utility.hpp

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#ifndef OPENCV_CUDA_UTILITY_HPP
#define OPENCV_CUDA_UTILITY_HPP
 
#include "saturate_cast.hpp"
#include "datamov_utils.hpp"
 
 
namespace cv { namespace cuda { namespace device
{
    struct CV_EXPORTS ThrustAllocator
    {
        typedef uchar value_type;
        virtual ~ThrustAllocator();
        virtual __device__ __host__ uchar* allocate(size_t numBytes) = 0;
        virtual __device__ __host__ void deallocate(uchar* ptr, size_t numBytes) = 0;
        static ThrustAllocator& getAllocator();
        static void setAllocator(ThrustAllocator* allocator);
    };
    #define OPENCV_CUDA_LOG_WARP_SIZE        (5)
    #define OPENCV_CUDA_WARP_SIZE            (1 << OPENCV_CUDA_LOG_WARP_SIZE)
    #define OPENCV_CUDA_LOG_MEM_BANKS        ((__CUDA_ARCH__ >= 200) ? 5 : 4) // 32 banks on fermi, 16 on tesla
    #define OPENCV_CUDA_MEM_BANKS            (1 << OPENCV_CUDA_LOG_MEM_BANKS)
 
    // swap
 
    template <typename T> void __device__ __host__ __forceinline__ swap(T& a, T& b)
    {
        const T temp = a;
        a = b;
        b = temp;
    }
 
    // Mask Reader
 
    struct SingleMask
    {
        explicit __host__ __device__ __forceinline__ SingleMask(PtrStepb mask_) : mask(mask_) {}
        __host__ __device__ __forceinline__ SingleMask(const SingleMask& mask_): mask(mask_.mask){}
 
        __device__ __forceinline__ bool operator()(int y, int x) const
        {
            return mask.ptr(y)[x] != 0;
        }
 
        PtrStepb mask;
    };
 
    struct SingleMaskChannels
    {
        __host__ __device__ __forceinline__ SingleMaskChannels(PtrStepb mask_, int channels_)
        : mask(mask_), channels(channels_) {}
        __host__ __device__ __forceinline__ SingleMaskChannels(const SingleMaskChannels& mask_)
            :mask(mask_.mask), channels(mask_.channels){}
 
        __device__ __forceinline__ bool operator()(int y, int x) const
        {
            return mask.ptr(y)[x / channels] != 0;
        }
 
        PtrStepb mask;
        int channels;
    };
 
    struct MaskCollection
    {
        explicit __host__ __device__ __forceinline__ MaskCollection(PtrStepb* maskCollection_)
            : maskCollection(maskCollection_) {}
 
        __device__ __forceinline__ MaskCollection(const MaskCollection& masks_)
            : maskCollection(masks_.maskCollection), curMask(masks_.curMask){}
 
        __device__ __forceinline__ void next()
        {
            curMask = *maskCollection++;
        }
        __device__ __forceinline__ void setMask(int z)
        {
            curMask = maskCollection[z];
        }
 
        __device__ __forceinline__ bool operator()(int y, int x) const
        {
            uchar val;
            return curMask.data == 0 || (ForceGlob<uchar>::Load(curMask.ptr(y), x, val), (val != 0));
        }
 
        const PtrStepb* maskCollection;
        PtrStepb curMask;
    };
 
    struct WithOutMask
    {
        __host__ __device__ __forceinline__ WithOutMask(){}
        __host__ __device__ __forceinline__ WithOutMask(const WithOutMask&){}
 
        __device__ __forceinline__ void next() const
        {
        }
        __device__ __forceinline__ void setMask(int) const
        {
        }
 
        __device__ __forceinline__ bool operator()(int, int) const
        {
            return true;
        }
 
        __device__ __forceinline__ bool operator()(int, int, int) const
        {
            return true;
        }
 
        static __device__ __forceinline__ bool check(int, int)
        {
            return true;
        }
 
        static __device__ __forceinline__ bool check(int, int, int)
        {
            return true;
        }
    };
 
    // Solve linear system
 
    // solve 2x2 linear system Ax=b
    template <typename T> __device__ __forceinline__ bool solve2x2(const T A[2][2], const T b[2], T x[2])
    {
        T det = A[0][0] * A[1][1] - A[1][0] * A[0][1];
 
        if (det != 0)
        {
            double invdet = 1.0 / det;
 
            x[0] = saturate_cast<T>(invdet * (b[0] * A[1][1] - b[1] * A[0][1]));
 
            x[1] = saturate_cast<T>(invdet * (A[0][0] * b[1] - A[1][0] * b[0]));
 
            return true;
        }
 
        return false;
    }
 
    // solve 3x3 linear system Ax=b
    template <typename T> __device__ __forceinline__ bool solve3x3(const T A[3][3], const T b[3], T x[3])
    {
        T det = A[0][0] * (A[1][1] * A[2][2] - A[1][2] * A[2][1])
              - A[0][1] * (A[1][0] * A[2][2] - A[1][2] * A[2][0])
              + A[0][2] * (A[1][0] * A[2][1] - A[1][1] * A[2][0]);
 
        if (det != 0)
        {
            double invdet = 1.0 / det;
 
            x[0] = saturate_cast<T>(invdet *
                (b[0]    * (A[1][1] * A[2][2] - A[1][2] * A[2][1]) -
                 A[0][1] * (b[1]    * A[2][2] - A[1][2] * b[2]   ) +
                 A[0][2] * (b[1]    * A[2][1] - A[1][1] * b[2]   )));
 
            x[1] = saturate_cast<T>(invdet *
                (A[0][0] * (b[1]    * A[2][2] - A[1][2] * b[2]   ) -
                 b[0]    * (A[1][0] * A[2][2] - A[1][2] * A[2][0]) +
                 A[0][2] * (A[1][0] * b[2]    - b[1]    * A[2][0])));
 
            x[2] = saturate_cast<T>(invdet *
                (A[0][0] * (A[1][1] * b[2]    - b[1]    * A[2][1]) -
                 A[0][1] * (A[1][0] * b[2]    - b[1]    * A[2][0]) +
                 b[0]    * (A[1][0] * A[2][1] - A[1][1] * A[2][0])));
 
            return true;
        }
 
        return false;
    }
}}} // namespace cv { namespace cuda { namespace cudev
 
 
#endif // OPENCV_CUDA_UTILITY_HPP