mirror of
https://github.com/opencv/opencv.git
synced 2025-01-18 06:03:15 +08:00
Merge branch 'master' of git://code.opencv.org/opencv
This commit is contained in:
commit
9f1c10e1c5
@ -267,6 +267,97 @@ public:
|
|||||||
static Ptr<Feature2D> create( const string& name );
|
static Ptr<Feature2D> create( const string& name );
|
||||||
};
|
};
|
||||||
|
|
||||||
|
/*!
|
||||||
|
BRISK implementation
|
||||||
|
*/
|
||||||
|
class CV_EXPORTS_W BRISK : public Feature2D
|
||||||
|
{
|
||||||
|
public:
|
||||||
|
CV_WRAP explicit BRISK(int thresh=30, int octaves=3, float patternScale=1.0f);
|
||||||
|
|
||||||
|
virtual ~BRISK();
|
||||||
|
|
||||||
|
// returns the descriptor size in bytes
|
||||||
|
int descriptorSize() const;
|
||||||
|
// returns the descriptor type
|
||||||
|
int descriptorType() const;
|
||||||
|
|
||||||
|
// Compute the BRISK features on an image
|
||||||
|
void operator()(InputArray image, InputArray mask, vector<KeyPoint>& keypoints) const;
|
||||||
|
|
||||||
|
// Compute the BRISK features and descriptors on an image
|
||||||
|
void operator()( InputArray image, InputArray mask, vector<KeyPoint>& keypoints,
|
||||||
|
OutputArray descriptors, bool useProvidedKeypoints=false ) const;
|
||||||
|
|
||||||
|
AlgorithmInfo* info() const;
|
||||||
|
|
||||||
|
// custom setup
|
||||||
|
CV_WRAP explicit BRISK(std::vector<float> &radiusList, std::vector<int> &numberList,
|
||||||
|
float dMax=5.85f, float dMin=8.2f, std::vector<int> indexChange=std::vector<int>());
|
||||||
|
|
||||||
|
// call this to generate the kernel:
|
||||||
|
// circle of radius r (pixels), with n points;
|
||||||
|
// short pairings with dMax, long pairings with dMin
|
||||||
|
CV_WRAP void generateKernel(std::vector<float> &radiusList,
|
||||||
|
std::vector<int> &numberList, float dMax=5.85f, float dMin=8.2f,
|
||||||
|
std::vector<int> indexChange=std::vector<int>());
|
||||||
|
|
||||||
|
protected:
|
||||||
|
|
||||||
|
void computeImpl( const Mat& image, vector<KeyPoint>& keypoints, Mat& descriptors ) const;
|
||||||
|
void detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const;
|
||||||
|
|
||||||
|
void computeKeypointsNoOrientation(InputArray image, InputArray mask, vector<KeyPoint>& keypoints) const;
|
||||||
|
void computeDescriptorsAndOrOrientation(InputArray image, InputArray mask, vector<KeyPoint>& keypoints,
|
||||||
|
OutputArray descriptors, bool doDescriptors, bool doOrientation,
|
||||||
|
bool useProvidedKeypoints) const;
|
||||||
|
|
||||||
|
// Feature parameters
|
||||||
|
CV_PROP_RW int threshold;
|
||||||
|
CV_PROP_RW int octaves;
|
||||||
|
|
||||||
|
// some helper structures for the Brisk pattern representation
|
||||||
|
struct BriskPatternPoint{
|
||||||
|
float x; // x coordinate relative to center
|
||||||
|
float y; // x coordinate relative to center
|
||||||
|
float sigma; // Gaussian smoothing sigma
|
||||||
|
};
|
||||||
|
struct BriskShortPair{
|
||||||
|
unsigned int i; // index of the first pattern point
|
||||||
|
unsigned int j; // index of other pattern point
|
||||||
|
};
|
||||||
|
struct BriskLongPair{
|
||||||
|
unsigned int i; // index of the first pattern point
|
||||||
|
unsigned int j; // index of other pattern point
|
||||||
|
int weighted_dx; // 1024.0/dx
|
||||||
|
int weighted_dy; // 1024.0/dy
|
||||||
|
};
|
||||||
|
inline int smoothedIntensity(const cv::Mat& image,
|
||||||
|
const cv::Mat& integral,const float key_x,
|
||||||
|
const float key_y, const unsigned int scale,
|
||||||
|
const unsigned int rot, const unsigned int point) const;
|
||||||
|
// pattern properties
|
||||||
|
BriskPatternPoint* patternPoints_; //[i][rotation][scale]
|
||||||
|
unsigned int points_; // total number of collocation points
|
||||||
|
float* scaleList_; // lists the scaling per scale index [scale]
|
||||||
|
unsigned int* sizeList_; // lists the total pattern size per scale index [scale]
|
||||||
|
static const unsigned int scales_; // scales discretization
|
||||||
|
static const float scalerange_; // span of sizes 40->4 Octaves - else, this needs to be adjusted...
|
||||||
|
static const unsigned int n_rot_; // discretization of the rotation look-up
|
||||||
|
|
||||||
|
// pairs
|
||||||
|
int strings_; // number of uchars the descriptor consists of
|
||||||
|
float dMax_; // short pair maximum distance
|
||||||
|
float dMin_; // long pair maximum distance
|
||||||
|
BriskShortPair* shortPairs_; // d<_dMax
|
||||||
|
BriskLongPair* longPairs_; // d>_dMin
|
||||||
|
unsigned int noShortPairs_; // number of shortParis
|
||||||
|
unsigned int noLongPairs_; // number of longParis
|
||||||
|
|
||||||
|
// general
|
||||||
|
static const float basicSize_;
|
||||||
|
};
|
||||||
|
|
||||||
|
|
||||||
/*!
|
/*!
|
||||||
ORB implementation.
|
ORB implementation.
