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element operations

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This commit is contained in:
Vladislav Vinogradov 2012-11-21 12:46:11 +04:00 committed by Vladislav Vinogradov
parent f00efcfc59
commit 11c6eb6305
4 changed files with 5066 additions and 2972 deletions
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34
modules/gpu/include/opencv2/gpu/device/functional.hpp
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@ -357,6 +357,9 @@ namespace cv { namespace gpu { namespace device
{
return abs(x);
}
__device__ __forceinline__ abs_func() {}
__device__ __forceinline__ abs_func(const abs_func&) {}
};
template <> struct abs_func<unsigned char> : unary_function<unsigned char, unsigned char>
{
@ -364,6 +367,9 @@ namespace cv { namespace gpu { namespace device
{
return x;
}
__device__ __forceinline__ abs_func() {}
__device__ __forceinline__ abs_func(const abs_func&) {}
};
template <> struct abs_func<signed char> : unary_function<signed char, signed char>
{
@ -371,6 +377,9 @@ namespace cv { namespace gpu { namespace device
{
return ::abs(x);
}
__device__ __forceinline__ abs_func() {}
__device__ __forceinline__ abs_func(const abs_func&) {}
};
template <> struct abs_func<char> : unary_function<char, char>
{
@ -378,6 +387,9 @@ namespace cv { namespace gpu { namespace device
{
return ::abs(x);
}
__device__ __forceinline__ abs_func() {}
__device__ __forceinline__ abs_func(const abs_func&) {}
};
template <> struct abs_func<unsigned short> : unary_function<unsigned short, unsigned short>
{
@ -385,6 +397,9 @@ namespace cv { namespace gpu { namespace device
{
return x;
}
__device__ __forceinline__ abs_func() {}
__device__ __forceinline__ abs_func(const abs_func&) {}
};
template <> struct abs_func<short> : unary_function<short, short>
{
@ -392,6 +407,9 @@ namespace cv { namespace gpu { namespace device
{
return ::abs(x);
}
__device__ __forceinline__ abs_func() {}
__device__ __forceinline__ abs_func(const abs_func&) {}
};
template <> struct abs_func<unsigned int> : unary_function<unsigned int, unsigned int>
{
@ -399,6 +417,9 @@ namespace cv { namespace gpu { namespace device
{
return x;
}
__device__ __forceinline__ abs_func() {}
__device__ __forceinline__ abs_func(const abs_func&) {}
};
template <> struct abs_func<int> : unary_function<int, int>
{
@ -406,6 +427,9 @@ namespace cv { namespace gpu { namespace device
{
return ::abs(x);
}
__device__ __forceinline__ abs_func() {}
__device__ __forceinline__ abs_func(const abs_func&) {}
};
template <> struct abs_func<float> : unary_function<float, float>
{
@ -413,6 +437,9 @@ namespace cv { namespace gpu { namespace device
{
return ::fabsf(x);
}
__device__ __forceinline__ abs_func() {}
__device__ __forceinline__ abs_func(const abs_func&) {}
};
template <> struct abs_func<double> : unary_function<double, double>
{
@ -420,6 +447,9 @@ namespace cv { namespace gpu { namespace device
{
return ::fabs(x);
}
__device__ __forceinline__ abs_func() {}
__device__ __forceinline__ abs_func(const abs_func&) {}
};
#define OPENCV_GPU_IMPLEMENT_UN_FUNCTOR(name, func) \
@ -429,6 +459,8 @@ namespace cv { namespace gpu { namespace device
{ \
return func ## f(v); \
} \
__device__ __forceinline__ name ## _func() {} \
__device__ __forceinline__ name ## _func(const name ## _func&) {} \
}; \
template <> struct name ## _func<double> : unary_function<double, double> \
{ \
@ -436,6 +468,8 @@ namespace cv { namespace gpu { namespace device
{ \
return func(v); \
} \
__device__ __forceinline__ name ## _func() {} \
__device__ __forceinline__ name ## _func(const name ## _func&) {} \
};
#define OPENCV_GPU_IMPLEMENT_BIN_FUNCTOR(name, func) \

4366
modules/gpu/src/cuda/element_operations.cu
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3494
modules/gpu/src/element_operations.cpp
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File diff suppressed because it is too large Load Diff

