Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
447 lines
16 KiB
447 lines
16 KiB
/*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. |
|
// |
|
// * 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. |
|
// |
|
// * The name of the copyright holders may not be used to endorse or promote products |
|
// derived from this software without specific prior written permission. |
|
// |
|
// This software is provided by the copyright holders and contributors "as is" and |
|
// any express or bpied warranties, including, but not limited to, the bpied |
|
// warranties of merchantability and fitness for a particular purpose are disclaimed. |
|
// In no event shall the Intel Corporation or contributors be liable for any direct, |
|
// indirect, incidental, special, exemplary, or consequential damages |
|
// (including, but not limited to, procurement of substitute goods or services; |
|
// loss of use, data, or profits; or business interruption) however caused |
|
// and on any theory of liability, whether in contract, strict liability, |
|
// or tort (including negligence or otherwise) arising in any way out of |
|
// the use of this software, even if advised of the possibility of such damage. |
|
// |
|
//M*/ |
|
|
|
#include "precomp.hpp" |
|
|
|
using namespace cv; |
|
using namespace cv::gpu; |
|
using namespace std; |
|
|
|
#if !defined (HAVE_CUDA) |
|
|
|
cv::gpu::SURF_GPU::SURF_GPU() { throw_nogpu(); } |
|
cv::gpu::SURF_GPU::SURF_GPU(double, int, int, bool, float, bool) { throw_nogpu(); } |
|
int cv::gpu::SURF_GPU::descriptorSize() const { throw_nogpu(); return 0;} |
|
void cv::gpu::SURF_GPU::uploadKeypoints(const vector<KeyPoint>&, GpuMat&) { throw_nogpu(); } |
|
void cv::gpu::SURF_GPU::downloadKeypoints(const GpuMat&, vector<KeyPoint>&) { throw_nogpu(); } |
|
void cv::gpu::SURF_GPU::downloadDescriptors(const GpuMat&, vector<float>&) { throw_nogpu(); } |
|
void cv::gpu::SURF_GPU::operator()(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); } |
|
void cv::gpu::SURF_GPU::operator()(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, bool) { throw_nogpu(); } |
|
void cv::gpu::SURF_GPU::operator()(const GpuMat&, const GpuMat&, vector<KeyPoint>&) { throw_nogpu(); } |
|
void cv::gpu::SURF_GPU::operator()(const GpuMat&, const GpuMat&, vector<KeyPoint>&, GpuMat&, bool) { throw_nogpu(); } |
|
void cv::gpu::SURF_GPU::operator()(const GpuMat&, const GpuMat&, vector<KeyPoint>&, vector<float>&, bool) { throw_nogpu(); } |
|
|
|
#else /* !defined (HAVE_CUDA) */ |
|
|
|
namespace cv { namespace gpu { namespace surf |
|
{ |
|
void icvCalcLayerDetAndTrace_gpu(const PtrStepf& det, const PtrStepf& trace, int img_rows, int img_cols, int octave, int nOctaveLayers); |
|
|
|
void icvFindMaximaInLayer_gpu(const PtrStepf& det, const PtrStepf& trace, int4* maxPosBuffer, unsigned int* maxCounter, |
|
