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Commit e1e5047b authored by Vladislav Vinogradov's avatar Vladislav Vinogradov
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added gpu::LUT for CV_8UC3 type, added gpu::cvtColor for BGR2BGR5x5, minor fix in tests.

parent 1b8c0000
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Showing with 1435 additions and 1359 deletions
modules/gpu/src/arithm.cpp
View file @ e1e5047b
......@@ -266,13 +266,13 @@ double cv::gpu::norm(const GpuMat& src1, const GpuMat& src2, int normType)
sz.height = src1.rows;
int funcIdx = normType >> 1;
Scalar retVal;
double retVal;
nppSafeCall( npp_norm_diff_func[funcIdx](src1.ptr<Npp8u>(), src1.step,
src2.ptr<Npp8u>(), src2.step,
sz, retVal.val) );
sz, &retVal) );
return retVal[0];
return retVal;
}
////////////////////////////////////////////////////////////////////////
......@@ -307,10 +307,7 @@ void cv::gpu::flip(const GpuMat& src, GpuMat& dst, int flipCode)
Scalar cv::gpu::sum(const GpuMat& src)
{
CV_Assert(src.type() == CV_8UC1 || src.type() == CV_8UC4);
CV_Assert(src.type() == CV_8UC1 || src.type() == CV_8UC4);
NppiSize sz;
sz.width = src.cols;
......@@ -324,7 +321,7 @@ Scalar cv::gpu::sum(const GpuMat& src)
GpuMat buf(1, bufsz, CV_32S);
Scalar res;
nppSafeCall( nppiSum_8u_C1R(src.ptr<Npp8u>(), src.step, sz, buf.ptr<Npp32s>(), res.val) );
nppSafeCall( nppiSum_8u_C1R(src.ptr<Npp8u>(), src.step, sz, buf.ptr<Npp32s>(), res.val) );
return res;
}
else
......@@ -336,8 +333,6 @@ Scalar cv::gpu::sum(const GpuMat& src)
nppSafeCall( nppiSum_8u_C4R(src.ptr<Npp8u>(), src.step, sz, buf.ptr<Npp32s>(), res.val) );
return res;
}
}
////////////////////////////////////////////////////////////////////////
......@@ -371,28 +366,54 @@ void cv::gpu::LUT(const GpuMat& src, const Mat& lut, GpuMat& dst)
{
public:
Npp32s pLevels[256];
const Npp32s* pLevels3[3];
int nValues3[3];
LevelsInit()
{
{
nValues3[0] = nValues3[1] = nValues3[2] = 256;
for (int i = 0; i < 256; ++i)
pLevels[i] = i;
pLevels3[0] = pLevels3[1] = pLevels3[2] = pLevels;
}
};
static LevelsInit lvls;
int cn = src.channels();
CV_Assert(src.type() == CV_8UC1);
CV_Assert(lut.depth() == CV_32SC1 && lut.rows * lut.cols == 256 && lut.isContinuous());
CV_Assert(src.type() == CV_8UC1 || src.type() == CV_8UC3);
CV_Assert(lut.depth() == CV_8U && (lut.channels() == 1 || lut.channels() == cn) && lut.rows * lut.cols == 256 && lut.isContinuous());
dst.create(src.size(), src.type());
dst.create(src.size(), CV_MAKETYPE(lut.depth(), cn));
NppiSize sz;
sz.height = src.rows;
sz.width = src.cols;
Mat nppLut;
lut.convertTo(nppLut, CV_32S);
nppSafeCall( nppiLUT_Linear_8u_C1R(src.ptr<Npp8u>(), src.step, dst.ptr<Npp8u>(), dst.step, sz,
lut.ptr<Npp32s>(), lvls.pLevels, 256) );
if (src.type() == CV_8UC1)
{
nppSafeCall( nppiLUT_Linear_8u_C1R(src.ptr<Npp8u>(), src.step, dst.ptr<Npp8u>(), dst.step, sz,
nppLut.ptr<Npp32s>(), lvls.pLevels, 256) );
}
else
{
Mat nppLut3[3];
const Npp32s* pValues3[3];
if (nppLut.channels() == 1)
pValues3[0] = pValues3[1] = pValues3[2] = nppLut.ptr<Npp32s>();
else
{
cv::split(nppLut, nppLut3);
pValues3[0] = nppLut3[0].ptr<Npp32s>();
pValues3[1] = nppLut3[1].ptr<Npp32s>();
pValues3[2] = nppLut3[2].ptr<Npp32s>();
}
nppSafeCall( nppiLUT_Linear_8u_C3R(src.ptr<Npp8u>(), src.step, dst.ptr<Npp8u>(), dst.step, sz,
pValues3, lvls.pLevels3, lvls.nValues3) );
}
}
#endif /* !defined (HAVE_CUDA) */
\ No newline at end of file
modules/gpu/src/cuda/color.cu
View file @ e1e5047b
......@@ -65,7 +65,7 @@ namespace imgproc
template<> struct TypeVec<float, 3> { typedef float3 vec_t; };
template<> struct TypeVec<float, 4> { typedef float4 vec_t; };
template<typename _Tp> struct ColorChannel {};
template<typename T> struct ColorChannel {};
template<> struct ColorChannel<uchar>
{
......@@ -86,7 +86,17 @@ namespace imgproc
typedef float worktype_f;
static __device__ float max() { return 1.f; }
static __device__ float half() { return 0.5f; }
};
};
template <typename T>
__device__ void assignAlpha(typename TypeVec<T, 3>::vec_t& vec, T val)
{
}
template <typename T>
__device__ void assignAlpha(typename TypeVec<T, 4>::vec_t& vec, T val)
{
vec.w = val;
}
}
//////////////////////////////////////// SwapChannels /////////////////////////////////////
......@@ -96,7 +106,7 @@ namespace imgproc
__constant__ int ccoeffs[4];
template <int CN, typename T>
__global__ void swapChannels(const T* src_, size_t src_step, T* dst_, size_t dst_step, int rows, int cols)
__global__ void swapChannels(const uchar* src_, size_t src_step, uchar* dst_, size_t dst_step, int rows, int cols)
{
typedef typename TypeVec<T, CN>::vec_t vec_t;
......@@ -121,8 +131,8 @@ namespace imgproc
namespace cv { namespace gpu { namespace improc
{
template <typename T>
void swapChannels_caller(const DevMem2D_<T>& src, const DevMem2D_<T>& dst, int cn, const int* coeffs, cudaStream_t stream)
template <typename T, int CN>
void swapChannels_caller(const DevMem2D& src, const DevMem2D& dst, const int* coeffs, cudaStream_t stream)
{
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
......@@ -130,39 +140,38 @@ namespace cv { namespace gpu { namespace improc
grid.x = divUp(src.cols, threads.x);
grid.y = divUp(src.rows, threads.y);
cudaSafeCall( cudaMemcpyToSymbol(imgproc::ccoeffs, coeffs, cn * sizeof(int)) );
cudaSafeCall( cudaMemcpyToSymbol(imgproc::ccoeffs, coeffs, CN * sizeof(int)) );
switch (cn)
{
case 3:
imgproc::swapChannels<3><<<grid, threads, 0, stream>>>(src.ptr, src.step / sizeof(T), dst.ptr, dst.step / sizeof(T), src.rows, src.cols);
break;
case 4:
imgproc::swapChannels<4><<<grid, threads, 0, stream>>>(src.ptr, src.step / sizeof(T), dst.ptr, dst.step / sizeof(T), src.rows, src.cols);
break;
default:
cv::gpu::error("Unsupported channels count", __FILE__, __LINE__);
break;
}
imgproc::swapChannels<CN, T><<<grid, threads, 0, stream>>>(src.ptr, src.step,
dst.ptr, dst.step, src.rows, src.cols);
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
}
void swapChannels_gpu(const DevMem2D& src, const DevMem2D& dst, int cn, const int* coeffs, cudaStream_t stream)
void swapChannels_gpu_8u(const DevMem2D& src, const DevMem2D& dst, int cn, const int* coeffs, cudaStream_t stream)
{
swapChannels_caller(src, dst, cn, coeffs, stream);
typedef void (*swapChannels_caller_t)(const DevMem2D& src, const DevMem2D& dst, const int* coeffs, cudaStream_t stream);
static const swapChannels_caller_t swapChannels_callers[] = {swapChannels_caller<uchar, 3>, swapChannels_caller<uchar, 4>};
swapChannels_callers[cn - 3](src, dst, coeffs, stream);
}
void swapChannels_gpu(const DevMem2D_<unsigned short>& src, const DevMem2D_<unsigned short>& dst, int cn, const int* coeffs, cudaStream_t stream)
void swapChannels_gpu_16u(const DevMem2D& src, const DevMem2D& dst, int cn, const int* coeffs, cudaStream_t stream)
{
swapChannels_caller(src, dst, cn, coeffs, stream);
typedef void (*swapChannels_caller_t)(const DevMem2D& src, const DevMem2D& dst, const int* coeffs, cudaStream_t stream);
static const swapChannels_caller_t swapChannels_callers[] = {swapChannels_caller<unsigned short, 3>, swapChannels_caller<unsigned short, 4>};
swapChannels_callers[cn - 3](src, dst, coeffs, stream);
}
void swapChannels_gpu(const DevMem2Df& src, const DevMem2Df& dst, int cn, const int* coeffs, cudaStream_t stream)
void swapChannels_gpu_32f(const DevMem2D& src, const DevMem2D& dst, int cn, const int* coeffs, cudaStream_t stream)
{
swapChannels_caller(src, dst, cn, coeffs, stream);
}
typedef void (*swapChannels_caller_t)(const DevMem2D& src, const DevMem2D& dst, const int* coeffs, cudaStream_t stream);
static const swapChannels_caller_t swapChannels_callers[] = {swapChannels_caller<float, 3>, swapChannels_caller<float, 4>};
swapChannels_callers[cn - 3](src, dst, coeffs, stream);
}
}}}
////////////////// Various 3/4-channel to 3/4-channel RGB transformations /////////////////
......@@ -170,7 +179,7 @@ namespace cv { namespace gpu { namespace improc
namespace imgproc
{
template <int SRCCN, int DSTCN, typename T>
__global__ void RGB2RGB(const T* src_, size_t src_step, T* dst_, size_t dst_step, int rows, int cols, int bidx)
__global__ void RGB2RGB(const uchar* src_, size_t src_step, uchar* dst_, size_t dst_step, int rows, int cols, int bidx)
{
typedef typename TypeVec<T, SRCCN>::vec_t src_t;
typedef typename TypeVec<T, DSTCN>::vec_t dst_t;
......@@ -186,8 +195,7 @@ namespace imgproc
dst.x = ((const T*)(&src))[bidx];
dst.y = src.y;
dst.z = ((const T*)(&src))[bidx ^ 2];
if (DSTCN == 4)
((T*)(&dst))[3] = ColorChannel<T>::max();
assignAlpha(dst, ColorChannel<T>::max());
*(dst_t*)(dst_ + y * dst_step + x * DSTCN) = dst;
}
......@@ -196,8 +204,8 @@ namespace imgproc
namespace cv { namespace gpu { namespace improc
{
template <typename T>
void RGB2RGB_caller(const DevMem2D_<T>& src, int srccn, const DevMem2D_<T>& dst, int dstcn, int bidx, cudaStream_t stream)
template <typename T, int SRCCN, int DSTCN>
void RGB2RGB_caller(const DevMem2D& src, const DevMem2D& dst, int bidx, cudaStream_t stream)
{
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
......@@ -205,171 +213,248 @@ namespace cv { namespace gpu { namespace improc
grid.x = divUp(src.cols, threads.x);
grid.y = divUp(src.rows, threads.y);
switch (dstcn)
{
case 3:
switch (srccn)
{
case 3:
{
int coeffs[] = {2, 1, 0};
cudaSafeCall( cudaMemcpyToSymbol(imgproc::ccoeffs, coeffs, 3 * sizeof(int)) );
imgproc::swapChannels<3><<<grid, threads, 0, stream>>>(src.ptr, src.step / sizeof(T), dst.ptr, dst.step / sizeof(T), src.rows, src.cols);
break;
}
case 4:
imgproc::RGB2RGB<4, 3><<<grid, threads, 0, stream>>>(src.ptr, src.step / sizeof(T), dst.ptr, dst.step / sizeof(T),
src.rows, src.cols, bidx);
break;
default:
cv::gpu::error("Unsupported channels count", __FILE__, __LINE__);
break;
