gftt.cpp

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//    Peng Xiao, pengxiao@outlook.com
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#include "precomp.hpp"
#include "opencl_kernels.hpp"

using namespace cv;
using namespace cv::ocl;

// compact structure for corners
struct DefCorner
{
    float eig;  //eigenvalue of corner
    short x;    //x coordinate of corner point
    short y;    //y coordinate of corner point
};

// compare procedure for corner
//it is used for sort on the host side
struct DefCornerCompare :
        public std::binary_function<DefCorner, DefCorner, bool>
{
    bool operator()(const DefCorner a, const DefCorner b) const
    {
        return a.eig > b.eig;
    }
};

// find corners on matrix and put it into array
static void findCorners_caller(
    const oclMat&   eig_mat,        //input matrix worth eigenvalues
    oclMat&         eigMinMax,      //input with min and max values of eigenvalues
    const float     qualityLevel,
    const oclMat&   mask,
    oclMat&         corners,        //output array with detected corners
    oclMat&         counter)        //output value with number of detected corners, have to be 0 before call
{
    String  opt;
    std::vector<int> k;
    Context * cxt = Context::getContext();

    std::vector< std::pair<size_t, const void*> > args;

    const int mask_strip = mask.step / mask.elemSize1();

    args.push_back(std::make_pair( sizeof(cl_mem),   (void*)&(eig_mat.data)));

    int src_pitch = (int)eig_mat.step;
    args.push_back(std::make_pair( sizeof(cl_int),   (void*)&src_pitch ));
    args.push_back(std::make_pair( sizeof(cl_mem),   (void*)&mask.data ));
    args.push_back(std::make_pair( sizeof(cl_mem),   (void*)&corners.data ));
    args.push_back(std::make_pair( sizeof(cl_int),   (void*)&mask_strip));
    args.push_back(std::make_pair( sizeof(cl_mem),   (void*)&eigMinMax.data ));
    args.push_back(std::make_pair( sizeof(cl_float), (void*)&qualityLevel ));
    args.push_back(std::make_pair( sizeof(cl_int),   (void*)&eig_mat.rows ));
    args.push_back(std::make_pair( sizeof(cl_int),   (void*)&eig_mat.cols ));
    args.push_back(std::make_pair( sizeof(cl_int),   (void*)&corners.cols ));
    args.push_back(std::make_pair( sizeof(cl_mem),   (void*)&counter.data ));

    size_t globalThreads[3] = {eig_mat.cols, eig_mat.rows, 1};
    size_t localThreads[3]  = {16, 16, 1};
    if(!mask.empty())
        opt += " -D WITH_MASK=1";

     openCLExecuteKernel(cxt, &imgproc_gftt, "findCorners", globalThreads, localThreads, args, -1, -1, opt.c_str());
}


static void minMaxEig_caller(const oclMat &src, oclMat &dst, oclMat & tozero)
{
    size_t groupnum = src.clCxt->getDeviceInfo().maxComputeUnits;
    CV_Assert(groupnum != 0);

    int dbsize = groupnum * 2 * src.elemSize();

    ensureSizeIsEnough(1, dbsize, CV_8UC1, dst);

    cl_mem dst_data = reinterpret_cast<cl_mem>(dst.data);

    int all_cols = src.step / src.elemSize();
    int pre_cols = (src.offset % src.step) / src.elemSize();
    int sec_cols = all_cols - (src.offset % src.step + src.cols * src.elemSize() - 1) / src.elemSize() - 1;
    int invalid_cols = pre_cols + sec_cols;
    int cols = all_cols - invalid_cols , elemnum = cols * src.rows;
    int offset = src.offset / src.elemSize();

    {
        // first parallel pass
        std::vector<std::pair<size_t , const void *> > args;
        args.push_back( std::make_pair( sizeof(cl_mem) , (void *)&src.data));
        args.push_back( std::make_pair( sizeof(cl_mem) , (void *)&dst_data ));
        args.push_back( std::make_pair( sizeof(cl_int) , (void *)&cols ));
        args.push_back( std::make_pair( sizeof(cl_int) , (void *)&invalid_cols ));
        args.push_back( std::make_pair( sizeof(cl_int) , (void *)&offset));
        args.push_back( std::make_pair( sizeof(cl_int) , (void *)&elemnum));
        args.push_back( std::make_pair( sizeof(cl_int) , (void *)&groupnum));
        size_t globalThreads[3] = {groupnum * 256, 1, 1};
        size_t localThreads[3] = {256, 1, 1};
        openCLExecuteKernel(src.clCxt, &arithm_minMax, "arithm_op_minMax", globalThreads, localThreads,
                            args, -1, -1, "-D T=float -D DEPTH_5");
    }