int img_rows, int img_cols, int octave, bool use_mask, int nLayers); |
|
|
|
void icvInterpolateKeypoint_gpu(const PtrStepf& det, const int4* maxPosBuffer, unsigned int maxCounter, KeyPoint_GPU* featuresBuffer, unsigned int* featureCounter); |
|
|
|
void icvCalcOrientation_gpu(const KeyPoint_GPU* featureBuffer, int nFeatures, KeyPoint_GPU* keypoints, unsigned int* keypointCounter); |
|
|
|
void compute_descriptors_gpu(const DevMem2Df& descriptors, const KeyPoint_GPU* features, int nFeatures); |
|
}}} |
|
|
|
using namespace cv::gpu::surf; |
|
|
|
namespace |
|
{ |
|
class SURF_GPU_Invoker : private CvSURFParams |
|
{ |
|
public: |
|
SURF_GPU_Invoker(SURF_GPU& surf, const GpuMat& img, const GpuMat& mask) : |
|
CvSURFParams(surf), |
|
|
|
sum(surf.sum), mask1(surf.mask1), maskSum(surf.maskSum), intBuffer(surf.intBuffer), det(surf.det), trace(surf.trace), |
|
|
|
maxPosBuffer(surf.maxPosBuffer), featuresBuffer(surf.featuresBuffer), keypointsBuffer(surf.keypointsBuffer), |
|
|
|
img_cols(img.cols), img_rows(img.rows), |
|
|
|
use_mask(!mask.empty()), |
|
|
|
upright(surf.upright) |
|
{ |
|
CV_Assert(!img.empty() && img.type() == CV_8UC1); |
|
CV_Assert(mask.empty() || (mask.size() == img.size() && mask.type() == CV_8UC1)); |
|
CV_Assert(nOctaves > 0 && nOctaveLayers > 0); |
|
CV_Assert(TargetArchs::builtWith(GLOBAL_ATOMICS) && DeviceInfo().supports(GLOBAL_ATOMICS)); |
|
|
|
maxKeypoints = static_cast<int>(img.size().area() * surf.keypointsRatio); |
|
maxFeatures = static_cast<int>(1.5 * maxKeypoints); |
|
maxCandidates = static_cast<int>(1.5 * maxFeatures); |
|
|
|
CV_Assert(maxKeypoints > 0); |
|
|
|
cudaSafeCall( cudaMalloc((void**)&d_counters, (nOctaves + 2) * sizeof(unsigned int)) ); |
|
cudaSafeCall( cudaMemset(d_counters, 0, (nOctaves + 2) * sizeof(unsigned int)) ); |
|
|
|
uploadConstant("cv::gpu::surf::c_max_candidates", maxCandidates); |
|
uploadConstant("cv::gpu::surf::c_max_features", maxFeatures); |
|
uploadConstant("cv::gpu::surf::c_max_keypoints", maxKeypoints); |
|
uploadConstant("cv::gpu::surf::c_img_rows", img_rows); |
|
uploadConstant("cv::gpu::surf::c_img_cols", img_cols); |
|
uploadConstant("cv::gpu::surf::c_nOctaveLayers", nOctaveLayers); |
|
uploadConstant("cv::gpu::surf::c_hessianThreshold", static_cast<float>(hessianThreshold)); |
|
|
|
bindTexture("cv::gpu::surf::imgTex", (DevMem2D)img); |
|
|
|
integralBuffered(img, sum, intBuffer); |
|
bindTexture("cv::gpu::surf::sumTex", (DevMem2D_<unsigned int>)sum); |
|
|
|
if (use_mask) |
|
{ |
|
min(mask, 1.0, mask1); |
|
integralBuffered(mask1, maskSum, intBuffer); |
|
|
|
bindTexture("cv::gpu::surf::maskSumTex", (DevMem2D_<unsigned int>)maskSum); |
|
} |
|
} |
|
|
|
~SURF_GPU_Invoker() |
|
{ |
|
cudaSafeCall( cudaFree(d_counters) ); |
|
|
|
unbindTexture("cv::gpu::surf::imgTex"); |
|
unbindTexture("cv::gpu::surf::sumTex"); |
|
if (use_mask) |
|
unbindTexture("cv::gpu::surf::maskSumTex"); |