}
break;
case 4:
switch (srccn)
{
case 3:
imgproc::RGB2RGB<3, 4><<<grid, threads, 0, stream>>>(src.ptr, src.step / sizeof(T), dst.ptr, dst.step / sizeof(T),
src.rows, src.cols, bidx);
break;
case 4:
{
int coeffs[] = {2, 1, 0, 3};
cudaSafeCall( cudaMemcpyToSymbol(imgproc::ccoeffs, coeffs, 4 * sizeof(int)) );
imgproc::swapChannels<4><<<grid, threads, 0, stream>>>(src.ptr, src.step / sizeof(T), dst.ptr, dst.step / sizeof(T), src.rows, src.cols);
break;
}
default:
cv::gpu::error("Unsupported channels count", __FILE__, __LINE__);
break;
}
break;
default:
cv::gpu::error("Unsupported channels count", __FILE__, __LINE__);
break;
}
imgproc::RGB2RGB<SRCCN, DSTCN, T><<<grid, threads, 0, stream>>>(src.ptr, src.step,
dst.ptr, dst.step, src.rows, src.cols, bidx);
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
}
void RGB2RGB_gpu(const DevMem2D& src, int srccn, const DevMem2D& dst, int dstcn, int bidx, cudaStream_t stream)
void RGB2RGB_gpu_8u(const DevMem2D& src, int srccn, const DevMem2D& dst, int dstcn, int bidx, cudaStream_t stream)
{
RGB2RGB_caller(src, srccn, dst, dstcn, bidx, stream);
typedef void (*RGB2RGB_caller_t)(const DevMem2D& src, const DevMem2D& dst, int bidx, cudaStream_t stream);
static const RGB2RGB_caller_t RGB2RGB_callers[2][2] =
{
{RGB2RGB_caller<uchar, 3, 3>, RGB2RGB_caller<uchar, 3, 4>},
{RGB2RGB_caller<uchar, 4, 3>, RGB2RGB_caller<uchar, 4, 4>}
};
RGB2RGB_callers[srccn-3][dstcn-3](src, dst, bidx, stream);
}
void RGB2RGB_gpu(const DevMem2D_<unsigned short>& src, int srccn, const DevMem2D_<unsigned short>& dst, int dstcn, int bidx, cudaStream_t stream)
void RGB2RGB_gpu_16u(const DevMem2D& src, int srccn, const DevMem2D& dst, int dstcn, int bidx, cudaStream_t stream)
{
RGB2RGB_caller(src, srccn, dst, dstcn, bidx, stream);
typedef void (*RGB2RGB_caller_t)(const DevMem2D& src, const DevMem2D& dst, int bidx, cudaStream_t stream);
static const RGB2RGB_caller_t RGB2RGB_callers[2][2] =
{
{RGB2RGB_caller<unsigned short, 3, 3>, RGB2RGB_caller<unsigned short, 3, 4>},
{RGB2RGB_caller<unsigned short, 4, 3>, RGB2RGB_caller<unsigned short, 4, 4>}
};
RGB2RGB_callers[srccn-3][dstcn-3](src, dst, bidx, stream);
}
void RGB2RGB_gpu(const DevMem2Df& src, int srccn, const DevMem2Df& dst, int dstcn, int bidx, cudaStream_t stream)
void RGB2RGB_gpu_32f(const DevMem2D& src, int srccn, const DevMem2D& dst, int dstcn, int bidx, cudaStream_t stream)
{
RGB2RGB_caller(src, srccn, dst, dstcn, bidx, stream);
typedef void (*RGB2RGB_caller_t)(const DevMem2D& src, const DevMem2D& dst, int bidx, cudaStream_t stream);
static const RGB2RGB_caller_t RGB2RGB_callers[2][2] =
{
{RGB2RGB_caller<float, 3, 3>, RGB2RGB_caller<float, 3, 4>},
{RGB2RGB_caller<float, 4, 3>, RGB2RGB_caller<float, 4, 4>}
};
RGB2RGB_callers[srccn-3][dstcn-3](src, dst, bidx, stream);
}
}}}
/////////// Transforming 16-bit (565 or 555) RGB to/from 24/32-bit (888[8]) RGB //////////
//namespace imgproc
//{
// struct RGB5x52RGB
// {
// typedef uchar channel_type;
//
// RGB5x52RGB(int _dstcn, int _blueIdx, int _greenBits)
// : dstcn(_dstcn), blueIdx(_blueIdx), greenBits(_greenBits) {}
//
// void operator()(const uchar* src, uchar* dst, int n) const
// {
// int dcn = dstcn, bidx = blueIdx;
// if( greenBits == 6 )
// for( int i = 0; i < n; i++, dst += dcn )
// {
// unsigned t = ((const unsigned short*)src)[i];
// dst[bidx] = (uchar)(t << 3);
// dst[1] = (uchar)((t >> 3) & ~3);
// dst[bidx ^ 2] = (uchar)((t >> 8) & ~7);
// if( dcn == 4 )
// dst[3] = 255;
// }
// else
// for( int i = 0; i < n; i++, dst += dcn )
// {
// unsigned t = ((const unsigned short*)src)[i];
// dst[bidx] = (uchar)(t << 3);
// dst[1] = (uchar)((t >> 2) & ~7);
// dst[bidx ^ 2] = (uchar)((t >> 7) & ~7);
// if( dcn == 4 )
// dst[3] = t & 0x8000 ? 255 : 0;
// }
// }
//
// int dstcn, blueIdx, greenBits;
// };
//
//
// struct RGB2RGB5x5
// {
// typedef uchar channel_type;
//
// RGB2RGB5x5(int _srccn, int _blueIdx, int _greenBits)
// : srccn(_srccn), blueIdx(_blueIdx), greenBits(_greenBits) {}
//
// void operator()(const uchar* src, uchar* dst, int n) const
// {
// int scn = srccn, bidx = blueIdx;
// if( greenBits == 6 )
// for( int i = 0; i < n; i++, src += scn )
// {
// ((unsigned short*)dst)[i] = (unsigned short)((src[bidx] >> 3)|((src[1]&~3) << 3)|((src[bidx^2]&~7) << 8));
// }
// else if( scn == 3 )
// for( int i = 0; i < n; i++, src += 3 )
// {
// ((unsigned short*)dst)[i] = (unsigned short)((src[bidx] >> 3)|((src[1]&~7) << 2)|((src[bidx^2]&~7) << 7));
// }
// else
// for( int i = 0; i < n; i++, src += 4 )
// {
// ((unsigned short*)dst)[i] = (unsigned short)((src[bidx] >> 3)|((src[1]&~7) << 2)|
// ((src[bidx^2]&~7) << 7)|(src[3] ? 0x8000 : 0));
// }
// }
//
// int srccn, blueIdx, greenBits;
// };
//}
//
//namespace cv { namespace gpu { namespace impl
//{
//}}}
///////////////////////////////// Grayscale to Color ////////////////////////////////
namespace imgproc
{
template <typename T>
__global__ void Gray2RGB_3(const T* src_, size_t src_step, T* dst_, size_t dst_step, int rows, int cols)
template <int GREEN_BITS, int DSTCN> struct RGB5x52RGBConverter {};
template <int DSTCN> struct RGB5x52RGBConverter<5, DSTCN>
{
typedef typename TypeVec<uchar, DSTCN>::vec_t dst_t;
static __device__ dst_t cvt(unsigned int src, int bidx)
{
dst_t dst;
((uchar*)(&dst))[bidx] = (uchar)(src << 3);
dst.y = (uchar)((src >> 2) & ~7);
((uchar*)(&dst))[bidx ^ 2] = (uchar)((src >> 7) & ~7);
assignAlpha(dst, (uchar)(src & 0x8000 ? 255 : 0));
return dst;
}
};
template <int DSTCN> struct RGB5x52RGBConverter<6, DSTCN>
{
typedef typename TypeVec<uchar, DSTCN>::vec_t dst_t;
static __device__ dst_t cvt(unsigned int src, int bidx)
{
dst_t dst;
((uchar*)(&dst))[bidx] = (uchar)(src << 3);
dst.y = (uchar)((src >> 3) & ~3);
((uchar*)(&dst))[bidx ^ 2] = (uchar)((src >> 8) & ~7);
assignAlpha(dst, (uchar)(255));
return dst;
}
};
template <int GREEN_BITS, int DSTCN>
__global__ void RGB5x52RGB(const uchar* src_, size_t src_step, uchar* dst_, size_t dst_step, int rows, int cols, int bidx)
{
typedef typename TypeVec<uchar, DSTCN>::vec_t dst_t;
const int x = blockDim.x * blockIdx.x + threadIdx.x;
const int y = blockDim.y * blockIdx.y + threadIdx.y;
if (y < rows && x < cols)
{
T src = src_[y * src_step + x];
T* dst = dst_ + y * dst_step + x * 3;
dst[0] = src;
dst[1] = src;
dst[2] = src;
unsigned int src = *(const unsigned short*)(src_ + y * src_step + (x << 1));
*(dst_t*)(dst_ + y * dst_step + x * DSTCN) = RGB5x52RGBConverter<GREEN_BITS, DSTCN>::cvt(src, bidx);
}
}
template <typename T>
__global__ void Gray2RGB_4(const T* src_, size_t src_step, T* dst_, size_t dst_step, int rows, int cols)
/*struct RGB5x52RGB
{
typedef uchar channel_type;
RGB5x52RGB(int _dstcn, int _blueIdx, int _greenBits)
: dstcn(_dstcn), blueIdx(_blueIdx), greenBits(_greenBits) {}
void operator()(const uchar* src, uchar* dst, int n) const
{
int dcn = dstcn, bidx = blueIdx;
if( greenBits == 6 )
for( int i = 0; i < n; i++, dst += dcn )
{
unsigned t = ((const unsigned short*)src)[i];
dst[bidx] = (uchar)(t << 3);
dst[1] = (uchar)((t >> 3) & ~3);
dst[bidx ^ 2] = (uchar)((t >> 8) & ~7);
if( dcn == 4 )
dst[3] = 255;
}
else
for( int i = 0; i < n; i++, dst += dcn )
{
unsigned t = ((const unsigned short*)src)[i];
dst[bidx] = (uchar)(t << 3);
dst[1] = (uchar)((t >> 2) & ~7);
dst[bidx ^ 2] = (uchar)((t >> 7) & ~7);
if( dcn == 4 )
dst[3] = t & 0x8000 ? 255 : 0;
}
}
int dstcn, blueIdx, greenBits;
};*/
template <int SRCCN, int GREEN_BITS> struct RGB2RGB5x5Converter {};
template<int SRCCN> struct RGB2RGB5x5Converter<SRCCN, 6>
{
static __device__ unsigned short cvt(const uchar* src_ptr, int bidx)
{
return (unsigned short)((src_ptr[bidx] >> 3) | ((src_ptr[1] & ~3) << 3) | ((src_ptr[bidx^2] & ~7) << 8));
}
};
template<> struct RGB2RGB5x5Converter<3, 5>
{
static __device__ unsigned short cvt(const uchar* src_ptr, int bidx)
{
return (unsigned short)((src_ptr[bidx] >> 3) | ((src_ptr[1] & ~7) << 2) | ((src_ptr[bidx^2] & ~7) << 7));
}
};
template<> struct RGB2RGB5x5Converter<4, 5>
{
typedef typename TypeVec<T, 4>::vec_t vec4_t;
static __device__ unsigned short cvt(const uchar* src_ptr, int bidx)
{
return (unsigned short)((src_ptr[bidx] >> 3) | ((src_ptr[1] & ~7) << 2) | ((src_ptr[bidx^2] & ~7) << 7)|(src_ptr[3] ? 0x8000 : 0));
}
};
template<int SRCCN, int GREEN_BITS>
__global__ void RGB2RGB5x5(const uchar* src_, size_t src_step, uchar* dst_, size_t dst_step, int rows, int cols, int bidx)
{
typedef typename TypeVec<uchar, SRCCN>::vec_t src_t;
const int x = blockDim.x * blockIdx.x + threadIdx.x;
const int y = blockDim.y * blockIdx.y + threadIdx.y;
if (y < rows && x < cols)
{
src_t src = *(src_t*)(src_ + y * src_step + x * SRCCN);
*(unsigned short*)(dst_ + y * dst_step + (x << 1)) = RGB2RGB5x5Converter<SRCCN, GREEN_BITS>::cvt((const uchar*)(&src), bidx);
}
}
}
namespace cv { namespace gpu { namespace improc
{
template <int GREEN_BITS, int DSTCN>
void RGB5x52RGB_caller(const DevMem2D& src, const DevMem2D& dst, int bidx, cudaStream_t stream)
{
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
grid.x = divUp(src.cols, threads.x);
grid.y = divUp(src.rows, threads.y);
imgproc::RGB5x52RGB<GREEN_BITS, DSTCN><<<grid, threads, 0, stream>>>(src.ptr, src.step,
dst.ptr, dst.step, src.rows, src.cols, bidx);
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
}
void RGB5x52RGB_gpu(const DevMem2D& src, int green_bits, const DevMem2D& dst, int dstcn, int bidx, cudaStream_t stream)
{
typedef void (*RGB5x52RGB_caller_t)(const DevMem2D& src, const DevMem2D& dst, int bidx, cudaStream_t stream);
static const RGB5x52RGB_caller_t RGB5x52RGB_callers[2][2] =
{
{RGB5x52RGB_caller<5, 3>, RGB5x52RGB_caller<5, 4>},
{RGB5x52RGB_caller<6, 3>, RGB5x52RGB_caller<6, 4>}
};
RGB5x52RGB_callers[green_bits - 5][dstcn - 5](src, dst, bidx, stream);
