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#include "opencv2/opencv_modules.hpp"
#if defined(HAVE_OPENCV_CUDAARITHM) && defined(HAVE_OPENCV_CUDAWARPING) && defined(HAVE_OPENCV_CUDAFILTERS)
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/vec_traits.hpp"
#include "opencv2/core/cuda/vec_math.hpp"
using namespace cv::cuda;
using namespace cv::cuda::device;
namespace btv_l1_cudev
{
void buildMotionMaps(PtrStepSzf forwardMotionX, PtrStepSzf forwardMotionY,
PtrStepSzf backwardMotionX, PtrStepSzf bacwardMotionY,
PtrStepSzf forwardMapX, PtrStepSzf forwardMapY,
PtrStepSzf backwardMapX, PtrStepSzf backwardMapY);
template <int cn>
void upscale(const PtrStepSzb src, PtrStepSzb dst, int scale, cudaStream_t stream);
void diffSign(PtrStepSzf src1, PtrStepSzf src2, PtrStepSzf dst, cudaStream_t stream);
void loadBtvWeights(const float* weights, size_t count);
template <int cn> void calcBtvRegularization(PtrStepSzb src, PtrStepSzb dst, int ksize);
}
namespace btv_l1_cudev
{
__global__ void buildMotionMapsKernel(const PtrStepSzf forwardMotionX, const PtrStepf forwardMotionY,
PtrStepf backwardMotionX, PtrStepf backwardMotionY,
PtrStepf forwardMapX, PtrStepf forwardMapY,
PtrStepf backwardMapX, PtrStepf backwardMapY)
{
const int x = blockIdx.x * blockDim.x + threadIdx.x;
const int y = blockIdx.y * blockDim.y + threadIdx.y;
if (x >= forwardMotionX.cols || y >= forwardMotionX.rows)
return;
const float fx = forwardMotionX(y, x);
const float fy = forwardMotionY(y, x);
const float bx = backwardMotionX(y, x);
const float by = backwardMotionY(y, x);
forwardMapX(y, x) = x + bx;
forwardMapY(y, x) = y + by;
backwardMapX(y, x) = x + fx;
backwardMapY(y, x) = y + fy;
}
void buildMotionMaps(PtrStepSzf forwardMotionX, PtrStepSzf forwardMotionY,
PtrStepSzf backwardMotionX, PtrStepSzf bacwardMotionY,
PtrStepSzf forwardMapX, PtrStepSzf forwardMapY,
PtrStepSzf backwardMapX, PtrStepSzf backwardMapY)
{
const dim3 block(32, 8);
const dim3 grid(divUp(forwardMapX.cols, block.x), divUp(forwardMapX.rows, block.y));
buildMotionMapsKernel<<<grid, block>>>(forwardMotionX, forwardMotionY,
backwardMotionX, bacwardMotionY,
forwardMapX, forwardMapY,
backwardMapX, backwardMapY);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaDeviceSynchronize() );
}
template <typename T>
__global__ void upscaleKernel(const PtrStepSz<T> src, PtrStep<T> dst, const int scale)
{
const int x = blockIdx.x * blockDim.x + threadIdx.x;
const int y = blockIdx.y * blockDim.y + threadIdx.y;
if (x >= src.cols || y >= src.rows)
return;
dst(y * scale, x * scale) = src(y, x);
}
template <int cn>
void upscale(const PtrStepSzb src, PtrStepSzb dst, int scale, cudaStream_t stream)
{
typedef typename TypeVec<float, cn>::vec_type src_t;
const dim3 block(32, 8);
const dim3 grid(divUp(src.cols, block.x), divUp(src.rows, block.y));
upscaleKernel<src_t><<<grid, block, 0, stream>>>((PtrStepSz<src_t>) src, (PtrStepSz<src_t>) dst, scale);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
template void upscale<1>(const PtrStepSzb src, PtrStepSzb dst, int scale, cudaStream_t stream);
template void upscale<3>(const PtrStepSzb src, PtrStepSzb dst, int scale, cudaStream_t stream);
template void upscale<4>(const PtrStepSzb src, PtrStepSzb dst, int scale, cudaStream_t stream);
__device__ __forceinline__ float diffSign(float a, float b)
{
return a > b ? 1.0f : a < b ? -1.0f : 0.0f;
}
__device__ __forceinline__ float3 diffSign(const float3& a, const float3& b)
{
return make_float3(
a.x > b.x ? 1.0f : a.x < b.x ? -1.0f : 0.0f,
a.y > b.y ? 1.0f : a.y < b.y ? -1.0f : 0.0f,
a.z > b.z ? 1.0f : a.z < b.z ? -1.0f : 0.0f
);
}
__device__ __forceinline__ float4 diffSign(const float4& a, const float4& b)
{
return make_float4(
a.x > b.x ? 1.0f : a.x < b.x ? -1.0f : 0.0f,
a.y > b.y ? 1.0f : a.y < b.y ? -1.0f : 0.0f,
a.z > b.z ? 1.0f : a.z < b.z ? -1.0f : 0.0f,
0.0f
);
}
struct DiffSign : binary_function<float, float, float>
{
__device__ __forceinline__ float operator ()(float a, float b) const
{
return diffSign(a, b);
}
};
}
namespace cv { namespace cuda { namespace device
{
template <> struct TransformFunctorTraits<btv_l1_cudev::DiffSign> : DefaultTransformFunctorTraits<btv_l1_cudev::DiffSign>
{
enum { smart_block_dim_y = 8 };
enum { smart_shift = 4 };
};
}}}
namespace btv_l1_cudev
{
void diffSign(PtrStepSzf src1, PtrStepSzf src2, PtrStepSzf dst, cudaStream_t stream)
{
transform(src1, src2, dst, DiffSign(), WithOutMask(), stream);
}
__constant__ float c_btvRegWeights[16*16];
template <typename T>
__global__ void calcBtvRegularizationKernel(const PtrStepSz<T> src, PtrStep<T> dst, const int ksize)
{
const int x = blockIdx.x * blockDim.x + threadIdx.x + ksize;
const int y = blockIdx.y * blockDim.y + threadIdx.y + ksize;
if (y >= src.rows - ksize || x >= src.cols - ksize)
return;
const T srcVal = src(y, x);
T dstVal = VecTraits<T>::all(0);
for (int m = 0, count = 0; m <= ksize; ++m)
{
for (int l = ksize; l + m >= 0; --l, ++count)
dstVal = dstVal + c_btvRegWeights[count] * (diffSign(srcVal, src(y + m, x + l)) - diffSign(src(y - m, x - l), srcVal));
}
dst(y, x) = dstVal;
}
void loadBtvWeights(const float* weights, size_t count)
{
cudaSafeCall( cudaMemcpyToSymbol(c_btvRegWeights, weights, count * sizeof(float)) );
}
template <int cn>
void calcBtvRegularization(PtrStepSzb src, PtrStepSzb dst, int ksize)
{
typedef typename TypeVec<float, cn>::vec_type src_t;
const dim3 block(32, 8);
const dim3 grid(divUp(src.cols, block.x), divUp(src.rows, block.y));
calcBtvRegularizationKernel<src_t><<<grid, block>>>((PtrStepSz<src_t>) src, (PtrStepSz<src_t>) dst, ksize);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaDeviceSynchronize() );
}
template void calcBtvRegularization<1>(PtrStepSzb src, PtrStepSzb dst, int ksize);
template void calcBtvRegularization<3>(PtrStepSzb src, PtrStepSzb dst, int ksize);
template void calcBtvRegularization<4>(PtrStepSzb src, PtrStepSzb dst, int ksize);
}
#endif