|
||||||
|
2237
modules/features2d/src/brisk.cpp
Executable file
2237
modules/features2d/src/brisk.cpp
Executable file
File diff suppressed because it is too large
Load Diff
@ -42,335 +42,11 @@ The references are:
|
|||||||
*/
|
*/
|
||||||
|
|
||||||
#include "precomp.hpp"
|
#include "precomp.hpp"
|
||||||
|
#include "fast_score.hpp"
|
||||||
|
|
||||||
namespace cv
|
namespace cv
|
||||||
{
|
{
|
||||||
|
|
||||||
static void makeOffsets(int pixel[], int row_stride, int patternSize)
|
|
||||||
{
|
|
||||||
switch(patternSize) {
|
|
||||||
case 16:
|
|
||||||
pixel[0] = 0 + row_stride * 3;
|
|
||||||
pixel[1] = 1 + row_stride * 3;
|
|
||||||
pixel[2] = 2 + row_stride * 2;
|
|
||||||
pixel[3] = 3 + row_stride * 1;
|
|
||||||
pixel[4] = 3 + row_stride * 0;
|
|
||||||
pixel[5] = 3 + row_stride * -1;
|
|
||||||
pixel[6] = 2 + row_stride * -2;
|
|
||||||
pixel[7] = 1 + row_stride * -3;
|
|
||||||
pixel[8] = 0 + row_stride * -3;
|
|
||||||
pixel[9] = -1 + row_stride * -3;
|
|
||||||
pixel[10] = -2 + row_stride * -2;
|
|
||||||
pixel[11] = -3 + row_stride * -1;
|
|
||||||
pixel[12] = -3 + row_stride * 0;
|
|
||||||
pixel[13] = -3 + row_stride * 1;
|
|
||||||
pixel[14] = -2 + row_stride * 2;
|
|
||||||
pixel[15] = -1 + row_stride * 3;
|
|
||||||
break;
|
|
||||||
case 12:
|
|
||||||
pixel[0] = 0 + row_stride * 2;
|
|
||||||
pixel[1] = 1 + row_stride * 2;
|
|
||||||
pixel[2] = 2 + row_stride * 1;
|
|
||||||
pixel[3] = 2 + row_stride * 0;
|
|
||||||
pixel[4] = 2 + row_stride * -1;
|
|
||||||
pixel[5] = 1 + row_stride * -2;
|
|
||||||
pixel[6] = 0 + row_stride * -2;
|
|
||||||
pixel[7] = -1 + row_stride * -2;
|
|
||||||
pixel[8] = -2 + row_stride * -1;
|
|
||||||
pixel[9] = -2 + row_stride * 0;
|
|
||||||
pixel[10] = -2 + row_stride * 1;
|
|
||||||
pixel[11] = -1 + row_stride * 2;
|
|
||||||
break;
|
|
||||||
case 8:
|
|
||||||
pixel[0] = 0 + row_stride * 1;
|
|
||||||
pixel[1] = 1 + row_stride * 1;
|
|
||||||
pixel[2] = 1 + row_stride * 0;
|
|
||||||
pixel[3] = 1 + row_stride * -1;
|
|
||||||
pixel[4] = 0 + row_stride * -1;
|
|
||||||
pixel[5] = -1 + row_stride * -1;
|
|
||||||
pixel[6] = 0 + row_stride * 0;
|
|
||||||
pixel[7] = 1 + row_stride * 1;
|
|
||||||
break;
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
/*static void testCorner(const uchar* ptr, const int pixel[], int K, int N, int threshold) {
|
|
||||||
// check that with the computed "threshold" the pixel is still a corner
|
|
||||||
// and that with the increased-by-1 "threshold" the pixel is not a corner anymore
|
|
||||||
for( int delta = 0; delta <= 1; delta++ )
|
|
||||||
{
|
|
||||||
int v0 = std::min(ptr[0] + threshold + delta, 255);
|
|
||||||
int v1 = std::max(ptr[0] - threshold - delta, 0);
|
|
||||||
int c0 = 0, c1 = 0;
|
|
||||||
|
|
||||||
for( int k = 0; k < N; k++ )
|
|
||||||
{
|
|
||||||
int x = ptr[pixel[k]];
|
|
||||||
if(x > v0)
|
|
||||||
{
|
|
||||||
if( ++c0 > K )
|
|
||||||
break;
|
|
||||||
c1 = 0;
|
|
||||||
}
|
|
||||||
else if( x < v1 )
|
|
||||||
{
|
|
||||||
if( ++c1 > K )
|
|
||||||
break;
|
|
||||||
c0 = 0;
|
|
||||||
}
|
|
||||||
else
|
|
||||||
{
|
|
||||||
c0 = c1 = 0;
|
|
||||||
}
|
|
||||||
}
|
|
||||||
CV_Assert( (delta == 0 && std::max(c0, c1) > K) ||
|
|
||||||
(delta == 1 && std::max(c0, c1) <= K) );
|
|
||||||
}
|
|
||||||
}*/
|
|
||||||
|
|
||||||
template<int patternSize>
|
|
||||||
int cornerScore(const uchar* ptr, const int pixel[], int threshold);
|
|
||||||
|
|
||||||
template<>
|
|
||||||
int cornerScore<16>(const uchar* ptr, const int pixel[], int threshold)
|
|
||||||
{
|
|
||||||
const int K = 8, N = 16 + K + 1;
|
|
||||||
int k, v = ptr[0];
|
|
||||||
short d[N];
|
|
||||||
for( k = 0; k < N; k++ )
|
|
||||||
d[k] = (short)(v - ptr[pixel[k]]);
|
|
||||||
|
|
||||||
#if CV_SSE2
|
|
||||||
__m128i q0 = _mm_set1_epi16(-1000), q1 = _mm_set1_epi16(1000);
|
|
||||||
for( k = 0; k < 16; k += 8 )
|
|
||||||
{
|
|
||||||
__m128i v0 = _mm_loadu_si128((__m128i*)(d+k+1));
|
|
||||||
__m128i v1 = _mm_loadu_si128((__m128i*)(d+k+2));
|
|
||||||
__m128i a = _mm_min_epi16(v0, v1);
|
|
||||||
__m128i b = _mm_max_epi16(v0, v1);
|
|
||||||
v0 = _mm_loadu_si128((__m128i*)(d+k+3));
|
|
||||||
a = _mm_min_epi16(a, v0);
|
|
||||||
b = _mm_max_epi16(b, v0);
|
|
||||||
v0 = _mm_loadu_si128((__m128i*)(d+k+4));
|
|
||||||
a = _mm_min_epi16(a, v0);
|
|
||||||
b = _mm_max_epi16(b, v0);
|
|
||||||
v0 = _mm_loadu_si128((__m128i*)(d+k+5));
|
|
||||||
a = _mm_min_epi16(a, v0);
|
|
||||||
b = _mm_max_epi16(b, v0);
|
|
||||||
v0 = _mm_loadu_si128((__m128i*)(d+k+6));
|
|
||||||
a = _mm_min_epi16(a, v0);
|
|
||||||
b = _mm_max_epi16(b, v0);
|
|
||||||
v0 = _mm_loadu_si128((__m128i*)(d+k+7));
|
|
||||||
a = _mm_min_epi16(a, v0);
|
|
||||||
b = _mm_max_epi16(b, v0);
|
|
||||||
v0 = _mm_loadu_si128((__m128i*)(d+k+8));
|
|
||||||
a = _mm_min_epi16(a, v0);
|
|
||||||
b = _mm_max_epi16(b, v0);
|
|
||||||
v0 = _mm_loadu_si128((__m128i*)(d+k));
|
|
||||||
q0 = _mm_max_epi16(q0, _mm_min_epi16(a, v0));
|
|
||||||
q1 = _mm_min_epi16(q1, _mm_max_epi16(b, v0));
|
|
||||||
v0 = _mm_loadu_si128((__m128i*)(d+k+9));
|
|
||||||
q0 = _mm_max_epi16(q0, _mm_min_epi16(a, v0));
|
|
||||||
q1 = _mm_min_epi16(q1, _mm_max_epi16(b, v0));
|
|
||||||
}
|
|
||||||
q0 = _mm_max_epi16(q0, _mm_sub_epi16(_mm_setzero_si128(), q1));
|
|
||||||
q0 = _mm_max_epi16(q0, _mm_unpackhi_epi64(q0, q0));
|
|
||||||
q0 = _mm_max_epi16(q0, _mm_srli_si128(q0, 4));
|
|
||||||
q0 = _mm_max_epi16(q0, _mm_srli_si128(q0, 2));
|
|
||||||