}
template <int SRCCN, int GREEN_BITS>
void RGB2RGB5x5_caller(const DevMem2D& src, const DevMem2D& dst, int bidx, cudaStream_t stream)
{
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
grid.x = divUp(src.cols, threads.x);
grid.y = divUp(src.rows, threads.y);
imgproc::RGB2RGB5x5<SRCCN, GREEN_BITS><<<grid, threads, 0, stream>>>(src.ptr, src.step,
dst.ptr, dst.step, src.rows, src.cols, bidx);
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
}
void RGB2RGB5x5_gpu(const DevMem2D& src, int srccn, const DevMem2D& dst, int green_bits, int bidx, cudaStream_t stream)
{
typedef void (*RGB2RGB5x5_caller_t)(const DevMem2D& src, const DevMem2D& dst, int bidx, cudaStream_t stream);
static const RGB2RGB5x5_caller_t RGB2RGB5x5_callers[2][2] =
{
{RGB2RGB5x5_caller<3, 5>, RGB2RGB5x5_caller<3, 6>},
{RGB2RGB5x5_caller<4, 5>, RGB2RGB5x5_caller<4, 6>}
};
RGB2RGB5x5_callers[srccn - 3][green_bits - 5](src, dst, bidx, stream);
}
}}}
///////////////////////////////// Grayscale to Color ////////////////////////////////
namespace imgproc
{
template <int DSTCN, typename T>
__global__ void Gray2RGB(const T* src_, size_t src_step, T* dst_, size_t dst_step, int rows, int cols)
{
typedef typename TypeVec<T, DSTCN>::vec_t dst_t;
const int x = blockDim.x * blockIdx.x + threadIdx.x;
const int y = blockDim.y * blockIdx.y + threadIdx.y;
......@@ -377,12 +462,12 @@ namespace imgproc
if (y < rows && x < cols)
{
T src = src_[y * src_step + x];
vec4_t dst;
dst_t dst;
dst.x = src;
dst.y = src;
dst.z = src;
dst.w = ColorChannel<T>::max();
*(vec4_t*)(dst_ + y * dst_step + (x << 2)) = dst;
assignAlpha(dst, ColorChannel<T>::max());
*(dst_t*)(dst_ + y * dst_step + x * DSTCN) = dst;
}
}
......@@ -412,8 +497,8 @@ namespace imgproc
namespace cv { namespace gpu { namespace improc
{
template <typename T>
void Gray2RGB_caller(const DevMem2D_<T>& src, const DevMem2D_<T>& dst, int dstcn, cudaStream_t stream)
template <typename T, int DSTCN>
void Gray2RGB_caller(const DevMem2D_<T>& src, const DevMem2D_<T>& dst, cudaStream_t stream)
{
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
......@@ -421,18 +506,8 @@ namespace cv { namespace gpu { namespace improc
grid.x = divUp(src.cols, threads.x);
grid.y = divUp(src.rows, threads.y);
switch (dstcn)
{
case 3:
imgproc::Gray2RGB_3<<<grid, threads, 0, stream>>>(src.ptr, src.step / sizeof(T), dst.ptr, dst.step / sizeof(T), src.rows, src.cols);
break;
case 4:
imgproc::Gray2RGB_4<<<grid, threads, 0, stream>>>(src.ptr, src.step / sizeof(T), dst.ptr, dst.step / sizeof(T), src.rows, src.cols);
break;
default:
cv::gpu::error("Unsupported channels count", __FILE__, __LINE__);
break;
}
imgproc::Gray2RGB<DSTCN><<<grid, threads, 0, stream>>>(src.ptr, src.step / sizeof(T),
dst.ptr, dst.step / sizeof(T), src.rows, src.cols);
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -440,17 +515,26 @@ namespace cv { namespace gpu { namespace improc
void Gray2RGB_gpu(const DevMem2D& src, const DevMem2D& dst, int dstcn, cudaStream_t stream)
{
Gray2RGB_caller(src, dst, dstcn, stream);
typedef void (*Gray2RGB_caller_t)(const DevMem2D& src, const DevMem2D& dst, cudaStream_t stream);
static const Gray2RGB_caller_t Gray2RGB_callers[] = {Gray2RGB_caller<uchar, 3>, Gray2RGB_caller<uchar, 4>};
Gray2RGB_callers[dstcn - 3](src, dst, stream);
}
void Gray2RGB_gpu(const DevMem2D_<unsigned short>& src, const DevMem2D_<unsigned short>& dst, int dstcn, cudaStream_t stream)
{
Gray2RGB_caller(src, dst, dstcn, stream);
typedef void (*Gray2RGB_caller_t)(const DevMem2D_<unsigned short>& src, const DevMem2D_<unsigned short>& dst, cudaStream_t stream);
static const Gray2RGB_caller_t Gray2RGB_callers[] = {Gray2RGB_caller<unsigned short, 3>, Gray2RGB_caller<unsigned short, 4>};
Gray2RGB_callers[dstcn - 3](src, dst, stream);
}
void Gray2RGB_gpu(const DevMem2Df& src, const DevMem2Df& dst, int dstcn, cudaStream_t stream)
{
Gray2RGB_caller(src, dst, dstcn, stream);
typedef void (*Gray2RGB_caller_t)(const DevMem2Df& src, const DevMem2Df& dst, cudaStream_t stream);
static const Gray2RGB_caller_t Gray2RGB_callers[] = {Gray2RGB_caller<float, 3>, Gray2RGB_caller<float, 4>};
Gray2RGB_callers[dstcn - 3](src, dst, stream);
}
}}}
......
modules/gpu/src/imgproc_gpu.cpp
View file @ e1e5047b
......@@ -81,13 +81,16 @@ namespace cv { namespace gpu
void reprojectImageTo3D_gpu(const DevMem2D& disp, const DevMem2Df& xyzw, const float* q, const cudaStream_t& stream);
void reprojectImageTo3D_gpu(const DevMem2D_<short>& disp, const DevMem2Df& xyzw, const float* q, const cudaStream_t& stream);
void swapChannels_gpu(const DevMem2D& src, const DevMem2D& dst, int cn, const int* coeffs, cudaStream_t stream);
void swapChannels_gpu(const DevMem2D_<ushort>& src, const DevMem2D_<ushort>& dst, int cn, const int* coeffs, cudaStream_t stream);
void swapChannels_gpu(const DevMem2Df& src, const DevMem2Df& dst, int cn, const int* coeffs, cudaStream_t stream);
void swapChannels_gpu_8u(const DevMem2D& src, const DevMem2D& dst, int cn, const int* coeffs, cudaStream_t stream);
void swapChannels_gpu_16u(const DevMem2D& src, const DevMem2D& dst, int cn, const int* coeffs, cudaStream_t stream);
void swapChannels_gpu_32f(const DevMem2D& src, const DevMem2D& dst, int cn, const int* coeffs, cudaStream_t stream);
void RGB2RGB_gpu(const DevMem2D& src, int srccn, const DevMem2D& dst, int dstcn, int bidx, cudaStream_t stream);
void RGB2RGB_gpu(const DevMem2D_<ushort>& src, int srccn, const DevMem2D_<ushort>& dst, int dstcn, int bidx, cudaStream_t stream);
void RGB2RGB_gpu(const DevMem2Df& src, int srccn, const DevMem2Df& dst, int dstcn, int bidx, cudaStream_t stream);
void RGB2RGB_gpu_8u(const DevMem2D& src, int srccn, const DevMem2D& dst, int dstcn, int bidx, cudaStream_t stream);
void RGB2RGB_gpu_16u(const DevMem2D& src, int srccn, const DevMem2D& dst, int dstcn, int bidx, cudaStream_t stream);
void RGB2RGB_gpu_32f(const DevMem2D& src, int srccn, const DevMem2D& dst, int dstcn, int bidx, cudaStream_t stream);
void RGB5x52RGB_gpu(const DevMem2D& src, int green_bits, const DevMem2D& dst, int dstcn, int bidx, cudaStream_t stream);
void RGB2RGB5x5_gpu(const DevMem2D& src, int srccn, const DevMem2D& dst, int green_bits, int bidx, cudaStream_t stream);
void Gray2RGB_gpu(const DevMem2D& src, const DevMem2D& dst, int dstcn, cudaStream_t stream);
void Gray2RGB_gpu(const DevMem2D_<ushort>& src, const DevMem2D_<ushort>& dst, int dstcn, cudaStream_t stream);
......@@ -245,38 +248,36 @@ namespace
out.create(sz, CV_MAKETYPE(depth, dcn));
if( depth == CV_8U )
improc::RGB2RGB_gpu((DevMem2D)src, scn, (DevMem2D)out, dcn, bidx, stream);
improc::RGB2RGB_gpu_8u(src, scn, out, dcn, bidx, stream);
else if( depth == CV_16U )
improc::RGB2RGB_gpu((DevMem2D_<unsigned short>)src, scn, (DevMem2D_<unsigned short>)out, dcn, bidx, stream);
improc::RGB2RGB_gpu_16u(src, scn, out, dcn, bidx, stream);
else
improc::RGB2RGB_gpu((DevMem2Df)src, scn, (DevMem2Df)out, dcn, bidx, stream);
improc::RGB2RGB_gpu_32f(src, scn, out, dcn, bidx, stream);
break;
//case CV_BGR2BGR565: case CV_BGR2BGR555: case CV_RGB2BGR565: case CV_RGB2BGR555:
//case CV_BGRA2BGR565: case CV_BGRA2BGR555: case CV_RGBA2BGR565: case CV_RGBA2BGR555:
// CV_Assert( (scn == 3 || scn == 4) && depth == CV_8U );
// dst.create(sz, CV_8UC2);
//
// CvtColorLoop(src, dst, RGB2RGB5x5(scn,
// code == CV_BGR2BGR565 || code == CV_BGR2BGR555 ||
// code == CV_BGRA2BGR565 || code == CV_BGRA2BGR555 ? 0 : 2,
// code == CV_BGR2BGR565 || code == CV_RGB2BGR565 ||
// code == CV_BGRA2BGR565 || code == CV_RGBA2BGR565 ? 6 : 5 // green bits
// ));
// break;
case CV_BGR2BGR565: case CV_BGR2BGR555: case CV_RGB2BGR565: case CV_RGB2BGR555:
case CV_BGRA2BGR565: case CV_BGRA2BGR555: case CV_RGBA2BGR565: case CV_RGBA2BGR555:
CV_Assert( (scn == 3 || scn == 4) && depth == CV_8U );
out.create(sz, CV_8UC2);
improc::RGB2RGB5x5_gpu(src, scn, out, code == CV_BGR2BGR565 || code == CV_RGB2BGR565 ||
code == CV_BGRA2BGR565 || code == CV_RGBA2BGR565 ? 6 : 5,
code == CV_BGR2BGR565 || code == CV_BGR2BGR555 ||
code == CV_BGRA2BGR565 || code == CV_BGRA2BGR555 ? 0 : 2,
stream);
break;
//case CV_BGR5652BGR: case CV_BGR5552BGR: case CV_BGR5652RGB: case CV_BGR5552RGB:
//case CV_BGR5652BGRA: case CV_BGR5552BGRA: case CV_BGR5652RGBA: case CV_BGR5552RGBA:
// if(dcn <= 0) dcn = 3;
// CV_Assert( (dcn == 3 || dcn == 4) && scn == 2 && depth == CV_8U );
// dst.create(sz, CV_MAKETYPE(depth, dcn));
//
// CvtColorLoop(src, dst, RGB5x52RGB(dcn,
// code == CV_BGR5652BGR || code == CV_BGR5552BGR ||
// code == CV_BGR5652BGRA || code == CV_BGR5552BGRA ? 0 : 2, // blue idx
// code == CV_BGR5652BGR || code == CV_BGR5652RGB ||
// code == CV_BGR5652BGRA || code == CV_BGR5652RGBA ? 6 : 5 // green bits
// ));
// out.create(sz, CV_MAKETYPE(depth, dcn));
// improc::RGB5x52RGB_gpu(src, code == CV_BGR2BGR565 || code == CV_RGB2BGR565 ||
// code == CV_BGRA2BGR565 || code == CV_RGBA2BGR565 ? 6 : 5, out, dcn,
// code == CV_BGR2BGR565 || code == CV_BGR2BGR555 ||
// code == CV_BGRA2BGR565 || code == CV_BGRA2BGR555 ? 0 : 2,
// stream);
// break;
case CV_BGR2GRAY: case CV_BGRA2GRAY: case CV_RGB2GRAY: case CV_RGBA2GRAY:
......@@ -329,7 +330,7 @@ namespace
nppSafeCall( nppiRGBToYCbCr_8u_C3R(src.ptr<Npp8u>(), src.step, out.ptr<Npp8u>(), out.step, nppsz) );
{
static int coeffs[] = {0, 2, 1};
improc::swapChannels_gpu((DevMem2D)out, (DevMem2D)out, 3, coeffs, 0);
improc::swapChannels_gpu_8u(out, out, 3, coeffs, 0);
}
break;
......@@ -341,7 +342,7 @@ namespace
{
static int coeffs[] = {0, 2, 1};
GpuMat src1(src.size(), src.type());
improc::swapChannels_gpu((DevMem2D)src, (DevMem2D)src1, 3, coeffs, 0);
improc::swapChannels_gpu_8u(src, src1, 3, coeffs, 0);
nppSafeCall( nppiYCbCrToRGB_8u_C3R(src1.ptr<Npp8u>(), src1.step, out.ptr<Npp8u>(), out.step, nppsz) );
}
break;
......
