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#include "internal_shared.hpp"
#include "opencv2/gpu/device/limits.hpp"

namespace cv { namespace gpu { namespace device
{
    namespace bilateral_filter
    {
        __constant__ float* ctable_color;
        __constant__ float* ctable_space;
        __constant__ size_t ctable_space_step;

        __constant__ int cndisp;
        __constant__ int cradius;

        __constant__ short cedge_disc;
        __constant__ short cmax_disc;

        void load_constants(float* table_color, DevMem2Df table_space, int ndisp, int radius, short edge_disc, short max_disc)
        {
            cudaSafeCall( cudaMemcpyToSymbol(ctable_color, &table_color, sizeof(table_color)) );
            cudaSafeCall( cudaMemcpyToSymbol(ctable_space, &table_space.data, sizeof(table_space.data)) );
            size_t table_space_step = table_space.step / sizeof(float);
            cudaSafeCall( cudaMemcpyToSymbol(ctable_space_step, &table_space_step, sizeof(size_t)) );

            cudaSafeCall( cudaMemcpyToSymbol(cndisp, &ndisp, sizeof(int)) );
            cudaSafeCall( cudaMemcpyToSymbol(cradius, &radius, sizeof(int)) );

            cudaSafeCall( cudaMemcpyToSymbol(cedge_disc, &edge_disc, sizeof(short)) );
            cudaSafeCall( cudaMemcpyToSymbol(cmax_disc, &max_disc, sizeof(short)) );
        }

        template <int channels>
        struct DistRgbMax
        {
            static __device__ __forceinline__ uchar calc(const uchar* a, const uchar* b)
            {
                uchar x = ::abs(a[0] - b[0]);
                uchar y = ::abs(a[1] - b[1]);
                uchar z = ::abs(a[2] - b[2]);
                return (::max(::max(x, y), z));
            }
        };

        template <>
        struct DistRgbMax<1>
        {
            static __device__ __forceinline__ uchar calc(const uchar* a, const uchar* b)
            {
                return ::abs(a[0] - b[0]);
            }
        };

        template <int channels, typename T>
        __global__ void bilateral_filter(int t, T* disp, size_t disp_step, const uchar* img, size_t img_step, int h, int w)
        {
            const int y = blockIdx.y * blockDim.y + threadIdx.y;
            const int x = ((blockIdx.x * blockDim.x + threadIdx.x) << 1) + ((y + t) & 1);

            T dp[5];

            if (y > 0 && y < h - 1 && x > 0 && x < w - 1)
            {
                dp[0] = *(disp + (y  ) * disp_step + x + 0);
                dp[1] = *(disp + (y-1) * disp_step + x + 0);
                dp[2] = *(disp + (y  ) * disp_step + x - 1);
                dp[3] = *(disp + (y+1) * disp_step + x + 0);
                dp[4] = *(disp + (y  ) * disp_step + x + 1);

                if(::abs(dp[1] - dp[0]) >= cedge_disc || ::abs(dp[2] - dp[0]) >= cedge_disc || ::abs(dp[3] - dp[0]) >= cedge_disc || ::abs(dp[4] - dp[0]) >= cedge_disc)
                {
                    const int ymin = ::max(0, y - cradius);
                    const int xmin = ::max(0, x - cradius);
                    const int ymax = ::min(h - 1, y + cradius);
                    const int xmax = ::min(w - 1, x + cradius);

                    float cost[] = {0.0f, 0.0f, 0.0f, 0.0f, 0.0f};

                    const uchar* ic = img + y * img_step + channels * x;

                    for(int yi = ymin; yi <= ymax; yi++)
                    {
                        const T* disp_y = disp + yi * disp_step;

                        for(int xi = xmin; xi <= xmax; xi++)
                        {
                            const uchar* in = img + yi * img_step + channels * xi;

                            uchar dist_rgb = DistRgbMax<channels>::calc(in, ic);

                            const float weight = ctable_color[dist_rgb] * (ctable_space + ::abs(y-yi)* ctable_space_step)[::abs(x-xi)];

                            const T disp_reg = disp_y[xi];

                            cost[0] += ::min(cmax_disc, ::abs(disp_reg - dp[0])) * weight;
                            cost[1] += ::min(cmax_disc, ::abs(disp_reg - dp[1])) * weight;
                            cost[2] += ::min(cmax_disc, ::abs(disp_reg - dp[2])) * weight;
                            cost[3] += ::min(cmax_disc, ::abs(disp_reg - dp[3])) * weight;
                            cost[4] += ::min(cmax_disc, ::abs(disp_reg - dp[4])) * weight;
                        }
                    }

                    float minimum = numeric_limits<float>::max();
                    int id = 0;

                    if (cost[0] < minimum)
                    {
                        minimum = cost[0];
                        id = 0;
                    }
                    if (cost[1] < minimum)
                    {
                        minimum = cost[1];
                        id = 1;
                    }
                    if (cost[2] < minimum)
                    {
                        minimum = cost[2];
                        id = 2;
                    }
                    if (cost[3] < minimum)
                    {
                        minimum = cost[3];
                        id = 3;
                    }
                    if (cost[4] < minimum)
                    {
                        minimum = cost[4];
                        id = 4;
                    }

                    *(disp + y * disp_step + x) = dp[id];
                }
            }
        }

        template <typename T>
        void bilateral_filter_caller(DevMem2D_<T> disp, DevMem2Db img, int channels, int iters, cudaStream_t stream)
        {
            dim3 threads(32, 8, 1);
            dim3 grid(1, 1, 1);
            grid.x = divUp(disp.cols, threads.x << 1);
            grid.y = divUp(disp.rows, threads.y);

            switch (channels)
            {
            case 1:
                for (int i = 0; i < iters; ++i)
                {
                    bilateral_filter<1><<<grid, threads, 0, stream>>>(0, disp.data, disp.step/sizeof(T), img.data, img.step, disp.rows, disp.cols);
                    cudaSafeCall( cudaGetLastError() );

                    bilateral_filter<1><<<grid, threads, 0, stream>>>(1, disp.data, disp.step/sizeof(T), img.data, img.step, disp.rows, disp.cols);
                    cudaSafeCall( cudaGetLastError() );
                }
                break;
            case 3:
                for (int i = 0; i < iters; ++i)
                {
                    bilateral_filter<3><<<grid, threads, 0, stream>>>(0, disp.data, disp.step/sizeof(T), img.data, img.step, disp.rows, disp.cols);
                    cudaSafeCall( cudaGetLastError() );

                    bilateral_filter<3><<<grid, threads, 0, stream>>>(1, disp.data, disp.step/sizeof(T), img.data, img.step, disp.rows, disp.cols);
                    cudaSafeCall( cudaGetLastError() );
                }
                break;
            default:
                cv::gpu::error("Unsupported channels count", __FILE__, __LINE__, "bilateral_filter_caller");
            }

            if (stream == 0)
                cudaSafeCall( cudaDeviceSynchronize() );
        }

        void bilateral_filter_gpu(DevMem2Db disp, DevMem2Db img, int channels, int iters, cudaStream_t stream)
        {
            bilateral_filter_caller(disp, img, channels, iters, stream);
        }

        void bilateral_filter_gpu(DevMem2D_<short> disp, DevMem2Db img, int channels, int iters, cudaStream_t stream)
        {
            bilateral_filter_caller(disp, img, channels, iters, stream);
        }
    } // namespace bilateral_filter
}}} // namespace cv { namespace gpu { namespace device