threshold = (short)_mm_cvtsi128_si32(q0) - 1;
|
|
||||||
#else
|
|
||||||
int a0 = threshold;
|
|
||||||
for( k = 0; k < 16; k += 2 )
|
|
||||||
{
|
|
||||||
int a = std::min((int)d[k+1], (int)d[k+2]);
|
|
||||||
a = std::min(a, (int)d[k+3]);
|
|
||||||
if( a <= a0 )
|
|
||||||
continue;
|
|
||||||
a = std::min(a, (int)d[k+4]);
|
|
||||||
a = std::min(a, (int)d[k+5]);
|
|
||||||
a = std::min(a, (int)d[k+6]);
|
|
||||||
a = std::min(a, (int)d[k+7]);
|
|
||||||
a = std::min(a, (int)d[k+8]);
|
|
||||||
a0 = std::max(a0, std::min(a, (int)d[k]));
|
|
||||||
a0 = std::max(a0, std::min(a, (int)d[k+9]));
|
|
||||||
}
|
|
||||||
|
|
||||||
int b0 = -a0;
|
|
||||||
for( k = 0; k < 16; k += 2 )
|
|
||||||
{
|
|
||||||
int b = std::max((int)d[k+1], (int)d[k+2]);
|
|
||||||
b = std::max(b, (int)d[k+3]);
|
|
||||||
b = std::max(b, (int)d[k+4]);
|
|
||||||
b = std::max(b, (int)d[k+5]);
|
|
||||||
if( b >= b0 )
|
|
||||||
continue;
|
|
||||||
b = std::max(b, (int)d[k+6]);
|
|
||||||
b = std::max(b, (int)d[k+7]);
|
|
||||||
b = std::max(b, (int)d[k+8]);
|
|
||||||
|
|
||||||
b0 = std::min(b0, std::max(b, (int)d[k]));
|
|
||||||
b0 = std::min(b0, std::max(b, (int)d[k+9]));
|
|
||||||
}
|
|
||||||
|
|
||||||
threshold = -b0-1;
|
|
||||||
#endif
|
|
||||||
|
|
||||||
#if 0
|
|
||||||
testCorner(ptr, pixel, K, N, threshold);
|
|
||||||
#endif
|
|
||||||
return threshold;
|
|
||||||
}
|
|
||||||
|
|
||||||
template<>
|
|
||||||
int cornerScore<12>(const uchar* ptr, const int pixel[], int threshold)
|
|
||||||
{
|
|
||||||
const int K = 6, N = 12 + K + 1;
|
|
||||||
int k, v = ptr[0];
|
|
||||||
short d[N];
|
|
||||||
for( k = 0; k < N; k++ )
|
|
||||||
d[k] = (short)(v - ptr[pixel[k]]);
|
|
||||||
|
|
||||||
#if CV_SSE2
|
|
||||||
__m128i q0 = _mm_set1_epi16(-1000), q1 = _mm_set1_epi16(1000);
|
|
||||||
for( k = 0; k < 16; k += 8 )
|
|
||||||
{
|
|
||||||
__m128i v0 = _mm_loadu_si128((__m128i*)(d+k+1));
|
|
||||||
__m128i v1 = _mm_loadu_si128((__m128i*)(d+k+2));
|
|
||||||
__m128i a = _mm_min_epi16(v0, v1);
|
|
||||||
__m128i b = _mm_max_epi16(v0, v1);
|
|
||||||
v0 = _mm_loadu_si128((__m128i*)(d+k+3));
|
|
||||||
a = _mm_min_epi16(a, v0);
|
|
||||||
b = _mm_max_epi16(b, v0);
|
|
||||||
v0 = _mm_loadu_si128((__m128i*)(d+k+4));
|
|
||||||
a = _mm_min_epi16(a, v0);
|
|
||||||
b = _mm_max_epi16(b, v0);
|
|
||||||
v0 = _mm_loadu_si128((__m128i*)(d+k+5));
|
|
||||||
a = _mm_min_epi16(a, v0);
|
|
||||||
b = _mm_max_epi16(b, v0);
|
|
||||||
v0 = _mm_loadu_si128((__m128i*)(d+k+6));
|
|
||||||
a = _mm_min_epi16(a, v0);
|
|
||||||
b = _mm_max_epi16(b, v0);
|
|
||||||
v0 = _mm_loadu_si128((__m128i*)(d+k));
|
|
||||||
q0 = _mm_max_epi16(q0, _mm_min_epi16(a, v0));
|
|
||||||
q1 = _mm_min_epi16(q1, _mm_max_epi16(b, v0));
|
|
||||||
v0 = _mm_loadu_si128((__m128i*)(d+k+7));
|
|
||||||
q0 = _mm_max_epi16(q0, _mm_min_epi16(a, v0));
|
|
||||||
q1 = _mm_min_epi16(q1, _mm_max_epi16(b, v0));
|
|
||||||
}
|
|
||||||
q0 = _mm_max_epi16(q0, _mm_sub_epi16(_mm_setzero_si128(), q1));
|
|
||||||
q0 = _mm_max_epi16(q0, _mm_unpackhi_epi64(q0, q0));
|
|
||||||
q0 = _mm_max_epi16(q0, _mm_srli_si128(q0, 4));
|
|
||||||
q0 = _mm_max_epi16(q0, _mm_srli_si128(q0, 2));
|
|
||||||
threshold = (short)_mm_cvtsi128_si32(q0) - 1;
|
|
||||||
#else
|
|
||||||
int a0 = threshold;
|
|
||||||
for( k = 0; k < 12; k += 2 )
|
|
||||||
{
|
|
||||||
int a = std::min((int)d[k+1], (int)d[k+2]);
|
|
||||||
if( a <= a0 )
|
|
||||||
continue;
|
|
||||||
a = std::min(a, (int)d[k+3]);
|
|
||||||
a = std::min(a, (int)d[k+4]);
|
|
||||||
a = std::min(a, (int)d[k+5]);
|
|
||||||
a = std::min(a, (int)d[k+6]);
|
|
||||||
a0 = std::max(a0, std::min(a, (int)d[k]));
|
|
||||||
a0 = std::max(a0, std::min(a, (int)d[k+7]));
|
|
||||||
}
|
|
||||||
|
|
||||||
int b0 = -a0;
|
|
||||||
for( k = 0; k < 12; k += 2 )
|
|
||||||
{
|
|
||||||
int b = std::max((int)d[k+1], (int)d[k+2]);
|
|
||||||
b = std::max(b, (int)d[k+3]);
|
|
||||||
b = std::max(b, (int)d[k+4]);
|
|
||||||
if( b >= b0 )
|
|
||||||
continue;
|
|
||||||
b = std::max(b, (int)d[k+5]);
|
|
||||||
b = std::max(b, (int)d[k+6]);
|
|
||||||
|
|
||||||
b0 = std::min(b0, std::max(b, (int)d[k]));
|
|
||||||
b0 = std::min(b0, std::max(b, (int)d[k+7]));
|
|
||||||
}
|
|
||||||
|
|
||||||
threshold = -b0-1;
|
|
||||||
#endif
|
|
||||||
|
|
||||||
#if 0
|
|
||||||
testCorner(ptr, pixel, K, N, threshold);
|
|
||||||
#endif
|
|
||||||
return threshold;
|
|
||||||
}
|
|
||||||
|
|
||||||
template<>
|
|
||||||
int cornerScore<8>(const uchar* ptr, const int pixel[], int threshold)
|
|
||||||
{
|
|
||||||
const int K = 4, N = 8 + K + 1;
|
|
||||||
int k, v = ptr[0];
|
|
||||||
short d[N];
|
|
||||||
for( k = 0; k < N; k++ )
|
|
||||||
d[k] = (short)(v - ptr[pixel[k]]);
|
|
||||||
|
|
||||||
#if CV_SSE2
|
|
||||||
__m128i q0 = _mm_set1_epi16(-1000), q1 = _mm_set1_epi16(1000);
|
|
||||||
for( k = 0; k < 16; k += 8 )
|
|
||||||
{
|
|
||||||
__m128i v0 = _mm_loadu_si128((__m128i*)(d+k+1));
|
|
||||||
__m128i v1 = _mm_loadu_si128((__m128i*)(d+k+2));
|
|
||||||
__m128i a = _mm_min_epi16(v0, v1);
|
|
||||||
__m128i b = _mm_max_epi16(v0, v1);
|
|
||||||
v0 = _mm_loadu_si128((__m128i*)(d+k+3));
|
|
||||||
a = _mm_min_epi16(a, v0);
|
|
||||||
b = _mm_max_epi16(b, v0);
|
|
||||||
v0 = _mm_loadu_si128((__m128i*)(d+k+4));
|
|
||||||
a = _mm_min_epi16(a, v0);
|
|
||||||
b = _mm_max_epi16(b, v0);
|
|
||||||
v0 = _mm_loadu_si128((__m128i*)(d+k));
|
|
||||||
q0 = _mm_max_epi16(q0, _mm_min_epi16(a, v0));
|
|
||||||