tests/gpu/src/arithm.cpp
View file @ e1e5047b
/*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.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 <iostream>
#include <cmath>
#include <limits>
#include "gputest.hpp"
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
using namespace cv;
using namespace std;
using namespace gpu;
class CV_GpuArithmTest : public CvTest
{
public:
CV_GpuArithmTest(const char* test_name, const char* test_funcs) : CvTest(test_name, test_funcs) {}
virtual ~CV_GpuArithmTest() {}
protected:
void run(int);
int test(int type);
virtual int test(const Mat& mat1, const Mat& mat2) = 0;
int CheckNorm(const Mat& m1, const Mat& m2);
int CheckNorm(const Scalar& s1, const Scalar& s2);
int CheckNorm(double d1, double d2);
};
int CV_GpuArithmTest::test(int type)
{
cv::Size sz(200, 200);
cv::Mat mat1(sz, type), mat2(sz, type);
cv::RNG rng(*ts->get_rng());
rng.fill(mat1, cv::RNG::UNIFORM, cv::Scalar::all(10), cv::Scalar::all(100));
rng.fill(mat2, cv::RNG::UNIFORM, cv::Scalar::all(10), cv::Scalar::all(100));
return test(mat1, mat2);
}
int CV_GpuArithmTest::CheckNorm(const Mat& m1, const Mat& m2)
{
double ret = norm(m1, m2, NORM_INF);
if (ret < std::numeric_limits<double>::epsilon())
return CvTS::OK;
ts->printf(CvTS::LOG, "\nNorm: %f\n", ret);
return CvTS::FAIL_GENERIC;
}
int CV_GpuArithmTest::CheckNorm(const Scalar& s1, const Scalar& s2)
{
double ret0 = CheckNorm(s1[0], s2[0]), ret1 = CheckNorm(s1[1], s2[1]), ret2 = CheckNorm(s1[2], s2[2]), ret3 = CheckNorm(s1[3], s2[3]);
return (ret0 == CvTS::OK && ret1 == CvTS::OK && ret2 == CvTS::OK && ret3 == CvTS::OK) ? CvTS::OK : CvTS::FAIL_GENERIC;
}
int CV_GpuArithmTest::CheckNorm(double d1, double d2)
{
double ret = ::fabs(d1 - d2);
if (ret < std::numeric_limits<double>::epsilon())
return CvTS::OK;
ts->printf(CvTS::LOG, "\nNorm: %f\n", ret);
return CvTS::FAIL_GENERIC;
}
void CV_GpuArithmTest::run( int )
{
int testResult = CvTS::OK;
try
{
const int types[] = {CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1};
const char* type_names[] = {"CV_8UC1", "CV_8UC3", "CV_8UC4", "CV_32FC1"};
const int type_count = sizeof(types)/sizeof(types[0]);
//run tests
for (int t = 0; t < type_count; ++t)
{
ts->printf(CvTS::LOG, "========Start test %s========\n", type_names[t]);
if (CvTS::OK == test(types[t]))
ts->printf(CvTS::LOG, "SUCCESS\n");
else
{
ts->printf(CvTS::LOG, "FAIL\n");
testResult = CvTS::FAIL_MISMATCH;
}
}
///!!! author, please remove commented code if loop above is equivalent.
/*ts->printf(CvTS::LOG, "\n========Start test 8UC1========\n");
if (test(CV_8UC1) == CvTS::OK)
ts->printf(CvTS::LOG, "\nSUCCESS\n");
else
{
ts->printf(CvTS::LOG, "\nFAIL\n");
testResult = CvTS::FAIL_GENERIC;
}
ts->printf(CvTS::LOG, "\n========Start test 8UC3========\n");
if (test(CV_8UC3) == CvTS::OK)
ts->printf(CvTS::LOG, "\nSUCCESS\n");
else
{
ts->printf(CvTS::LOG, "\nFAIL\n");
testResult = CvTS::FAIL_GENERIC;
}
ts->printf(CvTS::LOG, "\n========Start test 8UC4========\n");
if (test(CV_8UC4) == CvTS::OK)
ts->printf(CvTS::LOG, "\nSUCCESS\n");
else
{
ts->printf(CvTS::LOG, "\nFAIL\n");
testResult = CvTS::FAIL_GENERIC;
}
ts->printf(CvTS::LOG, "\n========Start test 32FC1========\n");
if (test(CV_32FC1) == CvTS::OK)
ts->printf(CvTS::LOG, "\nSUCCESS\n");
else
{
ts->printf(CvTS::LOG, "\nFAIL\n");
testResult = CvTS::FAIL_GENERIC;
}*/
}
catch(const cv::Exception& e)
{
if (!check_and_treat_gpu_exception(e, ts))
throw;
return;
}
ts->set_failed_test_info(testResult);
}
////////////////////////////////////////////////////////////////////////////////
// Add
struct CV_GpuNppImageAddTest : public CV_GpuArithmTest
{
CV_GpuNppImageAddTest() : CV_GpuArithmTest( "GPU-NppImageAdd", "add" ) {}
virtual int test(const Mat& mat1, const Mat& mat2)
{
if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC4 && mat1.type() != CV_32FC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
cv::Mat cpuRes;
cv::add(mat1, mat2, cpuRes);
GpuMat gpu1(mat1);
GpuMat gpu2(mat2);
GpuMat gpuRes;
cv::gpu::add(gpu1, gpu2, gpuRes);
return CheckNorm(cpuRes, gpuRes);
}
};
////////////////////////////////////////////////////////////////////////////////
// Sub
struct CV_GpuNppImageSubtractTest : public CV_GpuArithmTest
{
CV_GpuNppImageSubtractTest() : CV_GpuArithmTest( "GPU-NppImageSubtract", "subtract" ) {}
int test( const Mat& mat1, const Mat& mat2 )
{
if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC4 && mat1.type() != CV_32FC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
cv::Mat cpuRes;
cv::subtract(mat1, mat2, cpuRes);
GpuMat gpu1(mat1);
GpuMat gpu2(mat2);
GpuMat gpuRes;
cv::gpu::subtract(gpu1, gpu2, gpuRes);
return CheckNorm(cpuRes, gpuRes);
}
};
////////////////////////////////////////////////////////////////////////////////
// multiply
struct CV_GpuNppImageMultiplyTest : public CV_GpuArithmTest
{
CV_GpuNppImageMultiplyTest() : CV_GpuArithmTest( "GPU-NppImageMultiply", "multiply" ) {}
int test( const Mat& mat1, const Mat& mat2 )
{
if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC4 && mat1.type() != CV_32FC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
cv::Mat cpuRes;
cv::multiply(mat1, mat2, cpuRes);
GpuMat gpu1(mat1);
GpuMat gpu2(mat2);
GpuMat gpuRes;
cv::gpu::multiply(gpu1, gpu2, gpuRes);
return CheckNorm(cpuRes, gpuRes);
}
};
////////////////////////////////////////////////////////////////////////////////
// divide
struct CV_GpuNppImageDivideTest : public CV_GpuArithmTest
{
CV_GpuNppImageDivideTest() : CV_GpuArithmTest( "GPU-NppImageDivide", "divide" ) {}
int test( const Mat& mat1, const Mat& mat2 )
{
if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC4 && mat1.type() != CV_32FC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
cv::Mat cpuRes;
cv::divide(mat1, mat2, cpuRes);
GpuMat gpu1(mat1);
GpuMat gpu2(mat2);
GpuMat gpuRes;
cv::gpu::divide(gpu1, gpu2, gpuRes);
return CheckNorm(cpuRes, gpuRes);
}
};
////////////////////////////////////////////////////////////////////////////////
// transpose
struct CV_GpuNppImageTransposeTest : public CV_GpuArithmTest
{
CV_GpuNppImageTransposeTest() : CV_GpuArithmTest( "GPU-NppImageTranspose", "transpose" ) {}
int test( const Mat& mat1, const Mat& )
{
if (mat1.type() != CV_8UC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
cv::Mat cpuRes;
cv::transpose(mat1, cpuRes);
GpuMat gpu1(mat1);
GpuMat gpuRes;
cv::gpu::transpose(gpu1, gpuRes);
return CheckNorm(cpuRes, gpuRes);
}
};
////////////////////////////////////////////////////////////////////////////////
// absdiff
struct CV_GpuNppImageAbsdiffTest : public CV_GpuArithmTest
{
CV_GpuNppImageAbsdiffTest() : CV_GpuArithmTest( "GPU-NppImageAbsdiff", "absdiff" ) {}
int test( const Mat& mat1, const Mat& mat2 )
{
if (mat1.type() != CV_8UC1 && mat1.type() != CV_32FC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
cv::Mat cpuRes;
cv::absdiff(mat1, mat2, cpuRes);
GpuMat gpu1(mat1);
GpuMat gpu2(mat2);
GpuMat gpuRes;
cv::gpu::absdiff(gpu1, gpu2, gpuRes);
return CheckNorm(cpuRes, gpuRes);
}
};
////////////////////////////////////////////////////////////////////////////////
// compare
struct CV_GpuNppImageCompareTest : public CV_GpuArithmTest
{
CV_GpuNppImageCompareTest() : CV_GpuArithmTest( "GPU-NppImageCompare", "compare" ) {}
int test( const Mat& mat1, const Mat& mat2 )
{
if (mat1.type() != CV_32FC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
int cmp_codes[] = {CMP_EQ, CMP_GT, CMP_GE, CMP_LT, CMP_LE, CMP_NE};
const char* cmp_str[] = {"CMP_EQ", "CMP_GT", "CMP_GE", "CMP_LT", "CMP_LE", "CMP_NE"};
int cmp_num = sizeof(cmp_codes) / sizeof(int);
int test_res = CvTS::OK;
for (int i = 0; i < cmp_num; ++i)
{
ts->printf(CvTS::LOG, "\nCompare operation: %s\n", cmp_str[i]);
cv::Mat cpuRes;
cv::compare(mat1, mat2, cpuRes, cmp_codes[i]);
GpuMat gpu1(mat1);
GpuMat gpu2(mat2);
GpuMat gpuRes;
cv::gpu::compare(gpu1, gpu2, gpuRes, cmp_codes[i]);
if (CheckNorm(cpuRes, gpuRes) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// meanStdDev
struct CV_GpuNppImageMeanStdDevTest : public CV_GpuArithmTest
{
CV_GpuNppImageMeanStdDevTest() : CV_GpuArithmTest( "GPU-NppImageMeanStdDev", "meanStdDev" ) {}
int test( const Mat& mat1, const Mat& )
{
if (mat1.type() != CV_8UC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
Scalar cpumean;
Scalar cpustddev;
cv::meanStdDev(mat1, cpumean, cpustddev);
GpuMat gpu1(mat1);
Scalar gpumean;
Scalar gpustddev;
cv::gpu::meanStdDev(gpu1, gpumean, gpustddev);
int test_res = CvTS::OK;
if (CheckNorm(cpumean, gpumean) != CvTS::OK)
{
ts->printf(CvTS::LOG, "\nMean FAILED\n");
test_res = CvTS::FAIL_GENERIC;
}
if (CheckNorm(cpustddev, gpustddev) != CvTS::OK)
{
ts->printf(CvTS::LOG, "\nStdDev FAILED\n");
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// norm
struct CV_GpuNppImageNormTest : public CV_GpuArithmTest
{
CV_GpuNppImageNormTest() : CV_GpuArithmTest( "GPU-NppImageNorm", "norm" ) {}
int test( const Mat& mat1, const Mat& mat2 )
{
if (mat1.type() != CV_8UC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