|
} |
|
|
|
void detectKeypoints(GpuMat& keypoints) |
|
{ |
|
ensureSizeIsEnough(img_rows * (nOctaveLayers + 2), img_cols, CV_32FC1, det); |
|
ensureSizeIsEnough(img_rows * (nOctaveLayers + 2), img_cols, CV_32FC1, trace); |
|
|
|
ensureSizeIsEnough(1, maxCandidates, CV_32SC4, maxPosBuffer); |
|
ensureSizeIsEnough(1, maxFeatures, CV_32FC(6), featuresBuffer); |
|
|
|
for (int octave = 0; octave < nOctaves; ++octave) |
|
{ |
|
const int layer_rows = img_rows >> octave; |
|
const int layer_cols = img_cols >> octave; |
|
|
|
uploadConstant("cv::gpu::surf::c_octave", octave); |
|
uploadConstant("cv::gpu::surf::c_layer_rows", layer_rows); |
|
uploadConstant("cv::gpu::surf::c_layer_cols", layer_cols); |
|
|
|
icvCalcLayerDetAndTrace_gpu(det, trace, img_rows, img_cols, octave, nOctaveLayers); |
|
|
|
icvFindMaximaInLayer_gpu(det, trace, maxPosBuffer.ptr<int4>(), d_counters + 2 + octave, |
|
img_rows, img_cols, octave, use_mask, nOctaveLayers); |
|
|
|
unsigned int maxCounter; |
|
cudaSafeCall( cudaMemcpy(&maxCounter, d_counters + 2 + octave, sizeof(unsigned int), cudaMemcpyDeviceToHost) ); |
|
maxCounter = std::min(maxCounter, static_cast<unsigned int>(maxCandidates)); |
|
|
|
if (maxCounter > 0) |
|
{ |
|
icvInterpolateKeypoint_gpu(det, maxPosBuffer.ptr<int4>(), maxCounter, |
|
featuresBuffer.ptr<KeyPoint_GPU>(), d_counters); |
|
} |
|
} |
|
unsigned int featureCounter; |
|
cudaSafeCall( cudaMemcpy(&featureCounter, d_counters, sizeof(unsigned int), cudaMemcpyDeviceToHost) ); |
|
featureCounter = std::min(featureCounter, static_cast<unsigned int>(maxFeatures)); |
|
|
|
if (!upright) |
|
findOrientation(featuresBuffer.colRange(0, featureCounter), keypoints); |
|
else |
|
{ |
|
if (featureCounter > 0) |
|
featuresBuffer.colRange(0, featureCounter).copyTo(keypoints); |
|
else |
|
keypoints.release(); |
|
} |
|
} |
|
|
|
void findOrientation(const GpuMat& features, GpuMat& keypoints) |
|
{ |
|
if (features.cols > 0) |
|
{ |
|
ensureSizeIsEnough(1, maxKeypoints, CV_32FC(6), keypointsBuffer); |
|
|
|
icvCalcOrientation_gpu(features.ptr<KeyPoint_GPU>(), features.cols, keypointsBuffer.ptr<KeyPoint_GPU>(), |
|
d_counters + 1); |
|
|
|
unsigned int keypointsCounter; |
|
cudaSafeCall( cudaMemcpy(&keypointsCounter, d_counters + 1, sizeof(unsigned int), cudaMemcpyDeviceToHost) ); |
|
keypointsCounter = std::min(keypointsCounter, static_cast<unsigned int>(maxKeypoints)); |
|
|
|
if (keypointsCounter > 0) |
|
keypointsBuffer.colRange(0, keypointsCounter).copyTo(keypoints); |
|
else |
|
keypoints.release(); |
|
} |
|
} |
|
|
|
void computeDescriptors(const GpuMat& keypoints, GpuMat& descriptors, int descriptorSize) |
|
{ |
|
if (keypoints.cols > 0) |
|
{ |
|
descriptors.create(keypoints.cols, descriptorSize, CV_32F); |
|
compute_descriptors_gpu(descriptors, keypoints.ptr<KeyPoint_GPU>(), keypoints.cols); |
|
} |
|
} |
|
|
|
private: |