q1 = _mm_min_epi16(q1, _mm_max_epi16(b, v0));
|
|
||||||
v0 = _mm_loadu_si128((__m128i*)(d+k+5));
|
|
||||||
q0 = _mm_max_epi16(q0, _mm_min_epi16(a, v0));
|
|
||||||
q1 = _mm_min_epi16(q1, _mm_max_epi16(b, v0));
|
|
||||||
}
|
|
||||||
q0 = _mm_max_epi16(q0, _mm_sub_epi16(_mm_setzero_si128(), q1));
|
|
||||||
q0 = _mm_max_epi16(q0, _mm_unpackhi_epi64(q0, q0));
|
|
||||||
q0 = _mm_max_epi16(q0, _mm_srli_si128(q0, 4));
|
|
||||||
q0 = _mm_max_epi16(q0, _mm_srli_si128(q0, 2));
|
|
||||||
threshold = (short)_mm_cvtsi128_si32(q0) - 1;
|
|
||||||
#else
|
|
||||||
int a0 = threshold;
|
|
||||||
for( k = 0; k < 8; k += 2 )
|
|
||||||
{
|
|
||||||
int a = std::min((int)d[k+1], (int)d[k+2]);
|
|
||||||
if( a <= a0 )
|
|
||||||
continue;
|
|
||||||
a = std::min(a, (int)d[k+3]);
|
|
||||||
a = std::min(a, (int)d[k+4]);
|
|
||||||
a0 = std::max(a0, std::min(a, (int)d[k]));
|
|
||||||
a0 = std::max(a0, std::min(a, (int)d[k+5]));
|
|
||||||
}
|
|
||||||
|
|
||||||
int b0 = -a0;
|
|
||||||
for( k = 0; k < 8; k += 2 )
|
|
||||||
{
|
|
||||||
int b = std::max((int)d[k+1], (int)d[k+2]);
|
|
||||||
b = std::max(b, (int)d[k+3]);
|
|
||||||
if( b >= b0 )
|
|
||||||
continue;
|
|
||||||
b = std::max(b, (int)d[k+4]);
|
|
||||||
|
|
||||||
b0 = std::min(b0, std::max(b, (int)d[k]));
|
|
||||||
b0 = std::min(b0, std::max(b, (int)d[k+5]));
|
|
||||||
}
|
|
||||||
|
|
||||||
threshold = -b0-1;
|
|
||||||
#endif
|
|
||||||
|
|
||||||
#if 0
|
|
||||||
testCorner(ptr, pixel, K, N, threshold);
|
|
||||||
#endif
|
|
||||||
return threshold;
|
|
||||||
}
|
|
||||||
|
|
||||||
template<int patternSize>
|
template<int patternSize>
|
||||||
void FAST_t(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool nonmax_suppression)
|
void FAST_t(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool nonmax_suppression)
|
||||||
{
|
{
|
||||||
@ -381,8 +57,6 @@ void FAST_t(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bo
|
|||||||
#endif
|
#endif
|
||||||
int i, j, k, pixel[25];
|
int i, j, k, pixel[25];
|
||||||
makeOffsets(pixel, (int)img.step, patternSize);
|
makeOffsets(pixel, (int)img.step, patternSize);
|
||||||
for(k = patternSize; k < 25; k++)
|
|
||||||
pixel[k] = pixel[k - patternSize];
|
|
||||||
|
|
||||||
keypoints.clear();
|
keypoints.clear();
|
||||||
|
|
||||||
|
374
modules/features2d/src/fast_score.cpp
Normal file
374
modules/features2d/src/fast_score.cpp
Normal file
@ -0,0 +1,374 @@
|
|||||||
|
/* This is FAST corner detector, contributed to OpenCV by the author, Edward Rosten.
|
||||||
|
Below is the original copyright and the references */
|
||||||
|
|
||||||
|
/*
|
||||||
|
Copyright (c) 2006, 2008 Edward Rosten
|
||||||
|
All rights reserved.
|
||||||
|
|
||||||
|
Redistribution and use in source and binary forms, with or without
|
||||||
|
modification, are permitted provided that the following conditions
|
||||||
|
are met:
|
||||||
|
|
||||||
|
*Redistributions of source code must retain the above copyright
|
||||||
|
notice, this list of conditions and the following disclaimer.
|
||||||
|
|
||||||
|
*Redistributions in binary form must reproduce the above copyright
|
||||||
|
notice, this list of conditions and the following disclaimer in the
|
||||||
|
documentation and/or other materials provided with the distribution.
|
||||||
|
|
||||||
|
*Neither the name of the University of Cambridge nor the names of
|
||||||
|
its contributors may 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 IMPLIED WARRANTIES, INCLUDING, BUT NOT
|
||||||
|
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
|
||||||
|
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER 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.
|
||||||
|
*/
|
||||||
|
|
||||||
|
/*
|
||||||
|
The references are:
|
||||||
|
* Machine learning for high-speed corner detection,
|
||||||
|
E. Rosten and T. Drummond, ECCV 2006
|
||||||
|
* Faster and better: A machine learning approach to corner detection
|
||||||
|
E. Rosten, R. Porter and T. Drummond, PAMI, 2009
|
||||||
|
*/
|
||||||
|
|
||||||
|
#include "fast_score.hpp"
|
||||||
|
|
||||||
|
namespace cv
|
||||||
|
{
|
||||||
|
|
||||||
|
void makeOffsets(int pixel[25], int row_stride, int patternSize)
|
||||||
|
{
|
||||||
|
CV_Assert(pixel != 0);
|
||||||
|
switch(patternSize) {
|
||||||
|
case 16:
|
||||||
|
pixel[0] = 0 + row_stride * 3;
|
||||||
|
pixel[1] = 1 + row_stride * 3;
|
||||||
|
pixel[2] = 2 + row_stride * 2;
|
||||||
|
pixel[3] = 3 + row_stride * 1;
|
||||||
|
pixel[4] = 3 + row_stride * 0;
|
||||||
|
pixel[5] = 3 + row_stride * -1;
|
||||||
|
pixel[6] = 2 + row_stride * -2;
|
||||||
|
pixel[7] = 1 + row_stride * -3;
|
||||||
|
pixel[8] = 0 + row_stride * -3;
|
||||||
|
pixel[9] = -1 + row_stride * -3;
|
||||||
|
pixel[10] = -2 + row_stride * -2;
|
||||||
|
pixel[11] = -3 + row_stride * -1;
|
||||||
|
pixel[12] = -3 + row_stride * 0;
|
||||||
|
pixel[13] = -3 + row_stride * 1;
|
||||||
|
pixel[14] = -2 + row_stride * 2;
|
||||||
|
pixel[15] = -1 + row_stride * 3;
|
||||||
|
break;
|
||||||
|
case 12:
|
||||||
|
pixel[0] = 0 + row_stride * 2;
|
||||||
|
pixel[1] = 1 + row_stride * 2;
|
||||||
|
pixel[2] = 2 + row_stride * 1;
|
||||||
|
pixel[3] = 2 + row_stride * 0;
|
||||||
|
pixel[4] = 2 + row_stride * -1;
|
||||||
|
pixel[5] = 1 + row_stride * -2;
|
||||||
|
pixel[6] = 0 + row_stride * -2;
|
||||||
|
pixel[7] = -1 + row_stride * -2;
|
||||||
|
pixel[8] = -2 + row_stride * -1;
|
||||||
|
pixel[9] = -2 + row_stride * 0;
|
||||||
|
pixel[10] = -2 + row_stride * 1;