144
modules/gpu/test/test_core.cpp
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@ -210,7 +210,6 @@ TEST_P(Add_Array, Accuracy)
{
cv::Mat mat1 = randomMat(size, stype);
cv::Mat mat2 = randomMat(size, stype);
cv::Mat mask = randomMat(size, CV_8UC1, 0.0, 2.0);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
@ -228,10 +227,10 @@ TEST_P(Add_Array, Accuracy)
{
cv::gpu::GpuMat dst = createMat(size, dtype, useRoi);
dst.setTo(cv::Scalar::all(0));
cv::gpu::add(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst, channels == 1 ? loadMat(mask, useRoi) : cv::gpu::GpuMat(), depth.second);
cv::gpu::add(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst, cv::gpu::GpuMat(), depth.second);
cv::Mat dst_gold(size, dtype, cv::Scalar::all(0));
cv::add(mat1, mat2, dst_gold, channels == 1 ? mask : cv::noArray(), depth.second);
cv::add(mat1, mat2, dst_gold, cv::noArray(), depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-4 : 0.0);
}
@ -244,6 +243,67 @@ INSTANTIATE_TEST_CASE_P(GPU_Core, Add_Array, testing::Combine(
ALL_CHANNELS,
WHOLE_SUBMAT));
PARAM_TEST_CASE(Add_Array_Mask, cv::gpu::DeviceInfo, cv::Size, std::pair<MatDepth, MatDepth>, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
std::pair<MatDepth, MatDepth> depth;
bool useRoi;
int stype;
int dtype;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
stype = CV_MAKE_TYPE(depth.first, 1);
dtype = CV_MAKE_TYPE(depth.second, 1);
}
};
TEST_P(Add_Array_Mask, Accuracy)
{
cv::Mat mat1 = randomMat(size, stype);
cv::Mat mat2 = randomMat(size, stype);
cv::Mat mask = randomMat(size, CV_8UC1, 0, 2);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::add(loadMat(mat1), loadMat(mat2), dst, cv::gpu::GpuMat(), depth.second);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(CV_StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, dtype, useRoi);
dst.setTo(cv::Scalar::all(0));
cv::gpu::add(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst, loadMat(mask, useRoi), depth.second);
cv::Mat dst_gold(size, dtype, cv::Scalar::all(0));
cv::add(mat1, mat2, dst_gold, mask, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-4 : 0.0);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Add_Array_Mask, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
DEPTH_PAIRS,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Add_Scalar
@ -362,6 +422,67 @@ PARAM_TEST_CASE(Subtract_Array, cv::gpu::DeviceInfo, cv::Size, std::pair<MatDept
};
TEST_P(Subtract_Array, Accuracy)
{
cv::Mat mat1 = randomMat(size, stype);
cv::Mat mat2 = randomMat(size, stype);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::subtract(loadMat(mat1), loadMat(mat2), dst, cv::gpu::GpuMat(), depth.second);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(CV_StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, dtype, useRoi);
dst.setTo(cv::Scalar::all(0));
cv::gpu::subtract(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst, cv::gpu::GpuMat(), depth.second);
cv::Mat dst_gold(size, dtype, cv::Scalar::all(0));
cv::subtract(mat1, mat2, dst_gold, cv::noArray(), depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-4 : 0.0);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Subtract_Array, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
DEPTH_PAIRS,
ALL_CHANNELS,
WHOLE_SUBMAT));
PARAM_TEST_CASE(Subtract_Array_Mask, cv::gpu::DeviceInfo, cv::Size, std::pair<MatDepth, MatDepth>, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
std::pair<MatDepth, MatDepth> depth;
bool useRoi;
int stype;
int dtype;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
stype = CV_MAKE_TYPE(depth.first, 1);
dtype = CV_MAKE_TYPE(depth.second, 1);
}
};
TEST_P(Subtract_Array_Mask, Accuracy)
{
cv::Mat mat1 = randomMat(size, stype);
cv::Mat mat2 = randomMat(size, stype);
@ -383,20 +504,19 @@ TEST_P(Subtract_Array, Accuracy)
{
cv::gpu::GpuMat dst = createMat(size, dtype, useRoi);
dst.setTo(cv::Scalar::all(0));
cv::gpu::subtract(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst, channels == 1 ? loadMat(mask, useRoi) : cv::gpu::GpuMat(), depth.second);
cv::gpu::subtract(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst, loadMat(mask, useRoi), depth.second);
cv::Mat dst_gold(size, dtype, cv::Scalar::all(0));
cv::subtract(mat1, mat2, dst_gold, channels == 1 ? mask : cv::noArray(), depth.second);
cv::subtract(mat1, mat2, dst_gold, mask, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-4 : 0.0);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Subtract_Array, testing::Combine(
INSTANTIATE_TEST_CASE_P(GPU_Core, Subtract_Array_Mask, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
DEPTH_PAIRS,
ALL_CHANNELS,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
@ -541,7 +661,7 @@ TEST_P(Multiply_Array, WithOutScale)
cv::Mat dst_gold;
cv::multiply(mat1, mat2, dst_gold, 1, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-4 : 0.0);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-2 : 0.0);
}
}
@ -571,7 +691,7 @@ TEST_P(Multiply_Array, WithScale)
cv::Mat dst_gold;
cv::multiply(mat1, mat2, dst_gold, scale, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, 1.0);
EXPECT_MAT_NEAR(dst_gold, dst, 2.0);
}
}
@ -726,7 +846,7 @@ TEST_P(Multiply_Scalar, WithOutScale)
cv::Mat dst_gold;
cv::multiply(mat, val, dst_gold, 1, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-2 : 0.0);
EXPECT_MAT_NEAR(dst_gold, dst, 1.0);
}
}
@ -757,7 +877,7 @@ TEST_P(Multiply_Scalar, WithScale)
cv::Mat dst_gold;
cv::multiply(mat, val, dst_gold, scale, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-4 : 0.0);
EXPECT_MAT_NEAR(dst_gold, dst, 1.0);
}
}
@ -1037,7 +1157,7 @@ TEST_P(Divide_Scalar, WithScale)
cv::Mat dst_gold;
cv::divide(mat, val, dst_gold, scale, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-4 : 0.0);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-2 : 0.0);
}
}