|
GpuMat& sum; |
|
GpuMat& mask1; |
|
GpuMat& maskSum; |
|
GpuMat& intBuffer; |
|
|
|
GpuMat& det; |
|
GpuMat& trace; |
|
|
|
GpuMat& maxPosBuffer; |
|
GpuMat& featuresBuffer; |
|
GpuMat& keypointsBuffer; |
|
|
|
int img_cols, img_rows; |
|
|
|
bool use_mask; |
|
|
|
bool upright; |
|
|
|
int maxCandidates; |
|
int maxFeatures; |
|
int maxKeypoints; |
|
|
|
unsigned int* d_counters; |
|
}; |
|
} |
|
|
|
cv::gpu::SURF_GPU::SURF_GPU() |
|
{ |
|
hessianThreshold = 100; |
|
extended = 1; |
|
nOctaves = 4; |
|
nOctaveLayers = 2; |
|
keypointsRatio = 0.01f; |
|
upright = false; |
|
} |
|
|
|
cv::gpu::SURF_GPU::SURF_GPU(double _threshold, int _nOctaves, int _nOctaveLayers, bool _extended, float _keypointsRatio, bool _upright) |
|
{ |
|
hessianThreshold = _threshold; |
|
extended = _extended; |
|
nOctaves = _nOctaves; |
|
nOctaveLayers = _nOctaveLayers; |
|
keypointsRatio = _keypointsRatio; |
|
upright = _upright; |
|
} |
|
|
|
int cv::gpu::SURF_GPU::descriptorSize() const |
|
{ |
|
return extended ? 128 : 64; |
|
} |
|
|
|
void cv::gpu::SURF_GPU::uploadKeypoints(const vector<KeyPoint>& keypoints, GpuMat& keypointsGPU) |
|
{ |
|
if (keypoints.empty()) |
|
keypointsGPU.release(); |
|
else |
|
{ |
|
Mat keypointsCPU(1, keypoints.size(), CV_32FC(6)); |
|
|
|
for (size_t i = 0; i < keypoints.size(); ++i) |
|
{ |
|
const KeyPoint& kp = keypoints[i]; |
|
KeyPoint_GPU& gkp = keypointsCPU.ptr<KeyPoint_GPU>()[i]; |
|
|
|
gkp.x = kp.pt.x; |
|
gkp.y = kp.pt.y; |
|
|
|
gkp.laplacian = 1.0f; |
|
|
|
gkp.size = kp.size; |
|
|
|
gkp.dir = kp.angle; |
|
gkp.hessian = kp.response; |
|
} |
|
|
|
keypointsGPU.upload(keypointsCPU); |
|
} |
|
} |
|
|
|
namespace |
|
{ |
|
int calcSize(int octave, int layer) |
|
{ |
|
/* Wavelet size at first layer of first octave. */ |
|
const int HAAR_SIZE0 = 9; |
|
|
|
/* Wavelet size increment between layers. This should be an even number, |
|
such that the wavelet sizes in an octave are either all even or all odd. |
|
This ensures that when looking for the neighbours of a sample, the layers |
|
above and below are aligned correctly. */ |
|
const int HAAR_SIZE_INC = 6; |
|
|
|
return (HAAR_SIZE0 + HAAR_SIZE_INC * layer) << octave; |
|
} |
|
|
|
int getPointOctave(const KeyPoint_GPU& kpt, const CvSURFParams& params) |
|
{ |
|
int best_octave = 0; |
|
float min_diff = numeric_limits<float>::max(); |
|
for (int octave = 1; octave < params.nOctaves; ++octave) |
|
{ |
|
for (int layer = 0; layer < params.nOctaveLayers; ++layer) |
|
{ |
|
float diff = std::abs(kpt.size - (float)calcSize(octave, layer)); |
|
if (min_diff > diff) |
|
{ |
|
min_diff = diff; |
|
best_octave = octave; |
|
if (min_diff == 0) |
|
return best_octave; |
|
} |
|
} |
|
} |
|
return best_octave; |
|
} |
|
} |
|
|
|
void cv::gpu::SURF_GPU::downloadKeypoints(const GpuMat& keypointsGPU, vector<KeyPoint>& keypoints) |
|
{ |
|
if (keypointsGPU.empty()) |