|
||||||
|
pixel[11] = -1 + row_stride * 2;
|
||||||
|
break;
|
||||||
|
case 8:
|
||||||
|
pixel[0] = 0 + row_stride * 1;
|
||||||
|
pixel[1] = 1 + row_stride * 1;
|
||||||
|
pixel[2] = 1 + row_stride * 0;
|
||||||
|
pixel[3] = 1 + row_stride * -1;
|
||||||
|
pixel[4] = 0 + row_stride * -1;
|
||||||
|
pixel[5] = -1 + row_stride * -1;
|
||||||
|
pixel[6] = 0 + row_stride * 0;
|
||||||
|
pixel[7] = 1 + row_stride * 1;
|
||||||
|
break;
|
||||||
|
}
|
||||||
|
for(int k = patternSize; k < 25; k++)
|
||||||
|
pixel[k] = pixel[k - patternSize];
|
||||||
|
}
|
||||||
|
|
||||||
|
/*static void testCorner(const uchar* ptr, const int pixel[], int K, int N, int threshold) {
|
||||||
|
// check that with the computed "threshold" the pixel is still a corner
|
||||||
|
// and that with the increased-by-1 "threshold" the pixel is not a corner anymore
|
||||||
|
for( int delta = 0; delta <= 1; delta++ )
|
||||||
|
{
|
||||||
|
int v0 = std::min(ptr[0] + threshold + delta, 255);
|
||||||
|
int v1 = std::max(ptr[0] - threshold - delta, 0);
|
||||||
|
int c0 = 0, c1 = 0;
|
||||||
|
|
||||||
|
for( int k = 0; k < N; k++ )
|
||||||
|
{
|
||||||
|
int x = ptr[pixel[k]];
|
||||||
|
if(x > v0)
|
||||||
|
{
|
||||||
|
if( ++c0 > K )
|
||||||
|
break;
|
||||||
|
c1 = 0;
|
||||||
|
}
|
||||||
|
else if( x < v1 )
|
||||||
|
{
|
||||||
|
if( ++c1 > K )
|
||||||
|
break;
|
||||||
|
c0 = 0;
|
||||||
|
}
|
||||||
|
else
|
||||||
|
{
|
||||||
|
c0 = c1 = 0;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
CV_Assert( (delta == 0 && std::max(c0, c1) > K) ||
|
||||||
|
(delta == 1 && std::max(c0, c1) <= K) );
|
||||||
|
}
|
||||||
|
}*/
|
||||||
|
|
||||||
|
template<>
|
||||||
|
int cornerScore<16>(const uchar* ptr, const int pixel[], int threshold)
|
||||||
|
{
|
||||||
|
const int K = 8, N = 16 + K + 1;
|
||||||
|
int k, v = ptr[0];
|
||||||
|
short d[N];
|
||||||
|
for( k = 0; k < N; k++ )
|
||||||
|
d[k] = (short)(v - ptr[pixel[k]]);
|
||||||
|
|
||||||
|
#if CV_SSE2
|
||||||
|
__m128i q0 = _mm_set1_epi16(-1000), q1 = _mm_set1_epi16(1000);
|
||||||
|
for( k = 0; k < 16; k += 8 )
|
||||||
|
{
|
||||||
|
__m128i v0 = _mm_loadu_si128((__m128i*)(d+k+1));
|
||||||
|
__m128i v1 = _mm_loadu_si128((__m128i*)(d+k+2));
|
||||||
|
__m128i a = _mm_min_epi16(v0, v1);
|
||||||
|
__m128i b = _mm_max_epi16(v0, v1);
|
||||||
|
v0 = _mm_loadu_si128((__m128i*)(d+k+3));
|
||||||
|
a = _mm_min_epi16(a, v0);
|
||||||
|
b = _mm_max_epi16(b, v0);
|
||||||
|
v0 = _mm_loadu_si128((__m128i*)(d+k+4));
|
||||||
|
a = _mm_min_epi16(a, v0);
|
||||||
|
b = _mm_max_epi16(b, v0);
|
||||||
|
v0 = _mm_loadu_si128((__m128i*)(d+k+5));
|
||||||
|
a = _mm_min_epi16(a, v0);
|
||||||
|
b = _mm_max_epi16(b, v0);
|
||||||
|
v0 = _mm_loadu_si128((__m128i*)(d+k+6));
|
||||||
|
a = _mm_min_epi16(a, v0);
|
||||||
|
b = _mm_max_epi16(b, v0);
|
||||||
|
v0 = _mm_loadu_si128((__m128i*)(d+k+7));
|
||||||
|
a = _mm_min_epi16(a, v0);
|
||||||
|
b = _mm_max_epi16(b, v0);
|
||||||
|
v0 = _mm_loadu_si128((__m128i*)(d+k+8));
|
||||||
|
a = _mm_min_epi16(a, v0);
|
||||||
|
b = _mm_max_epi16(b, v0);
|
||||||
|
v0 = _mm_loadu_si128((__m128i*)(d+k));
|
||||||
|
q0 = _mm_max_epi16(q0, _mm_min_epi16(a, v0));
|
||||||
|
q1 = _mm_min_epi16(q1, _mm_max_epi16(b, v0));
|
||||||
|
v0 = _mm_loadu_si128((__m128i*)(d+k+9));
|
||||||
|
q0 = _mm_max_epi16(q0, _mm_min_epi16(a, v0));
|
||||||
|
q1 = _mm_min_epi16(q1, _mm_max_epi16(b, v0));
|
||||||
|
}
|
||||||
|
q0 = _mm_max_epi16(q0, _mm_sub_epi16(_mm_setzero_si128(), q1));
|
||||||
|
q0 = _mm_max_epi16(q0, _mm_unpackhi_epi64(q0, q0));
|
||||||
|
q0 = _mm_max_epi16(q0, _mm_srli_si128(q0, 4));
|
||||||
|
q0 = _mm_max_epi16(q0, _mm_srli_si128(q0, 2));
|
||||||
|
threshold = (short)_mm_cvtsi128_si32(q0) - 1;
|
||||||
|
#else
|
||||||
|
int a0 = threshold;
|
||||||
|
for( k = 0; k < 16; k += 2 )
|
||||||
|
{
|
||||||
|
int a = std::min((int)d[k+1], (int)d[k+2]);
|
||||||
|
a = std::min(a, (int)d[k+3]);
|
||||||
|
if( a <= a0 )
|
||||||
|
continue;
|
||||||
|
a = std::min(a, (int)d[k+4]);
|
||||||
|
a = std::min(a, (int)d[k+5]);
|
||||||
|
a = std::min(a, (int)d[k+6]);
|
||||||
|
a = std::min(a, (int)d[k+7]);
|
||||||
|
a = std::min(a, (int)d[k+8]);
|
||||||
|
a0 = std::max(a0, std::min(a, (int)d[k]));
|
||||||
|
a0 = std::max(a0, std::min(a, (int)d[k+9]));
|
||||||
|
}
|
||||||
|
|
||||||
|
int b0 = -a0;
|
||||||
|
for( k = 0; k < 16; k += 2 )
|
||||||
|
{
|
||||||
|
int b = std::max((int)d[k+1], (int)d[k+2]);
|
||||||
|
b = std::max(b, (int)d[k+3]);
|
||||||
|
b = std::max(b, (int)d[k+4]);
|
||||||
|
b = std::max(b, (int)d[k+5]);
|
||||||
|
if( b >= b0 )
|
||||||
|
continue;
|
||||||
|
b = std::max(b, (int)d[k+6]);
|
||||||
|
b = std::max(b, (int)d[k+7]);
|
||||||
|
b = std::max(b, (int)d[k+8]);
|
||||||
|
|
||||||
|
b0 = std::min(b0, std::max(b, (int)d[k]));
|
||||||
|
b0 = std::min(b0, std::max(b, (int)d[k+9]));
|
||||||
|
}
|
||||||
|
|
||||||
|
threshold = -b0-1;
|
||||||
|
#endif
|
||||||
|
|
||||||
|
#if 0
|
||||||
|
testCorner(ptr, pixel, K, N, threshold);
|
||||||
|
#endif
|
||||||
|
return threshold;
|
||||||
|
}
|
||||||
|
|
||||||
|
template<>
|
||||||
|
int cornerScore<12>(const uchar* ptr, const int pixel[], int threshold)
|
||||||
|
{
|
||||||
|
const int K = 6, N = 12 + K + 1;
|
||||||
|
int k, v = ptr[0];
|
||||||
|
short d[N];
|
||||||
|
for( k = 0; k < N; k++ )
|
||||||
|
d[k] = (short)(v - ptr[pixel[k]]);
|
||||||
|
|
||||||
|
#if CV_SSE2
|
||||||
|
__m128i q0 = _mm_set1_epi16(-1000), q1 = _mm_set1_epi16(1000);
|
