenCV was built without CUDA support\n");
return 0;
}
#endif // HAVE_CUDA

43
modules/gpuarithm/test/test_precomp.cpp Normal file
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@ -0,0 +1,43 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "test_precomp.hpp"

60
modules/gpuarithm/test/test_precomp.hpp Normal file
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@ -0,0 +1,60 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifdef __GNUC__
# pragma GCC diagnostic ignored "-Wmissing-declarations"
# if defined __clang__ || defined __APPLE__
# pragma GCC diagnostic ignored "-Wmissing-prototypes"
# pragma GCC diagnostic ignored "-Wextra"
# endif
#endif
#ifndef __OPENCV_TEST_PRECOMP_HPP__
#define __OPENCV_TEST_PRECOMP_HPP__
#include "opencv2/ts.hpp"
#include "opencv2/ts/gpu_test.hpp"
#include "opencv2/core.hpp"
#include "opencv2/gpuarithm.hpp"
#endif

2
modules/stitching/CMakeLists.txt
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@ -1,3 +1,3 @@
set(the_description "Images stitching")
ocv_define_module(stitching opencv_imgproc opencv_features2d opencv_calib3d opencv_objdetect OPTIONAL opencv_gpu opencv_nonfree)
ocv_define_module(stitching opencv_imgproc opencv_features2d opencv_calib3d opencv_objdetect OPTIONAL opencv_gpu opencv_gpuarithm opencv_nonfree)

2
modules/superres/CMakeLists.txt
View File

@ -4,4 +4,4 @@ endif()
set(the_description "Super Resolution")
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4127 -Wundef)
ocv_define_module(superres opencv_imgproc opencv_video OPTIONAL opencv_gpu opencv_highgui opencv_gpucodec)
ocv_define_module(superres opencv_imgproc opencv_video OPTIONAL opencv_highgui opencv_gpu opencv_gpucodec opencv_gpuarithm)

1
samples/cpp/CMakeLists.txt
View File

@ -17,6 +17,7 @@ if(BUILD_EXAMPLES AND OCV_DEPENDENCIES_FOUND)
ocv_include_modules(${OPENCV_CPP_SAMPLES_REQUIRED_DEPS})
if(HAVE_opencv_gpu)
ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpuarithm/include")
ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpu/include")
endif()

2
samples/gpu/CMakeLists.txt
View File

@ -2,7 +2,7 @@ SET(OPENCV_GPU_SAMPLES_REQUIRED_DEPS opencv_core opencv_flann opencv_imgproc ope
opencv_ml opencv_video opencv_objdetect opencv_features2d
opencv_calib3d opencv_legacy opencv_contrib opencv_gpu
opencv_nonfree opencv_softcascade opencv_superres
opencv_gpucodec)
opencv_gpucodec opencv_gpuarithm)
ocv_check_dependencies(${OPENCV_GPU_SAMPLES_REQUIRED_DEPS})