|
keypoints.clear(); |
|
else |
|
{ |
|
CV_Assert(keypointsGPU.type() == CV_32FC(6) && keypointsGPU.isContinuous()); |
|
|
|
Mat keypointsCPU = keypointsGPU; |
|
keypoints.resize(keypointsGPU.cols); |
|
|
|
for (int i = 0; i < keypointsGPU.cols; ++i) |
|
{ |
|
KeyPoint& kp = keypoints[i]; |
|
const KeyPoint_GPU& gkp = keypointsCPU.ptr<KeyPoint_GPU>()[i]; |
|
|
|
kp.pt.x = gkp.x; |
|
kp.pt.y = gkp.y; |
|
|
|
kp.size = gkp.size; |
|
|
|
kp.angle = gkp.dir; |
|
|
|
kp.response = gkp.hessian; |
|
|
|
kp.octave = getPointOctave(gkp, *this); |
|
|
|
kp.class_id = static_cast<int>(gkp.laplacian); |
|
} |
|
} |
|
} |
|
|
|
void cv::gpu::SURF_GPU::downloadDescriptors(const GpuMat& descriptorsGPU, vector<float>& descriptors) |
|
{ |
|
if (descriptorsGPU.empty()) |
|
descriptors.clear(); |
|
else |
|
{ |
|
CV_Assert(descriptorsGPU.type() == CV_32F); |
|
|
|
descriptors.resize(descriptorsGPU.rows * descriptorsGPU.cols); |
|
Mat descriptorsCPU(descriptorsGPU.size(), CV_32F, &descriptors[0]); |
|
descriptorsGPU.download(descriptorsCPU); |
|
} |
|
} |
|
|
|
void cv::gpu::SURF_GPU::operator()(const GpuMat& img, const GpuMat& mask, GpuMat& keypoints) |
|
{ |
|
if (!img.empty()) |
|
{ |
|
SURF_GPU_Invoker surf(*this, img, mask); |
|
|
|
surf.detectKeypoints(keypoints); |
|
} |
|
} |
|
|
|
void cv::gpu::SURF_GPU::operator()(const GpuMat& img, const GpuMat& mask, GpuMat& keypoints, GpuMat& descriptors, |
|
bool useProvidedKeypoints) |
|
{ |
|
if (!img.empty()) |
|
{ |
|
SURF_GPU_Invoker surf(*this, img, mask); |
|
|
|
if (!useProvidedKeypoints) |
|
surf.detectKeypoints(keypoints); |
|
else if (!upright) |
|
{ |
|
GpuMat keypointsBuf; |
|
surf.findOrientation(keypoints, keypointsBuf); |
|
keypointsBuf.copyTo(keypoints); |
|
} |
|
|
|
surf.computeDescriptors(keypoints, descriptors, descriptorSize()); |
|
} |
|
} |
|
|
|
void cv::gpu::SURF_GPU::operator()(const GpuMat& img, const GpuMat& mask, vector<KeyPoint>& keypoints) |
|
{ |
|
GpuMat keypointsGPU; |
|
|
|
(*this)(img, mask, keypointsGPU); |
|
|
|
downloadKeypoints(keypointsGPU, keypoints); |
|
} |
|
|
|
void cv::gpu::SURF_GPU::operator()(const GpuMat& img, const GpuMat& mask, vector<KeyPoint>& keypoints, |
|
GpuMat& descriptors, bool useProvidedKeypoints) |
|
{ |
|
GpuMat keypointsGPU; |
|
|
|
if (useProvidedKeypoints) |
|
uploadKeypoints(keypoints, keypointsGPU); |
|
|
|
(*this)(img, mask, keypointsGPU, descriptors, useProvidedKeypoints); |
|
|
|
downloadKeypoints(keypointsGPU, keypoints); |
|
} |
|
|
|
void cv::gpu::SURF_GPU::operator()(const GpuMat& img, const GpuMat& mask, vector<KeyPoint>& keypoints, |
|
vector<float>& descriptors, bool useProvidedKeypoints) |
|
{ |
|
GpuMat descriptorsGPU; |
|
|
|
(*this)(img, mask, keypoints, descriptorsGPU, useProvidedKeypoints); |
|
|
|
downloadDescriptors(descriptorsGPU, descriptors); |
|
} |
|
|
|
#endif /* !defined (HAVE_CUDA) */
|
|
|