||||||
|
for( k = 0; k < 16; k += 8 )
|
||||||
|
{
|
||||||
|
__m128i v0 = _mm_loadu_si128((__m128i*)(d+k+1));
|
||||||
|
__m128i v1 = _mm_loadu_si128((__m128i*)(d+k+2));
|
||||||
|
__m128i a = _mm_min_epi16(v0, v1);
|
||||||
|
__m128i b = _mm_max_epi16(v0, v1);
|
||||||
|
v0 = _mm_loadu_si128((__m128i*)(d+k+3));
|
||||||
|
a = _mm_min_epi16(a, v0);
|
||||||
|
b = _mm_max_epi16(b, v0);
|
||||||
|
v0 = _mm_loadu_si128((__m128i*)(d+k+4));
|
||||||
|
a = _mm_min_epi16(a, v0);
|
||||||
|
b = _mm_max_epi16(b, v0);
|
||||||
|
v0 = _mm_loadu_si128((__m128i*)(d+k+5));
|
||||||
|
a = _mm_min_epi16(a, v0);
|
||||||
|
b = _mm_max_epi16(b, v0);
|
||||||
|
v0 = _mm_loadu_si128((__m128i*)(d+k+6));
|
||||||
|
a = _mm_min_epi16(a, v0);
|
||||||
|
b = _mm_max_epi16(b, v0);
|
||||||
|
v0 = _mm_loadu_si128((__m128i*)(d+k));
|
||||||
|
q0 = _mm_max_epi16(q0, _mm_min_epi16(a, v0));
|
||||||
|
q1 = _mm_min_epi16(q1, _mm_max_epi16(b, v0));
|
||||||
|
v0 = _mm_loadu_si128((__m128i*)(d+k+7));
|
||||||
|
q0 = _mm_max_epi16(q0, _mm_min_epi16(a, v0));
|
||||||
|
q1 = _mm_min_epi16(q1, _mm_max_epi16(b, v0));
|
||||||
|
}
|
||||||
|
q0 = _mm_max_epi16(q0, _mm_sub_epi16(_mm_setzero_si128(), q1));
|
||||||
|
q0 = _mm_max_epi16(q0, _mm_unpackhi_epi64(q0, q0));
|
||||||
|
q0 = _mm_max_epi16(q0, _mm_srli_si128(q0, 4));
|
||||||
|
q0 = _mm_max_epi16(q0, _mm_srli_si128(q0, 2));
|
||||||
|
threshold = (short)_mm_cvtsi128_si32(q0) - 1;
|
||||||
|
#else
|
||||||
|
int a0 = threshold;
|
||||||
|
for( k = 0; k < 12; k += 2 )
|
||||||
|
{
|
||||||
|
int a = std::min((int)d[k+1], (int)d[k+2]);
|
||||||
|
if( a <= a0 )
|
||||||
|
continue;
|
||||||
|
a = std::min(a, (int)d[k+3]);
|
||||||
|
a = std::min(a, (int)d[k+4]);
|
||||||
|
a = std::min(a, (int)d[k+5]);
|
||||||
|
a = std::min(a, (int)d[k+6]);
|
||||||
|
a0 = std::max(a0, std::min(a, (int)d[k]));
|
||||||
|
a0 = std::max(a0, std::min(a, (int)d[k+7]));
|
||||||
|
}
|
||||||
|
|
||||||
|
int b0 = -a0;
|
||||||
|
for( k = 0; k < 12; k += 2 )
|
||||||
|
{
|
||||||
|
int b = std::max((int)d[k+1], (int)d[k+2]);
|
||||||
|
b = std::max(b, (int)d[k+3]);
|
||||||
|
b = std::max(b, (int)d[k+4]);
|
||||||
|
if( b >= b0 )
|
||||||
|
continue;
|
||||||
|
b = std::max(b, (int)d[k+5]);
|
||||||
|
b = std::max(b, (int)d[k+6]);
|
||||||
|
|
||||||
|
b0 = std::min(b0, std::max(b, (int)d[k]));
|
||||||
|
b0 = std::min(b0, std::max(b, (int)d[k+7]));
|
||||||
|
}
|
||||||
|
|
||||||
|
threshold = -b0-1;
|
||||||
|
#endif
|
||||||
|
|
||||||
|
#if 0
|
||||||
|
testCorner(ptr, pixel, K, N, threshold);
|
||||||
|
#endif
|
||||||
|
return threshold;
|
||||||
|
}
|
||||||
|
|
||||||
|
template<>
|
||||||
|
int cornerScore<8>(const uchar* ptr, const int pixel[], int threshold)
|
||||||
|
{
|
||||||
|
const int K = 4, N = 8 + K + 1;
|
||||||
|
int k, v = ptr[0];
|
||||||
|
short d[N];
|
||||||
|
for( k = 0; k < N; k++ )
|
||||||
|
d[k] = (short)(v - ptr[pixel[k]]);
|
||||||
|
|
||||||
|
#if CV_SSE2
|
||||||
|
__m128i q0 = _mm_set1_epi16(-1000), q1 = _mm_set1_epi16(1000);
|
||||||
|
for( k = 0; k < 16; k += 8 )
|
||||||
|
{
|
||||||
|
__m128i v0 = _mm_loadu_si128((__m128i*)(d+k+1));
|
||||||
|
__m128i v1 = _mm_loadu_si128((__m128i*)(d+k+2));
|
||||||
|
__m128i a = _mm_min_epi16(v0, v1);
|
||||||
|
__m128i b = _mm_max_epi16(v0, v1);
|
||||||
|
v0 = _mm_loadu_si128((__m128i*)(d+k+3));
|
||||||
|
a = _mm_min_epi16(a, v0);
|
||||||
|
b = _mm_max_epi16(b, v0);
|
||||||
|
v0 = _mm_loadu_si128((__m128i*)(d+k+4));
|
||||||
|
a = _mm_min_epi16(a, v0);
|
||||||
|
b = _mm_max_epi16(b, v0);
|
||||||
|
v0 = _mm_loadu_si128((__m128i*)(d+k));
|
||||||
|
q0 = _mm_max_epi16(q0, _mm_min_epi16(a, v0));
|
||||||
|
q1 = _mm_min_epi16(q1, _mm_max_epi16(b, v0));
|
||||||
|
v0 = _mm_loadu_si128((__m128i*)(d+k+5));
|
||||||
|
q0 = _mm_max_epi16(q0, _mm_min_epi16(a, v0));
|
||||||
|
q1 = _mm_min_epi16(q1, _mm_max_epi16(b, v0));
|
||||||
|
}
|
||||||
|
q0 = _mm_max_epi16(q0, _mm_sub_epi16(_mm_setzero_si128(), q1));
|
||||||
|
q0 = _mm_max_epi16(q0, _mm_unpackhi_epi64(q0, q0));
|
||||||
|
q0 = _mm_max_epi16(q0, _mm_srli_si128(q0, 4));
|
||||||
|
q0 = _mm_max_epi16(q0, _mm_srli_si128(q0, 2));
|
||||||
|
threshold = (short)_mm_cvtsi128_si32(q0) - 1;
|
||||||
|
#else
|
||||||
|
int a0 = threshold;
|
||||||
|
for( k = 0; k < 8; k += 2 )
|
||||||
|
{
|
||||||
|
int a = std::min((int)d[k+1], (int)d[k+2]);
|
||||||
|
if( a <= a0 )
|
||||||
|
continue;
|
||||||
|
a = std::min(a, (int)d[k+3]);
|
||||||
|
a = std::min(a, (int)d[k+4]);
|
||||||
|
a0 = std::max(a0, std::min(a, (int)d[k]));
|
||||||
|
a0 = std::max(a0, std::min(a, (int)d[k+5]));
|
||||||
|
}
|
||||||
|
|
||||||
|
int b0 = -a0;
|
||||||
|
for( k = 0; k < 8; k += 2 )
|
||||||
|
{
|
||||||
|
int b = std::max((int)d[k+1], (int)d[k+2]);
|
||||||
|
b = std::max(b, (int)d[k+3]);
|
||||||
|
if( b >= b0 )
|
||||||
|
continue;
|
||||||
|
b = std::max(b, (int)d[k+4]);
|
||||||
|
|
||||||
|
b0 = std::min(b0, std::max(b, (int)d[k]));
|
||||||
|
b0 = std::min(b0, std::max(b, (int)d[k+5]));
|
||||||
|
}
|
||||||
|
|
||||||
|
threshold = -b0-1;
|
||||||
|
#endif
|
||||||
|
|
||||||
|
#if 0
|
||||||
|
testCorner(ptr, pixel, K, N, threshold);
|
||||||
|
#endif
|
||||||
|
return threshold;
|
||||||
|
}
|
||||||
|
|
||||||
|
}
|
64
modules/features2d/src/fast_score.hpp
Normal file
64
modules/features2d/src/fast_score.hpp
Normal file
@ -0,0 +1,64 @@
|
|||||||
|
/* This is FAST corner detector, contributed to OpenCV by the author, Edward Rosten.
