opencv/modules/gpu/src/gftt.cpp

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/*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.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., 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.
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// * 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 GpuMaterials provided with the distribution.
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// derived from this software without specific prior written permission.
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//M*/
#include "precomp.hpp"
using namespace std;
using namespace cv;
using namespace cv::gpu;
#if !defined (HAVE_CUDA)
void cv::gpu::GoodFeaturesToTrackDetector_GPU::operator ()(const GpuMat&, GpuMat&, const GpuMat&) { throw_nogpu(); }
#else /* !defined (HAVE_CUDA) */
namespace cv { namespace gpu { namespace device
{
namespace gfft
{
int findCorners_gpu(DevMem2Df eig, float threshold, DevMem2Db mask, float2* corners, int max_count);
void sortCorners_gpu(DevMem2Df eig, float2* corners, int count);
}
}}}
void cv::gpu::GoodFeaturesToTrackDetector_GPU::operator ()(const GpuMat& image, GpuMat& corners, const GpuMat& mask)
{
using namespace cv::gpu::device::gfft;
CV_Assert(qualityLevel > 0 && minDistance >= 0 && maxCorners >= 0);
CV_Assert(mask.empty() || (mask.type() == CV_8UC1 && mask.size() == image.size()));
CV_Assert(TargetArchs::builtWith(GLOBAL_ATOMICS) && DeviceInfo().supports(GLOBAL_ATOMICS));
ensureSizeIsEnough(image.size(), CV_32F, eig_);
if (useHarrisDetector)
cornerHarris(image, eig_, Dx_, Dy_, buf_, blockSize, 3, harrisK);
else
cornerMinEigenVal(image, eig_, Dx_, Dy_, buf_, blockSize, 3);
double maxVal = 0;
minMax(eig_, 0, &maxVal, GpuMat(), minMaxbuf_);
ensureSizeIsEnough(1, std::max(1000, static_cast<int>(image.size().area() * 0.05)), CV_32FC2, tmpCorners_);
int total = findCorners_gpu(eig_, static_cast<float>(maxVal * qualityLevel), mask, tmpCorners_.ptr<float2>(), tmpCorners_.cols);
sortCorners_gpu(eig_, tmpCorners_.ptr<float2>(), total);
if (minDistance < 1)
tmpCorners_.colRange(0, maxCorners > 0 ? std::min(maxCorners, total) : total).copyTo(corners);
else
{
vector<Point2f> tmp(total);
Mat tmpMat(1, total, CV_32FC2, (void*)&tmp[0]);
tmpCorners_.colRange(0, total).download(tmpMat);
vector<Point2f> tmp2;
tmp2.reserve(total);
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<Point2f> > grid(grid_width * grid_height);
for (int i = 0; i < total; ++i)
{
Point2f 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++)
{
vector<Point2f>& m = grid[yy * grid_width + xx];
if (!m.empty())
{
for(size_t j = 0; j < m.size(); j++)
{
float dx = p.x - m[j].x;
float dy = p.y - m[j].y;
if (dx * dx + dy * dy < minDistance * minDistance)
{
good = false;
goto break_out;
}
}
}
}
}
break_out:
if(good)
{
grid[y_cell * grid_width + x_cell].push_back(p);
tmp2.push_back(p);
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if (maxCorners > 0 && tmp2.size() == static_cast<size_t>(maxCorners))
break;
}
}
corners.upload(Mat(1, tmp2.size(), CV_32FC2, &tmp2[0]));
}
}
#endif /* !defined (HAVE_CUDA) */