int norms[] = {NORM_INF, NORM_L1, NORM_L2};
const char* norms_str[] = {"NORM_INF", "NORM_L1", "NORM_L2"};
int norms_num = sizeof(norms) / sizeof(int);
int test_res = CvTS::OK;
for (int i = 0; i < norms_num; ++i)
{
ts->printf(CvTS::LOG, "\nNorm type: %s\n", norms_str[i]);
double cpu_norm = cv::norm(mat1, mat2, norms[i]);
GpuMat gpu1(mat1);
GpuMat gpu2(mat2);
double gpu_norm = cv::gpu::norm(gpu1, gpu2, norms[i]);
if (CheckNorm(cpu_norm, gpu_norm) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// flip
struct CV_GpuNppImageFlipTest : public CV_GpuArithmTest
{
CV_GpuNppImageFlipTest() : CV_GpuArithmTest( "GPU-NppImageFlip", "flip" ) {}
int test( const Mat& mat1, const Mat& )
{
if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC4)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
int flip_codes[] = {0, 1, -1};
const char* flip_axis[] = {"X", "Y", "Both"};
int flip_codes_num = sizeof(flip_codes) / sizeof(int);
int test_res = CvTS::OK;
for (int i = 0; i < flip_codes_num; ++i)
{
ts->printf(CvTS::LOG, "\nFlip Axis: %s\n", flip_axis[i]);
Mat cpu_res;
cv::flip(mat1, cpu_res, flip_codes[i]);
GpuMat gpu1(mat1);
GpuMat gpu_res;
cv::gpu::flip(gpu1, gpu_res, flip_codes[i]);
if (CheckNorm(cpu_res, gpu_res) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// sum
struct CV_GpuNppImageSumTest : public CV_GpuArithmTest
{
CV_GpuNppImageSumTest() : CV_GpuArithmTest( "GPU-NppImageSum", "sum" ) {}
int test( const Mat& mat1, const Mat& )
{
if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC4)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
Scalar cpures = cv::sum(mat1);
GpuMat gpu1(mat1);
Scalar gpures = cv::gpu::sum(gpu1);
return CheckNorm(cpures, gpures);
}
};
////////////////////////////////////////////////////////////////////////////////
// minNax
struct CV_GpuNppImageMinNaxTest : public CV_GpuArithmTest
{
CV_GpuNppImageMinNaxTest() : CV_GpuArithmTest( "GPU-NppImageMinNax", "minNax" ) {}
int test( const Mat& mat1, const Mat& )
{
if (mat1.type() != CV_8UC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
double cpumin, cpumax;
cv::minMaxLoc(mat1, &cpumin, &cpumax);
GpuMat gpu1(mat1);
double gpumin, gpumax;
cv::gpu::minMax(gpu1, &gpumin, &gpumax);
return (CheckNorm(cpumin, gpumin) == CvTS::OK && CheckNorm(cpumax, gpumax) == CvTS::OK) ? CvTS::OK : CvTS::FAIL_GENERIC;
}
};
////////////////////////////////////////////////////////////////////////////////
// LUT
struct CV_GpuNppImageLUTTest : public CV_GpuArithmTest
{
CV_GpuNppImageLUTTest() : CV_GpuArithmTest( "GPU-NppImageLUT", "LUT" ) {}
int test( const Mat& mat1, const Mat& )
{
if (mat1.type() != CV_8UC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
cv::Mat lut(1, 256, CV_32SC1);
cv::RNG rng(*ts->get_rng());
rng.fill(lut, cv::RNG::UNIFORM, cv::Scalar::all(100), cv::Scalar::all(200));
cv::Mat cpuRes;
cv::LUT(mat1, lut, cpuRes);
cpuRes.convertTo(cpuRes, CV_8U);
cv::gpu::GpuMat gpuRes;
cv::gpu::LUT(GpuMat(mat1), lut, gpuRes);
return CheckNorm(cpuRes, gpuRes);
}
};
/////////////////////////////////////////////////////////////////////////////
/////////////////// tests registration /////////////////////////////////////
/////////////////////////////////////////////////////////////////////////////
// If we comment some tests, we may foget/miss to uncomment it after.
// Placing all test definitions in one place
// makes us know about what tests are commented.
/*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.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 <iostream>
#include <cmath>
#include <limits>
#include "gputest.hpp"
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
using namespace cv;
using namespace std;
using namespace gpu;
class CV_GpuArithmTest : public CvTest
{
public:
CV_GpuArithmTest(const char* test_name, const char* test_funcs) : CvTest(test_name, test_funcs) {}
virtual ~CV_GpuArithmTest() {}
protected:
void run(int);
int test(int type);
virtual int test(const Mat& mat1, const Mat& mat2) = 0;
int CheckNorm(const Mat& m1, const Mat& m2);
int CheckNorm(const Scalar& s1, const Scalar& s2);
int CheckNorm(double d1, double d2);
};
int CV_GpuArithmTest::test(int type)
{
cv::Size sz(200, 200);
cv::Mat mat1(sz, type), mat2(sz, type);
cv::RNG rng(*ts->get_rng());
rng.fill(mat1, cv::RNG::UNIFORM, cv::Scalar::all(10), cv::Scalar::all(100));
rng.fill(mat2, cv::RNG::UNIFORM, cv::Scalar::all(10), cv::Scalar::all(100));
return test(mat1, mat2);
}
int CV_GpuArithmTest::CheckNorm(const Mat& m1, const Mat& m2)
{
double ret = norm(m1, m2, NORM_INF);
if (ret < std::numeric_limits<double>::epsilon())
return CvTS::OK;
ts->printf(CvTS::LOG, "\nNorm: %f\n", ret);
return CvTS::FAIL_GENERIC;
}
int CV_GpuArithmTest::CheckNorm(const Scalar& s1, const Scalar& s2)
{
double ret0 = CheckNorm(s1[0], s2[0]), ret1 = CheckNorm(s1[1], s2[1]), ret2 = CheckNorm(s1[2], s2[2]), ret3 = CheckNorm(s1[3], s2[3]);
return (ret0 == CvTS::OK && ret1 == CvTS::OK && ret2 == CvTS::OK && ret3 == CvTS::OK) ? CvTS::OK : CvTS::FAIL_GENERIC;
}
int CV_GpuArithmTest::CheckNorm(double d1, double d2)
{
double ret = ::fabs(d1 - d2);
if (ret < std::numeric_limits<double>::epsilon())
return CvTS::OK;
ts->printf(CvTS::LOG, "\nNorm: %f\n", ret);
return CvTS::FAIL_GENERIC;
}
void CV_GpuArithmTest::run( int )
{
int testResult = CvTS::OK;
try
{
const int types[] = {CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1};
const char* type_names[] = {"CV_8UC1", "CV_8UC3", "CV_8UC4", "CV_32FC1"};
const int type_count = sizeof(types)/sizeof(types[0]);
//run tests
for (int t = 0; t < type_count; ++t)
{
ts->printf(CvTS::LOG, "========Start test %s========\n", type_names[t]);
if (CvTS::OK == test(types[t]))
ts->printf(CvTS::LOG, "SUCCESS\n");
else
{
ts->printf(CvTS::LOG, "FAIL\n");
testResult = CvTS::FAIL_MISMATCH;
}
}
}
catch(const cv::Exception& e)
{
if (!check_and_treat_gpu_exception(e, ts))
throw;
return;
}
ts->set_failed_test_info(testResult);
}
////////////////////////////////////////////////////////////////////////////////
// Add
struct CV_GpuNppImageAddTest : public CV_GpuArithmTest
{
CV_GpuNppImageAddTest() : CV_GpuArithmTest( "GPU-NppImageAdd", "add" ) {}
virtual int test(const Mat& mat1, const Mat& mat2)
{
if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC4 && mat1.type() != CV_32FC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
cv::Mat cpuRes;
cv::add(mat1, mat2, cpuRes);
GpuMat gpu1(mat1);
GpuMat gpu2(mat2);
GpuMat gpuRes;
cv::gpu::add(gpu1, gpu2, gpuRes);
return CheckNorm(cpuRes, gpuRes);
}
};
////////////////////////////////////////////////////////////////////////////////
// Sub
struct CV_GpuNppImageSubtractTest : public CV_GpuArithmTest
{
CV_GpuNppImageSubtractTest() : CV_GpuArithmTest( "GPU-NppImageSubtract", "subtract" ) {}
int test( const Mat& mat1, const Mat& mat2 )
{
if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC4 && mat1.type() != CV_32FC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
cv::Mat cpuRes;
cv::subtract(mat1, mat2, cpuRes);
GpuMat gpu1(mat1);
GpuMat gpu2(mat2);
GpuMat gpuRes;
cv::gpu::subtract(gpu1, gpu2, gpuRes);
return CheckNorm(cpuRes, gpuRes);
}
};
////////////////////////////////////////////////////////////////////////////////
// multiply
struct CV_GpuNppImageMultiplyTest : public CV_GpuArithmTest
{
CV_GpuNppImageMultiplyTest() : CV_GpuArithmTest( "GPU-NppImageMultiply", "multiply" ) {}
int test( const Mat& mat1, const Mat& mat2 )
{
if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC4 && mat1.type() != CV_32FC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
cv::Mat cpuRes;
cv::multiply(mat1, mat2, cpuRes);
GpuMat gpu1(mat1);
GpuMat gpu2(mat2);
GpuMat gpuRes;
cv::gpu::multiply(gpu1, gpu2, gpuRes);
return CheckNorm(cpuRes, gpuRes);
}
};
////////////////////////////////////////////////////////////////////////////////
// divide
struct CV_GpuNppImageDivideTest : public CV_GpuArithmTest
{
CV_GpuNppImageDivideTest() : CV_GpuArithmTest( "GPU-NppImageDivide", "divide" ) {}
int test( const Mat& mat1, const Mat& mat2 )
{
if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC4 && mat1.type() != CV_32FC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
cv::Mat cpuRes;
cv::divide(mat1, mat2, cpuRes);
GpuMat gpu1(mat1);
GpuMat gpu2(mat2);
GpuMat gpuRes;
cv::gpu::divide(gpu1, gpu2, gpuRes);
return CheckNorm(cpuRes, gpuRes);
}
};
////////////////////////////////////////////////////////////////////////////////
// transpose
struct CV_GpuNppImageTransposeTest : public CV_GpuArithmTest
{
CV_GpuNppImageTransposeTest() : CV_GpuArithmTest( "GPU-NppImageTranspose", "transpose" ) {}
int test( const Mat& mat1, const Mat& )
{
if (mat1.type() != CV_8UC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
cv::Mat cpuRes;
cv::transpose(mat1, cpuRes);
GpuMat gpu1(mat1);
GpuMat gpuRes;
cv::gpu::transpose(gpu1, gpuRes);
return CheckNorm(cpuRes, gpuRes);
}
};
////////////////////////////////////////////////////////////////////////////////
// absdiff