|
||||||
|
Below is the original copyright and the references */
|
||||||
|
|
||||||
|
/*
|
||||||
|
Copyright (c) 2006, 2008 Edward Rosten
|
||||||
|
All rights reserved.
|
||||||
|
|
||||||
|
Redistribution and use in source and binary forms, with or without
|
||||||
|
modification, are permitted provided that the following conditions
|
||||||
|
are met:
|
||||||
|
|
||||||
|
*Redistributions of source code must retain the above copyright
|
||||||
|
notice, this list of conditions and the following disclaimer.
|
||||||
|
|
||||||
|
*Redistributions in binary form must reproduce the above copyright
|
||||||
|
notice, this list of conditions and the following disclaimer in the
|
||||||
|
documentation and/or other materials provided with the distribution.
|
||||||
|
|
||||||
|
*Neither the name of the University of Cambridge nor the names of
|
||||||
|
its contributors may 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 IMPLIED WARRANTIES, INCLUDING, BUT NOT
|
||||||
|
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
|
||||||
|
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER 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.
|
||||||
|
*/
|
||||||
|
|
||||||
|
/*
|
||||||
|
The references are:
|
||||||
|
* Machine learning for high-speed corner detection,
|
||||||
|
E. Rosten and T. Drummond, ECCV 2006
|
||||||
|
* Faster and better: A machine learning approach to corner detection
|
||||||
|
E. Rosten, R. Porter and T. Drummond, PAMI, 2009
|
||||||
|
*/
|
||||||
|
|
||||||
|
#ifndef __OPENCV_FEATURES_2D_FAST_HPP__
|
||||||
|
#define __OPENCV_FEATURES_2D_FAST_HPP__
|
||||||
|
|
||||||
|
#ifdef __cplusplus
|
||||||
|
|
||||||
|
#include "precomp.hpp"
|
||||||
|
|
||||||
|
namespace cv
|
||||||
|
{
|
||||||
|
|
||||||
|
void makeOffsets(int pixel[25], int row_stride, int patternSize);
|
||||||
|
|
||||||
|
//static void testCorner(const uchar* ptr, const int pixel[], int K, int N, int threshold);
|
||||||
|
|
||||||
|
template<int patternSize>
|
||||||
|
int cornerScore(const uchar* ptr, const int pixel[], int threshold);
|
||||||
|
|
||||||
|
}
|
||||||
|
|
||||||
|
#endif
|
||||||
|
#endif
|
@ -51,6 +51,12 @@ using namespace cv;
|
|||||||
Otherwise, linker may throw away some seemingly unused stuff.
|
Otherwise, linker may throw away some seemingly unused stuff.
|
||||||
*/
|
*/
|
||||||
|
|
||||||
|
CV_INIT_ALGORITHM(BRISK, "Feature2D.BRISK",
|
||||||
|
obj.info()->addParam(obj, "thres", obj.threshold);
|
||||||
|
obj.info()->addParam(obj, "octaves", obj.octaves));
|
||||||
|
|
||||||
|
///////////////////////////////////////////////////////////////////////////////////////////////////////////
|
||||||
|
|
||||||
CV_INIT_ALGORITHM(BriefDescriptorExtractor, "Feature2D.BRIEF",
|
CV_INIT_ALGORITHM(BriefDescriptorExtractor, "Feature2D.BRIEF",
|
||||||
obj.info()->addParam(obj, "bytes", obj.bytes_));
|
obj.info()->addParam(obj, "bytes", obj.bytes_));
|
||||||
|
|
||||||
@ -154,6 +160,7 @@ bool cv::initModule_features2d(void)
|
|||||||
{
|
{
|
||||||
bool all = true;
|
bool all = true;
|
||||||
all &= !BriefDescriptorExtractor_info_auto.name().empty();
|
all &= !BriefDescriptorExtractor_info_auto.name().empty();
|
||||||
|
all &= !BRISK_info_auto.name().empty();
|
||||||
all &= !FastFeatureDetector_info_auto.name().empty();
|
all &= !FastFeatureDetector_info_auto.name().empty();
|
||||||
all &= !StarDetector_info_auto.name().empty();
|
all &= !StarDetector_info_auto.name().empty();
|
||||||
all &= !MSER_info_auto.name().empty();
|
all &= !MSER_info_auto.name().empty();
|
||||||
|
95
modules/features2d/test/test_brisk.cpp
Normal file
95
modules/features2d/test/test_brisk.cpp
Normal file
@ -0,0 +1,95 @@
|
|||||||
|
/*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 materials 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 implied warranties, including, but not limited to, the implied
|
||||||
|
// 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 "test_precomp.hpp"
|
||||||
|
|
||||||
|
using namespace cv;
|
||||||
|
|
||||||
|
class CV_BRISKTest : public cvtest::BaseTest
|
||||||
|
{
|
||||||
|
public:
|
||||||
|
CV_BRISKTest();
|
||||||
|
~CV_BRISKTest();
|
||||||
|
protected:
|
||||||
|
void run(int);
|
||||||
|
};
|
||||||
|
|
||||||
|
CV_BRISKTest::CV_BRISKTest() {}
|
||||||
|
CV_BRISKTest::~CV_BRISKTest() {}
|
||||||
|
|
||||||
|
void CV_BRISKTest::run( int )
|
||||||
|
{
|
||||||
|
Mat image1 = imread(string(ts->get_data_path()) + "inpaint/orig.jpg");
|
||||||
|
Mat image2 = imread(string(ts->get_data_path()) + "cameracalibration/chess9.jpg");
|
||||||
|
|
||||||
|
if (image1.empty() || image2.empty())
|
||||||
|
{
|
||||||
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
|
||||||
|
return;
|
||||||
|
}
|
||||||
|
|
||||||
|
Mat gray1, gray2;
|
||||||
|
cvtColor(image1, gray1, CV_BGR2GRAY);
|
||||||
|
cvtColor(image2, gray2, CV_BGR2GRAY);
|
||||||
|
|
||||||
|
Ptr<FeatureDetector> detector = Algorithm::create<FeatureDetector>("Feature2D.BRISK");
|
||||||
|
|
||||||
|
vector<KeyPoint> keypoints1;
|
||||||
|
vector<KeyPoint> keypoints2;
|
||||||
|
detector->detect(image1, keypoints1);
|
||||||
|
detector->detect(image2, keypoints2);
|
||||||
|
|
||||||
|
for(size_t i = 0; i < keypoints1.size(); ++i)
|
||||||
|
{
|
||||||
|
const KeyPoint& kp = keypoints1[i];
|
||||||
|
ASSERT_NE(kp.angle, -1);
|
||||||
|
}
|
||||||
|
|
||||||
|
for(size_t i = 0; i < keypoints2.size(); ++i)
|
||||||
|
{
|
||||||
|
const KeyPoint& kp = keypoints2[i];
|
||||||
|
ASSERT_NE(kp.angle, -1);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
TEST(Features2d_BRISK, regression) { CV_BRISKTest test; test.safe_run(); }
|
||||||
|
|
@ -301,6 +301,13 @@ private:
|
|||||||
* Tests registrations *
|
* Tests registrations *
|
||||||
\****************************************************************************************/
|