    {
        // run final "serial" kernel to find accumulate results from threads and reset corner counter
        std::vector<std::pair<size_t , const void *> > args;
        args.push_back( std::make_pair( sizeof(cl_mem) , (void *)&dst_data ));
        args.push_back( std::make_pair( sizeof(cl_int) , (void *)&groupnum ));
        args.push_back( std::make_pair( sizeof(cl_mem) , (void *)&tozero.data ));
        size_t globalThreads[3] = {1, 1, 1};
        size_t localThreads[3] = {1, 1, 1};
        openCLExecuteKernel(src.clCxt, &imgproc_gftt, "arithm_op_minMax_final", globalThreads, localThreads,
                            args, -1, -1);
    }
}

void cv::ocl::GoodFeaturesToTrackDetector_OCL::operator ()(const oclMat& image, oclMat& corners, const oclMat& mask)
{
    CV_Assert(qualityLevel > 0 && minDistance >= 0 && maxCorners >= 0);
    CV_Assert(mask.empty() || (mask.type() == CV_8UC1 && mask.size() == image.size()));

    ensureSizeIsEnough(image.size(), CV_32F, eig_);

    if (useHarrisDetector)
        cornerHarris_dxdy(image, eig_, Dx_, Dy_, blockSize, 3, harrisK);
    else
        cornerMinEigenVal_dxdy(image, eig_, Dx_, Dy_, blockSize, 3);

    ensureSizeIsEnough(1,1, CV_32SC1, counter_);

    // find max eigenvalue and reset detected counters
    minMaxEig_caller(eig_, eig_minmax_, counter_);

    // allocate buffer for kernels
    int corner_array_size = std::max(1024, static_cast<int>(image.size().area() * 0.05));
    ensureSizeIsEnough(1, corner_array_size , CV_32FC2, tmpCorners_);

    int total = tmpCorners_.cols; // by default the number of corner is full array
    std::vector<DefCorner> tmp(tmpCorners_.cols); // input buffer with corner for HOST part of algorithm

    // find points with high eigenvalue and put it into the output array
    findCorners_caller(eig_, eig_minmax_, static_cast<float>(qualityLevel), mask, tmpCorners_, counter_);

    // send non-blocking request to read real non-zero number of corners to sort it on the HOST side
    openCLVerifyCall(clEnqueueReadBuffer(getClCommandQueue(counter_.clCxt), (cl_mem)counter_.data, CL_FALSE, 0, sizeof(int), &total, 0, NULL, NULL));

    if (total == 0)
    {
        // check for trivial case
        corners.release();
        return;
    }

    // blocking read whole corners array (sorted or not sorted)
    openCLReadBuffer(tmpCorners_.clCxt, (cl_mem)tmpCorners_.data, &tmp[0], tmpCorners_.cols * sizeof(DefCorner));

    // sort detected corners on cpu side.
    tmp.resize(total);
    std::sort(tmp.begin(), tmp.end(), DefCornerCompare());

    // estimate maximal size of final output array
    int total_max = maxCorners > 0 ? std::min(maxCorners, total) : total;
    int D2 = (int)ceil(minDistance * minDistance);

    // allocate output buffer
    std::vector<Point2f> tmp2;
    tmp2.reserve(total_max);


    if (minDistance < 1)
    {
        // we have not distance restriction. then just copy with conversion maximal allowed points into output array
        for (int i = 0; i < total_max; ++i)
            tmp2.push_back(Point2f(tmp[i].x, tmp[i].y));
    }
    else
    {
        // we have distance restriction. then start coping to output array from the first element and check distance for each next one
        const int cell_size = cvRound(minDistance);
        const int grid_width = (image.cols + cell_size - 1) / cell_size;
        const int grid_height = (image.rows + cell_size - 1) / cell_size;

        std::vector< std::vector<Point2i> > grid(grid_width * grid_height);

        for (int i = 0; i < total ; ++i)
        {
            DefCorner p = tmp[i];
            bool good = true;

            int x_cell = static_cast<int>(p.x / cell_size);
            int y_cell = static_cast<int>(p.y / cell_size);

            int x1 = x_cell - 1;
            int y1 = y_cell - 1;
            int x2 = x_cell + 1;
            int y2 = y_cell + 1;

            // boundary check
            x1 = std::max(0, x1);
            y1 = std::max(0, y1);
            x2 = std::min(grid_width - 1, x2);
            y2 = std::min(grid_height - 1, y2);

            for (int yy = y1; yy <= y2; yy++)
            {
                for (int xx = x1; xx <= x2; xx++)
                {
                    std::vector<Point2i>& m = grid[yy * grid_width + xx];
                    if (m.empty())
                        continue;
                    for(size_t j = 0; j < m.size(); j++)
                    {
                        int dx = p.x - m[j].x;
                        int dy = p.y - m[j].y;

                        if (dx * dx + dy * dy < D2)
                        {
                            good = false;
                            goto break_out_;
                        }
                    }
                }
            }

            break_out_:

            if(good)
            {
                grid[y_cell * grid_width + x_cell].push_back(Point2i(p.x, p.y));
                tmp2.push_back(Point2f(p.x, p.y));

                if (maxCorners > 0 && tmp2.size() == static_cast<size_t>(maxCorners))
                    break;
            }
        }

    }

    int final_size = static_cast<int>(tmp2.size());
    if (final_size > 0)
        corners.upload(Mat(1, final_size, CV_32FC2, &tmp2[0]));
    else
        corners.release();
}

void cv::ocl::GoodFeaturesToTrackDetector_OCL::downloadPoints(const oclMat &points, std::vector<Point2f> &points_v)
{
    CV_DbgAssert(points.type() == CV_32FC2);
    points_v.resize(points.cols);
    openCLSafeCall(clEnqueueReadBuffer(
        *(cl_command_queue*)getClCommandQueuePtr(),
        reinterpret_cast<cl_mem>(points.data),
        CL_TRUE,
        0,
        points.cols * sizeof(Point2f),
        &points_v[0],
        0,
        NULL,
        NULL));
}