struct CV_GpuNppImageAbsdiffTest : public CV_GpuArithmTest
{
CV_GpuNppImageAbsdiffTest() : CV_GpuArithmTest( "GPU-NppImageAbsdiff", "absdiff" ) {}
int test( const Mat& mat1, const Mat& mat2 )
{
if (mat1.type() != CV_8UC1 && mat1.type() != CV_32FC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
cv::Mat cpuRes;
cv::absdiff(mat1, mat2, cpuRes);
GpuMat gpu1(mat1);
GpuMat gpu2(mat2);
GpuMat gpuRes;
cv::gpu::absdiff(gpu1, gpu2, gpuRes);
return CheckNorm(cpuRes, gpuRes);
}
};
////////////////////////////////////////////////////////////////////////////////
// compare
struct CV_GpuNppImageCompareTest : public CV_GpuArithmTest
{
CV_GpuNppImageCompareTest() : CV_GpuArithmTest( "GPU-NppImageCompare", "compare" ) {}
int test( const Mat& mat1, const Mat& mat2 )
{
if (mat1.type() != CV_32FC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
int cmp_codes[] = {CMP_EQ, CMP_GT, CMP_GE, CMP_LT, CMP_LE, CMP_NE};
const char* cmp_str[] = {"CMP_EQ", "CMP_GT", "CMP_GE", "CMP_LT", "CMP_LE", "CMP_NE"};
int cmp_num = sizeof(cmp_codes) / sizeof(int);
int test_res = CvTS::OK;
for (int i = 0; i < cmp_num; ++i)
{
ts->printf(CvTS::LOG, "\nCompare operation: %s\n", cmp_str[i]);
cv::Mat cpuRes;
cv::compare(mat1, mat2, cpuRes, cmp_codes[i]);
GpuMat gpu1(mat1);
GpuMat gpu2(mat2);
GpuMat gpuRes;
cv::gpu::compare(gpu1, gpu2, gpuRes, cmp_codes[i]);
if (CheckNorm(cpuRes, gpuRes) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// meanStdDev
struct CV_GpuNppImageMeanStdDevTest : public CV_GpuArithmTest
{
CV_GpuNppImageMeanStdDevTest() : CV_GpuArithmTest( "GPU-NppImageMeanStdDev", "meanStdDev" ) {}
int test( const Mat& mat1, const Mat& )
{
if (mat1.type() != CV_8UC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
Scalar cpumean;
Scalar cpustddev;
cv::meanStdDev(mat1, cpumean, cpustddev);
GpuMat gpu1(mat1);
Scalar gpumean;
Scalar gpustddev;
cv::gpu::meanStdDev(gpu1, gpumean, gpustddev);
int test_res = CvTS::OK;
if (CheckNorm(cpumean, gpumean) != CvTS::OK)
{
ts->printf(CvTS::LOG, "\nMean FAILED\n");
test_res = CvTS::FAIL_GENERIC;
}
if (CheckNorm(cpustddev, gpustddev) != CvTS::OK)
{
ts->printf(CvTS::LOG, "\nStdDev FAILED\n");
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// norm
struct CV_GpuNppImageNormTest : public CV_GpuArithmTest
{
CV_GpuNppImageNormTest() : CV_GpuArithmTest( "GPU-NppImageNorm", "norm" ) {}
int test( const Mat& mat1, const Mat& mat2 )
{
if (mat1.type() != CV_8UC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
int norms[] = {NORM_INF, NORM_L1, NORM_L2};
const char* norms_str[] = {"NORM_INF", "NORM_L1", "NORM_L2"};
int norms_num = sizeof(norms) / sizeof(int);
int test_res = CvTS::OK;
for (int i = 0; i < norms_num; ++i)
{
ts->printf(CvTS::LOG, "\nNorm type: %s\n", norms_str[i]);
double cpu_norm = cv::norm(mat1, mat2, norms[i]);
GpuMat gpu1(mat1);
GpuMat gpu2(mat2);
double gpu_norm = cv::gpu::norm(gpu1, gpu2, norms[i]);
if (CheckNorm(cpu_norm, gpu_norm) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// flip
struct CV_GpuNppImageFlipTest : public CV_GpuArithmTest
{
CV_GpuNppImageFlipTest() : CV_GpuArithmTest( "GPU-NppImageFlip", "flip" ) {}
int test( const Mat& mat1, const Mat& )
{
if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC4)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
int flip_codes[] = {0, 1, -1};
const char* flip_axis[] = {"X", "Y", "Both"};
int flip_codes_num = sizeof(flip_codes) / sizeof(int);
int test_res = CvTS::OK;
for (int i = 0; i < flip_codes_num; ++i)
{
ts->printf(CvTS::LOG, "\nFlip Axis: %s\n", flip_axis[i]);
Mat cpu_res;
cv::flip(mat1, cpu_res, flip_codes[i]);
GpuMat gpu1(mat1);
GpuMat gpu_res;
cv::gpu::flip(gpu1, gpu_res, flip_codes[i]);
if (CheckNorm(cpu_res, gpu_res) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// sum
struct CV_GpuNppImageSumTest : public CV_GpuArithmTest
{
CV_GpuNppImageSumTest() : CV_GpuArithmTest( "GPU-NppImageSum", "sum" ) {}
int test( const Mat& mat1, const Mat& )
{
if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC4)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
Scalar cpures = cv::sum(mat1);
GpuMat gpu1(mat1);
Scalar gpures = cv::gpu::sum(gpu1);
return CheckNorm(cpures, gpures);
}
};
////////////////////////////////////////////////////////////////////////////////
// minNax
struct CV_GpuNppImageMinNaxTest : public CV_GpuArithmTest
{
CV_GpuNppImageMinNaxTest() : CV_GpuArithmTest( "GPU-NppImageMinNax", "minNax" ) {}
int test( const Mat& mat1, const Mat& )
{
if (mat1.type() != CV_8UC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
double cpumin, cpumax;
cv::minMaxLoc(mat1, &cpumin, &cpumax);
GpuMat gpu1(mat1);
double gpumin, gpumax;
cv::gpu::minMax(gpu1, &gpumin, &gpumax);
return (CheckNorm(cpumin, gpumin) == CvTS::OK && CheckNorm(cpumax, gpumax) == CvTS::OK) ? CvTS::OK : CvTS::FAIL_GENERIC;
}
};
////////////////////////////////////////////////////////////////////////////////
// LUT
struct CV_GpuNppImageLUTTest : public CV_GpuArithmTest
{
CV_GpuNppImageLUTTest() : CV_GpuArithmTest( "GPU-NppImageLUT", "LUT" ) {}
int test( const Mat& mat1, const Mat& )
{
if (mat1.type() != CV_8UC1 && mat1.type() != CV_8UC3)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
cv::Mat lut(1, 256, CV_8UC1);
cv::RNG rng(*ts->get_rng());
rng.fill(lut, cv::RNG::UNIFORM, cv::Scalar::all(100), cv::Scalar::all(200));
cv::Mat cpuRes;
cv::LUT(mat1, lut, cpuRes);
cv::gpu::GpuMat gpuRes;
cv::gpu::LUT(GpuMat(mat1), lut, gpuRes);
return CheckNorm(cpuRes, gpuRes);
}
};
/////////////////////////////////////////////////////////////////////////////
/////////////////// tests registration /////////////////////////////////////
/////////////////////////////////////////////////////////////////////////////
// If we comment some tests, we may foget/miss to uncomment it after.
// Placing all test definitions in one place
// makes us know about what tests are commented.
CV_GpuNppImageAddTest CV_GpuNppImageAdd_test;
CV_GpuNppImageSubtractTest CV_GpuNppImageSubtract_test;
CV_GpuNppImageMultiplyTest CV_GpuNppImageMultiply_test;
......
tests/gpu/src/gputest_main.cpp
View file @ e1e5047b
......@@ -46,6 +46,18 @@ CvTS test_system;
const char* blacklist[] =
{
"GPU-NppImageSum",
"GPU-MatOperatorAsyncCall",
//"GPU-NppErode",
//"GPU-NppDilate",
//"GPU-NppMorphologyEx",
//"GPU-NppImageDivide",
//"GPU-NppImageMeanStdDev",
//"GPU-NppImageMinNax",
//"GPU-NppImageResize",
//"GPU-NppImageWarpAffine",
//"GPU-NppImageWarpPerspective",
//"GPU-NppImageIntegral",
//"GPU-NppImageBlur",
0
};
......
tests/gpu/src/imgproc_gpu.cpp
View file @ e1e5047b
/*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.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 <iostream>
#include <cmath>
#include <limits>
#include "gputest.hpp"
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
using namespace cv;
using namespace std;
using namespace gpu;
class CV_GpuImageProcTest : public CvTest
{
public:
CV_GpuImageProcTest(const char* test_name, const char* test_funcs) : CvTest(test_name, test_funcs) {}
virtual ~CV_GpuImageProcTest() {}
protected:
void run(int);
int test8UC1 (const Mat& img);
int test8UC4 (const Mat& img);
int test32SC1(const Mat& img);
int test32FC1(const Mat& img);
virtual int test(const Mat& img) = 0;
int CheckNorm(const Mat& m1, const Mat& m2);
};
int CV_GpuImageProcTest::test8UC1(const Mat& img)
{
cv::Mat img_C1;
cvtColor(img, img_C1, CV_BGR2GRAY);
return test(img_C1);
}
int CV_GpuImageProcTest::test8UC4(const Mat& img)
{
cv::Mat img_C4;
cvtColor(img, img_C4, CV_BGR2BGRA);
return test(img_C4);
}
int CV_GpuImageProcTest::test32SC1(const Mat& img)
{
cv::Mat img_C1;
cvtColor(img, img_C1, CV_BGR2GRAY);
img_C1.convertTo(img_C1, CV_32S);
return test(img_C1);
}
int CV_GpuImageProcTest::test32FC1(const Mat& img)
{
cv::Mat temp, img_C1;
img.convertTo(temp, CV_32F);
cvtColor(temp, img_C1, CV_BGR2GRAY);
return test(img_C1);
}
int CV_GpuImageProcTest::CheckNorm(const Mat& m1, const Mat& m2)
{
double ret = norm(m1, m2, NORM_INF);
if (ret < std::numeric_limits<double>::epsilon())
{
return CvTS::OK;
}
else
{
ts->printf(CvTS::LOG, "\nNorm: %f\n", ret);
return CvTS::FAIL_GENERIC;
}
}
void CV_GpuImageProcTest::run( int )
{
//load image
cv::Mat img = cv::imread(std::string(ts->get_data_path()) + "stereobp/aloe-L.png");
if (img.empty())
{
ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA);
return;
}
int testResult = CvTS::OK;
try
{
//run tests
ts->printf(CvTS::LOG, "\n========Start test 8UC1========\n");
if (test8UC1(img) == CvTS::OK)
ts->printf(CvTS::LOG, "\nSUCCESS\n");
else
{
ts->printf(CvTS::LOG, "\nFAIL\n");
testResult = CvTS::FAIL_GENERIC;
}
ts->printf(CvTS::LOG, "\n========Start test 8UC4========\n");
if (test8UC4(img) == CvTS::OK)
ts->printf(CvTS::LOG, "\nSUCCESS\n");
else
{
ts->printf(CvTS::LOG, "\nFAIL\n");
testResult = CvTS::FAIL_GENERIC;
}
ts->printf(CvTS::LOG, "\n========Start test 32SC1========\n");
if (test32SC1(img) == CvTS::OK)
ts->printf(CvTS::LOG, "\nSUCCESS\n");
else
{
ts->printf(CvTS::LOG, "\nFAIL\n");