\****************************************************************************************/
|
||||||
|
|
||||||
|
TEST( Features2d_DescriptorExtractor_BRISK, regression )
|
||||||
|
{
|
||||||
|
CV_DescriptorExtractorTest<Hamming> test( "descriptor-brisk", (CV_DescriptorExtractorTest<Hamming>::DistanceType)2.f,
|
||||||
|
DescriptorExtractor::create("BRISK") );
|
||||||
|
test.safe_run();
|
||||||
|
}
|
||||||
|
|
||||||
TEST( Features2d_DescriptorExtractor_ORB, regression )
|
TEST( Features2d_DescriptorExtractor_ORB, regression )
|
||||||
{
|
{
|
||||||
// TODO adjust the parameters below
|
// TODO adjust the parameters below
|
||||||
|
@ -247,6 +247,12 @@ void CV_FeatureDetectorTest::run( int /*start_from*/ )
|
|||||||
* Tests registrations *
|
* Tests registrations *
|
||||||
\****************************************************************************************/
|
\****************************************************************************************/
|
||||||
|
|
||||||
|
TEST( Features2d_Detector_BRISK, regression )
|
||||||
|
{
|
||||||
|
CV_FeatureDetectorTest test( "detector-brisk", FeatureDetector::create("BRISK") );
|
||||||
|
test.safe_run();
|
||||||
|
}
|
||||||
|
|
||||||
TEST( Features2d_Detector_FAST, regression )
|
TEST( Features2d_Detector_FAST, regression )
|
||||||
{
|
{
|
||||||
CV_FeatureDetectorTest test( "detector-fast", FeatureDetector::create("FAST") );
|
CV_FeatureDetectorTest test( "detector-fast", FeatureDetector::create("FAST") );
|
||||||
|
@ -119,6 +119,12 @@ protected:
|
|||||||
|
|
||||||
// Registration of tests
|
// Registration of tests
|
||||||
|
|
||||||
|
TEST(Features2d_Detector_Keypoints_BRISK, validation)
|
||||||
|
{
|
||||||
|
CV_FeatureDetectorKeypointsTest test(Algorithm::create<FeatureDetector>("Feature2D.BRISK"));
|
||||||
|
test.safe_run();
|
||||||
|
}
|
||||||
|
|
||||||
TEST(Features2d_Detector_Keypoints_FAST, validation)
|
TEST(Features2d_Detector_Keypoints_FAST, validation)
|
||||||
{
|
{
|
||||||
CV_FeatureDetectorKeypointsTest test(Algorithm::create<FeatureDetector>("Feature2D.FAST"));
|
CV_FeatureDetectorKeypointsTest test(Algorithm::create<FeatureDetector>("Feature2D.FAST"));
|
||||||
|
@ -592,6 +592,15 @@ protected:
|
|||||||
/*
|
/*
|
||||||
* Detector's rotation invariance check
|
* Detector's rotation invariance check
|
||||||
*/
|
*/
|
||||||
|
|
||||||
|
TEST(Features2d_RotationInvariance_Detector_BRISK, regression)
|
||||||
|
{
|
||||||
|
DetectorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.BRISK"),
|
||||||
|
0.32f,
|
||||||
|
0.81f);
|
||||||
|
test.safe_run();
|
||||||
|
}
|
||||||
|
|
||||||
TEST(Features2d_RotationInvariance_Detector_ORB, regression)
|
TEST(Features2d_RotationInvariance_Detector_ORB, regression)
|
||||||
{
|
{
|
||||||
DetectorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
|
DetectorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
|
||||||
@ -603,6 +612,16 @@ TEST(Features2d_RotationInvariance_Detector_ORB, regression)
|
|||||||
/*
|
/*
|
||||||
* Descriptors's rotation invariance check
|
* Descriptors's rotation invariance check
|
||||||
*/
|
*/
|
||||||
|
|
||||||
|
TEST(Features2d_RotationInvariance_Descriptor_BRISK, regression)
|
||||||
|
{
|
||||||
|
DescriptorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.BRISK"),
|
||||||
|
Algorithm::create<DescriptorExtractor>("Feature2D.BRISK"),
|
||||||
|
NORM_HAMMING,
|
||||||
|
0.99f);
|
||||||
|
test.safe_run();
|
||||||
|
}
|
||||||
|
|
||||||
TEST(Features2d_RotationInvariance_Descriptor_ORB, regression)
|
TEST(Features2d_RotationInvariance_Descriptor_ORB, regression)
|
||||||
{
|
{
|
||||||
DescriptorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
|
DescriptorRotationInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
|
||||||
@ -625,6 +644,14 @@ TEST(Features2d_RotationInvariance_Descriptor_ORB, regression)
|
|||||||
* Detector's scale invariance check
|
* Detector's scale invariance check
|
||||||
*/
|
*/
|
||||||
|
|
||||||
|
TEST(Features2d_ScaleInvariance_Detector_BRISK, regression)
|
||||||
|
{
|
||||||
|
DetectorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.BRISK"),
|
||||||
|
0.08f,
|
||||||
|
0.54f);
|
||||||
|
test.safe_run();
|
||||||
|
}
|
||||||
|
|
||||||
//TEST(Features2d_ScaleInvariance_Detector_ORB, regression)
|
//TEST(Features2d_ScaleInvariance_Detector_ORB, regression)
|
||||||
//{
|
//{
|
||||||
// DetectorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
|
// DetectorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
|
||||||
@ -637,6 +664,15 @@ TEST(Features2d_RotationInvariance_Descriptor_ORB, regression)
|
|||||||
* Descriptor's scale invariance check
|
* Descriptor's scale invariance check
|
||||||
*/
|
*/
|
||||||
|
|
||||||
|
//TEST(Features2d_ScaleInvariance_Descriptor_BRISK, regression)
|
||||||
|
//{
|
||||||
|
// DescriptorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.BRISK"),
|
||||||
|
// Algorithm::create<DescriptorExtractor>("Feature2D.BRISK"),
|
||||||
|
// NORM_HAMMING,
|
||||||
|
// 0.99f);
|
||||||
|
// test.safe_run();
|
||||||
|
//}
|
||||||
|
|
||||||
//TEST(Features2d_ScaleInvariance_Descriptor_ORB, regression)
|
//TEST(Features2d_ScaleInvariance_Descriptor_ORB, regression)
|
||||||
//{
|
//{
|
||||||
// DescriptorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
|
// DescriptorScaleInvarianceTest test(Algorithm::create<FeatureDetector>("Feature2D.ORB"),
|
||||||
|
@ -1314,7 +1314,7 @@ public:
|
|||||||
ssize.width *= cn;
|
ssize.width *= cn;
|
||||||
int dy, dx, k = 0;
|
int dy, dx, k = 0;
|
||||||
|
|
||||||
VecOp vop(scale_x, scale_y, src.channels(), src.step/*, area_ofs*/);
|
VecOp vop(scale_x, scale_y, src.channels(), (int)src.step/*, area_ofs*/);
|
||||||
|
|
||||||
for( dy = range.start; dy < range.end; dy++ )
|
for( dy = range.start; dy < range.end; dy++ )
|
||||||
{
|
{
|
||||||
|
Loading…
Reference in New Issue
Block a user