testResult = CvTS::FAIL_GENERIC;
}
ts->printf(CvTS::LOG, "\n========Start test 32FC1========\n");
if (test32FC1(img) == CvTS::OK)
ts->printf(CvTS::LOG, "\nSUCCESS\n");
else
{
ts->printf(CvTS::LOG, "\nFAIL\n");
testResult = CvTS::FAIL_GENERIC;
}
}
catch(const cv::Exception& e)
{
if (!check_and_treat_gpu_exception(e, ts))
throw;
return;
}
ts->set_failed_test_info(testResult);
}
////////////////////////////////////////////////////////////////////////////////
// threshold
struct CV_GpuNppImageThresholdTest : public CV_GpuImageProcTest
{
public:
CV_GpuNppImageThresholdTest() : CV_GpuImageProcTest( "GPU-NppImageThreshold", "threshold" ) {}
int test(const Mat& img)
{
if (img.type() != CV_32FC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
cv::RNG rng(*ts->get_rng());
const double thresh = rng;
cv::Mat cpuRes;
cv::threshold(img, cpuRes, thresh, 0.0, THRESH_TRUNC);
GpuMat gpu1(img);
GpuMat gpuRes;
cv::gpu::threshold(gpu1, gpuRes, thresh);
return CheckNorm(cpuRes, gpuRes);
}
};
////////////////////////////////////////////////////////////////////////////////
// resize
struct CV_GpuNppImageResizeTest : public CV_GpuImageProcTest
{
CV_GpuNppImageResizeTest() : CV_GpuImageProcTest( "GPU-NppImageResize", "resize" ) {}
int test(const Mat& img)
{
if (img.type() != CV_8UC1 && img.type() != CV_8UC4)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
int interpolations[] = {INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, INTER_LANCZOS4};
const char* interpolations_str[] = {"INTER_NEAREST", "INTER_LINEAR", "INTER_CUBIC", "INTER_LANCZOS4"};
int interpolations_num = sizeof(interpolations) / sizeof(int);
int test_res = CvTS::OK;
for (int i = 0; i < interpolations_num; ++i)
{
ts->printf(CvTS::LOG, "\nInterpolation type: %s\n", interpolations_str[i]);
Mat cpu_res;
cv::resize(img, cpu_res, Size(), 0.5, 0.5, interpolations[i]);
GpuMat gpu1(img), gpu_res;
cv::gpu::resize(gpu1, gpu_res, Size(), 0.5, 0.5, interpolations[i]);
if (CheckNorm(cpu_res, gpu_res) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// copyMakeBorder
struct CV_GpuNppImageCopyMakeBorderTest : public CV_GpuImageProcTest
{
CV_GpuNppImageCopyMakeBorderTest() : CV_GpuImageProcTest( "GPU-NppImageCopyMakeBorder", "copyMakeBorder" ) {}
int test(const Mat& img)
{
if (img.type() != CV_8UC1 && img.type() != CV_8UC4 && img.type() != CV_32SC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
cv::RNG rng(*ts->get_rng());
int top = rng.uniform(1, 10);
int botton = rng.uniform(1, 10);
int left = rng.uniform(1, 10);
int right = rng.uniform(1, 10);
cv::Scalar val(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
Mat cpudst;
cv::copyMakeBorder(img, cpudst, top, botton, left, right, BORDER_CONSTANT, val);
GpuMat gpu1(img);
GpuMat gpudst;
cv::gpu::copyMakeBorder(gpu1, gpudst, top, botton, left, right, val);
return CheckNorm(cpudst, gpudst);
}
};
////////////////////////////////////////////////////////////////////////////////
// warpAffine
struct CV_GpuNppImageWarpAffineTest : public CV_GpuImageProcTest
{
CV_GpuNppImageWarpAffineTest() : CV_GpuImageProcTest( "GPU-NppImageWarpAffine", "warpAffine" ) {}
int test(const Mat& img)
{
if (img.type() == CV_32SC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
static const double coeffs[2][3] =
{
{cos(3.14 / 6), -sin(3.14 / 6), 100.0},
{sin(3.14 / 6), cos(3.14 / 6), -100.0}
};
Mat M(2, 3, CV_64F, (void*)coeffs);
int flags[] = {INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, INTER_NEAREST | WARP_INVERSE_MAP, INTER_LINEAR | WARP_INVERSE_MAP, INTER_CUBIC | WARP_INVERSE_MAP};
const char* flags_str[] = {"INTER_NEAREST", "INTER_LINEAR", "INTER_CUBIC", "INTER_NEAREST | WARP_INVERSE_MAP", "INTER_LINEAR | WARP_INVERSE_MAP", "INTER_CUBIC | WARP_INVERSE_MAP"};
int flags_num = sizeof(flags) / sizeof(int);
int test_res = CvTS::OK;
for (int i = 0; i < flags_num; ++i)
{
ts->printf(CvTS::LOG, "\nFlags: %s\n", flags_str[i]);
Mat cpudst;
cv::warpAffine(img, cpudst, M, img.size(), flags[i]);
GpuMat gpu1(img);
GpuMat gpudst;
cv::gpu::warpAffine(gpu1, gpudst, M, gpu1.size(), flags[i]);
if (CheckNorm(cpudst, gpudst) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// warpPerspective
struct CV_GpuNppImageWarpPerspectiveTest : public CV_GpuImageProcTest
{
CV_GpuNppImageWarpPerspectiveTest() : CV_GpuImageProcTest( "GPU-NppImageWarpPerspective", "warpPerspective" ) {}
int test(const Mat& img)
{
if (img.type() == CV_32SC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
static const double coeffs[3][3] =
{
{cos(3.14 / 6), -sin(3.14 / 6), 100.0},
{sin(3.14 / 6), cos(3.14 / 6), -100.0},
{0.0, 0.0, 1.0}
};
Mat M(3, 3, CV_64F, (void*)coeffs);
int flags[] = {INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, INTER_NEAREST | WARP_INVERSE_MAP, INTER_LINEAR | WARP_INVERSE_MAP, INTER_CUBIC | WARP_INVERSE_MAP};
const char* flags_str[] = {"INTER_NEAREST", "INTER_LINEAR", "INTER_CUBIC", "INTER_NEAREST | WARP_INVERSE_MAP", "INTER_LINEAR | WARP_INVERSE_MAP", "INTER_CUBIC | WARP_INVERSE_MAP"};
int flags_num = sizeof(flags) / sizeof(int);
int test_res = CvTS::OK;
for (int i = 0; i < flags_num; ++i)
{
ts->printf(CvTS::LOG, "\nFlags: %s\n", flags_str[i]);
Mat cpudst;
cv::warpPerspective(img, cpudst, M, img.size(), flags[i]);
GpuMat gpu1(img);
GpuMat gpudst;
cv::gpu::warpPerspective(gpu1, gpudst, M, gpu1.size(), flags[i]);
if (CheckNorm(cpudst, gpudst) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// integral
struct CV_GpuNppImageIntegralTest : public CV_GpuImageProcTest
{
CV_GpuNppImageIntegralTest() : CV_GpuImageProcTest( "GPU-NppImageIntegral", "integral" ) {}
int CV_GpuNppImageIntegralTest::test(const Mat& img)
{
if (img.type() != CV_8UC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
Mat cpusum, cpusqsum;
cv::integral(img, cpusum, cpusqsum, CV_32S);
GpuMat gpu1(img);
GpuMat gpusum, gpusqsum;
cv::gpu::integral(gpu1, gpusum, gpusqsum);
gpusqsum.convertTo(gpusqsum, CV_64F);
int test_res = CvTS::OK;
if (CheckNorm(cpusum, gpusum) != CvTS::OK)
{
ts->printf(CvTS::LOG, "\nSum failed\n");
test_res = CvTS::FAIL_GENERIC;
}
if (CheckNorm(cpusqsum, gpusqsum) != CvTS::OK)
{
ts->printf(CvTS::LOG, "\nSquared sum failed\n");
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// blur
struct CV_GpuNppImageBlurTest : public CV_GpuImageProcTest
{
CV_GpuNppImageBlurTest() : CV_GpuImageProcTest( "GPU-NppImageBlur", "blur" ) {}
int test(const Mat& img)
{
if (img.type() != CV_8UC1 && img.type() != CV_8UC4)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
int ksizes[] = {3, 5, 7};
int ksizes_num = sizeof(ksizes) / sizeof(int);
int test_res = CvTS::OK;
for (int i = 0; i < ksizes_num; ++i)
{
ts->printf(CvTS::LOG, "\nksize = %d\n", ksizes[i]);
Mat cpudst;
cv::blur(img, cpudst, Size(ksizes[i], ksizes[i]));
GpuMat gpu1(img);
GpuMat gpudst;
cv::gpu::blur(gpu1, gpudst, Size(ksizes[i], ksizes[i]));
cv::Mat c;
cv::absdiff(cpudst, gpudst, c);
if (CheckNorm(cpudst, gpudst) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// cvtColor
class CV_GpuCvtColorTest : public CvTest
{
public:
CV_GpuCvtColorTest() : CvTest("GPU-NppCvtColor", "cvtColor") {}
~CV_GpuCvtColorTest() {};
protected:
void run(int);
int CheckNorm(const Mat& m1, const Mat& m2);
};
int CV_GpuCvtColorTest::CheckNorm(const Mat& m1, const Mat& m2)
{
double ret = norm(m1, m2, NORM_INF);
if (ret < std::numeric_limits<double>::epsilon())
{
return CvTS::OK;
}
else
{
ts->printf(CvTS::LOG, "\nNorm: %f\n", ret);
return CvTS::FAIL_GENERIC;
}
}
void CV_GpuCvtColorTest::run( int )
{
//load image
cv::Mat img = cv::imread(std::string(ts->get_data_path()) + "stereobp/aloe-L.png");
if (img.empty())
{
ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA);
return;
}
int testResult = CvTS::OK;
cv::Mat cpuRes;
cv::gpu::GpuMat gpuImg(img), gpuRes;
try
{
//run tests
int codes[] = {CV_BGR2RGB, CV_RGB2YCrCb, CV_YCrCb2RGB, CV_RGB2RGBA, CV_RGBA2BGRA, CV_BGRA2GRAY, CV_GRAY2RGB};
const char* codes_str[] = {"CV_BGR2RGB", "CV_RGB2YCrCb", "CV_YCrCb2RGB", "CV_RGB2RGBA", "CV_RGBA2BGRA", "CV_BGRA2GRAY", "CV_GRAY2RGB"};
int codes_num = sizeof(codes) / sizeof(int);
for (int i = 0; i < codes_num; ++i)
{
ts->printf(CvTS::LOG, "\n%s\n", codes_str[i]);
cv::cvtColor(img, cpuRes, codes[i]);
cv::gpu::cvtColor(gpuImg, gpuRes, codes[i]);
if (CheckNorm(cpuRes, gpuRes) == CvTS::OK)
ts->printf(CvTS::LOG, "\nSUCCESS\n");
else
{
ts->printf(CvTS::LOG, "\nFAIL\n");
testResult = CvTS::FAIL_GENERIC;
}
img = cpuRes;
gpuImg = gpuRes;
}
}
catch(const cv::Exception& e)
{
if (!check_and_treat_gpu_exception(e, ts))
throw;
return;
}
ts->set_failed_test_info(testResult);
}
/////////////////////////////////////////////////////////////////////////////
/////////////////// tests registration /////////////////////////////////////
/////////////////////////////////////////////////////////////////////////////
// If we comment some tests, we may foget/miss to uncomment it after.
// Placing all test definitions in one place
// makes us know about what tests are commented.
/*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.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 <iostream>
#include <cmath>
#include <limits>
#include "gputest.hpp"
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
using namespace cv;
using namespace std;
using namespace gpu;
class CV_GpuImageProcTest : public CvTest
{
public:
CV_GpuImageProcTest(const char* test_name, const char* test_funcs) : CvTest(test_name, test_funcs) {}
virtual ~CV_GpuImageProcTest() {}
protected:
void run(int);
int test8UC1 (const Mat& img);
int test8UC4 (const Mat& img);
int test32SC1(const Mat& img);
int test32FC1(const Mat& img);
virtual int test(const Mat& img) = 0;
int CheckNorm(const Mat& m1, const Mat& m2);
};
int CV_GpuImageProcTest::test8UC1(const Mat& img)
{
cv::Mat img_C1;
cvtColor(img, img_C1, CV_BGR2GRAY);
return test(img_C1);
}
int CV_GpuImageProcTest::test8UC4(const Mat& img)
{
cv::Mat img_C4;
cvtColor(img, img_C4, CV_BGR2BGRA);
return test(img_C4);
}
int CV_GpuImageProcTest::test32SC1(const Mat& img)
{
cv::Mat img_C1;
cvtColor(img, img_C1, CV_BGR2GRAY);
img_C1.convertTo(img_C1, CV_32S);
return test(img_C1);
}
int CV_GpuImageProcTest::test32FC1(const Mat& img)
{
cv::Mat temp, img_C1;
img.convertTo(temp, CV_32F);
cvtColor(temp, img_C1, CV_BGR2GRAY);
return test(img_C1);
}
int CV_GpuImageProcTest::CheckNorm(const Mat& m1, const Mat& m2)
{
double ret = norm(m1, m2, NORM_INF);
if (ret < std::numeric_limits<double>::epsilon())
{
return CvTS::OK;
}
else
{
ts->printf(CvTS::LOG, "\nNorm: %f\n", ret);
return CvTS::FAIL_GENERIC;
}
}
void CV_GpuImageProcTest::run( int )
{
//load image
cv::Mat img = cv::imread(std::string(ts->get_data_path()) + "stereobp/aloe-L.png");
if (img.empty())
{
ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA);
return;
}
int testResult = CvTS::OK;
try
{
//run tests
ts->printf(CvTS::LOG, "\n========Start test 8UC1========\n");
if (test8UC1(img) == CvTS::OK)
ts->printf(CvTS::LOG, "\nSUCCESS\n");
else
{
ts->printf(CvTS::LOG, "\nFAIL\n");
testResult = CvTS::FAIL_GENERIC;
}
ts->printf(CvTS::LOG, "\n========Start test 8UC4========\n");
if (test8UC4(img) == CvTS::OK)
ts->printf(CvTS::LOG, "\nSUCCESS\n");
else
{
ts->printf(CvTS::LOG, "\nFAIL\n");
testResult = CvTS::FAIL_GENERIC;
}
ts->printf(CvTS::LOG, "\n========Start test 32SC1========\n");
if (test32SC1(img) == CvTS::OK)
ts->printf(CvTS::LOG, "\nSUCCESS\n");
else
{
ts->printf(CvTS::LOG, "\nFAIL\n");
testResult = CvTS::FAIL_GENERIC;
}
ts->printf(CvTS::LOG, "\n========Start test 32FC1========\n");
if (test32FC1(img) == CvTS::OK)
ts->printf(CvTS::LOG, "\nSUCCESS\n");
else
{
ts->printf(CvTS::LOG, "\nFAIL\n");
testResult = CvTS::FAIL_GENERIC;
}
}
catch(const cv::Exception& e)
{
if (!check_and_treat_gpu_exception(e, ts))
throw;
return;
}
ts->set_failed_test_info(testResult);
}
////////////////////////////////////////////////////////////////////////////////
// threshold
struct CV_GpuNppImageThresholdTest : public CV_GpuImageProcTest
{
public:
CV_GpuNppImageThresholdTest() : CV_GpuImageProcTest( "GPU-NppImageThreshold", "threshold" ) {}
int test(const Mat& img)
{
if (img.type() != CV_32FC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
cv::RNG rng(*ts->get_rng());
const double thresh = rng;
cv::Mat cpuRes;
cv::threshold(img, cpuRes, thresh, 0.0, THRESH_TRUNC);
GpuMat gpu1(img);
GpuMat gpuRes;
cv::gpu::threshold(gpu1, gpuRes, thresh);
return CheckNorm(cpuRes, gpuRes);
}
};
////////////////////////////////////////////////////////////////////////////////
// resize
struct CV_GpuNppImageResizeTest : public CV_GpuImageProcTest
{
CV_GpuNppImageResizeTest() : CV_GpuImageProcTest( "GPU-NppImageResize", "resize" ) {}
int test(const Mat& img)
{
if (img.type() != CV_8UC1 && img.type() != CV_8UC4)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
int interpolations[] = {INTER_NEAREST, INTER_LINEAR, /*INTER_CUBIC,*/ /*INTER_LANCZOS4*/};
const char* interpolations_str[] = {"INTER_NEAREST", "INTER_LINEAR", /*"INTER_CUBIC",*/ /*"INTER_LANCZOS4"*/};
int interpolations_num = sizeof(interpolations) / sizeof(int);
int test_res = CvTS::OK;
for (int i = 0; i < interpolations_num; ++i)
{
ts->printf(CvTS::LOG, "\nInterpolation type: %s\n", interpolations_str[i]);
Mat cpu_res;
cv::resize(img, cpu_res, Size(), 0.5, 0.5, interpolations[i]);
GpuMat gpu1(img), gpu_res;
cv::gpu::resize(gpu1, gpu_res, Size(), 0.5, 0.5, interpolations[i]);
if (CheckNorm(cpu_res, gpu_res) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// copyMakeBorder
struct CV_GpuNppImageCopyMakeBorderTest : public CV_GpuImageProcTest
{
CV_GpuNppImageCopyMakeBorderTest() : CV_GpuImageProcTest( "GPU-NppImageCopyMakeBorder", "copyMakeBorder" ) {}
int test(const Mat& img)
{
if (img.type() != CV_8UC1 && img.type() != CV_8UC4 && img.type() != CV_32SC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
cv::RNG rng(*ts->get_rng());
int top = rng.uniform(1, 10);
int botton = rng.uniform(1, 10);
int left = rng.uniform(1, 10);
int right = rng.uniform(1, 10);
cv::Scalar val(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
Mat cpudst;
cv::copyMakeBorder(img, cpudst, top, botton, left, right, BORDER_CONSTANT, val);
GpuMat gpu1(img);
GpuMat gpudst;
cv::gpu::copyMakeBorder(gpu1, gpudst, top, botton, left, right, val);
return CheckNorm(cpudst, gpudst);
}
};
////////////////////////////////////////////////////////////////////////////////
// warpAffine
struct CV_GpuNppImageWarpAffineTest : public CV_GpuImageProcTest
{
CV_GpuNppImageWarpAffineTest() : CV_GpuImageProcTest( "GPU-NppImageWarpAffine", "warpAffine" ) {}
int test(const Mat& img)
{
if (img.type() == CV_32SC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
static const double coeffs[2][3] =
{
{cos(3.14 / 6), -sin(3.14 / 6), 100.0},
{sin(3.14 / 6), cos(3.14 / 6), -100.0}
};
Mat M(2, 3, CV_64F, (void*)coeffs);
int flags[] = {INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, INTER_NEAREST | WARP_INVERSE_MAP, INTER_LINEAR | WARP_INVERSE_MAP, INTER_CUBIC | WARP_INVERSE_MAP};
const char* flags_str[] = {"INTER_NEAREST", "INTER_LINEAR", "INTER_CUBIC", "INTER_NEAREST | WARP_INVERSE_MAP", "INTER_LINEAR | WARP_INVERSE_MAP", "INTER_CUBIC | WARP_INVERSE_MAP"};
int flags_num = sizeof(flags) / sizeof(int);
int test_res = CvTS::OK;
for (int i = 0; i < flags_num; ++i)
{
ts->printf(CvTS::LOG, "\nFlags: %s\n", flags_str[i]);
Mat cpudst;
cv::warpAffine(img, cpudst, M, img.size(), flags[i]);
GpuMat gpu1(img);
GpuMat gpudst;
cv::gpu::warpAffine(gpu1, gpudst, M, gpu1.size(), flags[i]);
if (CheckNorm(cpudst, gpudst) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// warpPerspective
struct CV_GpuNppImageWarpPerspectiveTest : public CV_GpuImageProcTest
{
CV_GpuNppImageWarpPerspectiveTest() : CV_GpuImageProcTest( "GPU-NppImageWarpPerspective", "warpPerspective" ) {}
int test(const Mat& img)
{
if (img.type() == CV_32SC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
static const double coeffs[3][3] =
{
{cos(3.14 / 6), -sin(3.14 / 6), 100.0},
{sin(3.14 / 6), cos(3.14 / 6), -100.0},
{0.0, 0.0, 1.0}
};
Mat M(3, 3, CV_64F, (void*)coeffs);
int flags[] = {INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, INTER_NEAREST | WARP_INVERSE_MAP, INTER_LINEAR | WARP_INVERSE_MAP, INTER_CUBIC | WARP_INVERSE_MAP};
const char* flags_str[] = {"INTER_NEAREST", "INTER_LINEAR", "INTER_CUBIC", "INTER_NEAREST | WARP_INVERSE_MAP", "INTER_LINEAR | WARP_INVERSE_MAP", "INTER_CUBIC | WARP_INVERSE_MAP"};
int flags_num = sizeof(flags) / sizeof(int);
int test_res = CvTS::OK;
for (int i = 0; i < flags_num; ++i)
{
ts->printf(CvTS::LOG, "\nFlags: %s\n", flags_str[i]);
Mat cpudst;
cv::warpPerspective(img, cpudst, M, img.size(), flags[i]);
GpuMat gpu1(img);
GpuMat gpudst;
cv::gpu::warpPerspective(gpu1, gpudst, M, gpu1.size(), flags[i]);
if (CheckNorm(cpudst, gpudst) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// integral
struct CV_GpuNppImageIntegralTest : public CV_GpuImageProcTest
{
CV_GpuNppImageIntegralTest() : CV_GpuImageProcTest( "GPU-NppImageIntegral", "integral" ) {}
int CV_GpuNppImageIntegralTest::test(const Mat& img)
{
if (img.type() != CV_8UC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
Mat cpusum, cpusqsum;
cv::integral(img, cpusum, cpusqsum, CV_32S);
GpuMat gpu1(img);
GpuMat gpusum, gpusqsum;
cv::gpu::integral(gpu1, gpusum, gpusqsum);
gpusqsum.convertTo(gpusqsum, CV_64F);
int test_res = CvTS::OK;
if (CheckNorm(cpusum, gpusum) != CvTS::OK)
{
ts->printf(CvTS::LOG, "\nSum failed\n");
test_res = CvTS::FAIL_GENERIC;
}
if (CheckNorm(cpusqsum, gpusqsum) != CvTS::OK)
{
ts->printf(CvTS::LOG, "\nSquared sum failed\n");
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// blur
struct CV_GpuNppImageBlurTest : public CV_GpuImageProcTest
{
CV_GpuNppImageBlurTest() : CV_GpuImageProcTest( "GPU-NppImageBlur", "blur" ) {}
int test(const Mat& img)
{
if (img.type() != CV_8UC1 && img.type() != CV_8UC4)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
int ksizes[] = {3, 5, 7};
int ksizes_num = sizeof(ksizes) / sizeof(int);
int test_res = CvTS::OK;
for (int i = 0; i < ksizes_num; ++i)
{
ts->printf(CvTS::LOG, "\nksize = %d\n", ksizes[i]);
Mat cpudst;
cv::blur(img, cpudst, Size(ksizes[i], ksizes[i]));
GpuMat gpu1(img);
GpuMat gpudst;
cv::gpu::blur(gpu1, gpudst, Size(ksizes[i], ksizes[i]));
if (CheckNorm(cpudst, gpudst) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// cvtColor
class CV_GpuCvtColorTest : public CvTest
{
public:
CV_GpuCvtColorTest() : CvTest("GPU-CvtColor", "cvtColor") {}
~CV_GpuCvtColorTest() {};
protected:
void run(int);
int CheckNorm(const Mat& m1, const Mat& m2);
};
int CV_GpuCvtColorTest::CheckNorm(const Mat& m1, const Mat& m2)
{
double ret = norm(m1, m2, NORM_INF);
if (ret < std::numeric_limits<double>::epsilon())
{
return CvTS::OK;
}
else
{
ts->printf(CvTS::LOG, "\nNorm: %f\n", ret);
return CvTS::FAIL_GENERIC;
}
}
void CV_GpuCvtColorTest::run( int )
{
//load image
cv::Mat img = cv::imread(std::string(ts->get_data_path()) + "stereobp/aloe-L.png");
if (img.empty())
{
ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA);
return;
}
int testResult = CvTS::OK;
cv::Mat cpuRes;
cv::gpu::GpuMat gpuImg(img), gpuRes;
try
{
//run tests
int codes[] = { CV_BGR2RGB, /* CV_RGB2YCrCb, CV_YCrCb2RGB,*/ CV_RGB2RGBA, CV_RGBA2BGRA, CV_BGRA2GRAY, CV_GRAY2RGB, CV_RGB2BGR555/*, CV_BGR5552BGR/*, CV_BGR2BGR565, CV_BGR5652RGB*/};
const char* codes_str[] = {"CV_BGR2RGB", /*"CV_RGB2YCrCb", "CV_YCrCb2RGB",*/ "CV_RGB2RGBA", "CV_RGBA2BGRA", "CV_BGRA2GRAY", "CV_GRAY2RGB", "CV_RGB2BGR555"/*, "CV_BGR5552BGR"/*, "CV_BGR2BGR565", "CV_BGR5652RGB"*/};
int codes_num = sizeof(codes) / sizeof(int);
for (int i = 0; i < codes_num; ++i)
{
ts->printf(CvTS::LOG, "\n%s\n", codes_str[i]);
cv::cvtColor(img, cpuRes, codes[i]);
cv::gpu::cvtColor(gpuImg, gpuRes, codes[i]);
if (CheckNorm(cpuRes, gpuRes) == CvTS::OK)
ts->printf(CvTS::LOG, "\nSUCCESS\n");
else
{
ts->printf(CvTS::LOG, "\nFAIL\n");
testResult = CvTS::FAIL_GENERIC;
}
img = cpuRes;
gpuImg = gpuRes;
}
}
catch(const cv::Exception& e)
{
if (!check_and_treat_gpu_exception(e, ts))
throw;
return;
}
ts->set_failed_test_info(testResult);
}
/////////////////////////////////////////////////////////////////////////////
/////////////////// tests registration /////////////////////////////////////
/////////////////////////////////////////////////////////////////////////////
// If we comment some tests, we may foget/miss to uncomment it after.
// Placing all test definitions in one place
// makes us know about what tests are commented.
CV_GpuNppImageThresholdTest CV_GpuNppImageThreshold_test;
CV_GpuNppImageResizeTest CV_GpuNppImageResize_test;
CV_GpuNppImageCopyMakeBorderTest CV_GpuNppImageCopyMakeBorder_test;
......
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