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提交 b74116e6 编写于 作者: V Vadim Pisarevsky
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unified norm computing; added generalized Hamming distance

上级 c1277b61
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Showing with 483 addition and 587 deletion
modules/core/include/opencv2/core/core.hpp
浏览文件 @ b74116e6
......@@ -598,6 +598,9 @@ public:
//! per-element multiplication
Vec mul(const Vec<_Tp, cn>& v) const;
//! conjugation (makes sense for complex numbers and quaternions)
Vec conj() const;
/*!
cross product of the two 3D vectors.
......
modules/core/include/opencv2/core/operations.hpp
浏览文件 @ b74116e6
......@@ -81,7 +81,7 @@
#define CV_XADD(addr,delta) InterlockedExchangeAdd((long volatile*)(addr), (delta))
#else
template<typename _Tp> static inline _Tp CV_XADD(_Tp* addr, _Tp delta)
static inline int CV_XADD(int* addr, int delta)
{ int tmp = *addr; *addr += delta; return tmp; }
#endif
......@@ -179,7 +179,14 @@ template<> inline int saturate_cast<int>(double v) { return cvRound(v); }
// we intentionally do not clip negative numbers, to make -1 become 0xffffffff etc.
template<> inline unsigned saturate_cast<unsigned>(float v){ return cvRound(v); }
template<> inline unsigned saturate_cast<unsigned>(double v) { return cvRound(v); }
inline int fast_abs(uchar v) { return v; }
inline int fast_abs(schar v) { return std::abs((int)v); }
inline int fast_abs(ushort v) { return v; }
inline int fast_abs(short v) { return std::abs((int)v); }
inline int fast_abs(int v) { return std::abs(v); }
inline float fast_abs(float v) { return std::abs(v); }
inline double fast_abs(double v) { return std::abs(v); }
//////////////////////////////// Matx /////////////////////////////////
......@@ -891,38 +898,152 @@ Matx<_Tp, n, l> Matx<_Tp, m, n>::solve(const Matx<_Tp, m, l>& rhs, int method) c
return ok ? x : Matx<_Tp, n, l>::zeros();
}
template<typename _Tp, typename _AccTp> static inline
_AccTp normL2Sqr(const _Tp* a, int n)
{
_AccTp s = 0;
int i;
for( i = 0; i <= n - 4; i += 4 )
{
_AccTp v0 = a[i], v1 = a[i+1], v2 = a[i+2], v3 = a[i+3];
s += v0*v0 + v1*v1 + v2*v2 + v3*v3;
}
for( ; i < n; i++ )
{
_AccTp v = a[i];
s += v*v;
}
return s;
}
template<typename _Tp, int m, int n> static inline
double norm(const Matx<_Tp, m, n>& M)
template<typename _Tp, typename _AccTp> static inline
_AccTp normL1(const _Tp* a, int n)
{
double s = 0;
for( int i = 0; i < m*n; i++ )
s += (double)M.val[i]*M.val[i];
return std::sqrt(s);
_AccTp s = 0;
int i;
for( i = 0; i <= n - 4; i += 4 )
{
s += (_AccTp)fast_abs(a[i]) + (_AccTp)fast_abs(a[i+1]) +
(_AccTp)fast_abs(a[i+2]) + (_AccTp)fast_abs(a[i+3]);
}
for( ; i < n; i++ )
s += fast_abs(a[i]);
return s;
}
template<typename _Tp, typename _AccTp> static inline
_AccTp normInf(const _Tp* a, int n)
{
_AccTp s = 0;
for( int i = 0; i < n; i++ )
s = std::max(s, (_AccTp)fast_abs(a[i]));
return s;
}
template<typename _Tp, int m, int n> static inline
double norm(const Matx<_Tp, m, n>& M, int normType)
template<typename _Tp, typename _AccTp> static inline
_AccTp normL2Sqr(const _Tp* a, const _Tp* b, int n)
{
if( normType == NORM_INF )
_AccTp s = 0;
int i;
for( i = 0; i <= n - 4; i += 4 )
{
_AccTp v0 = a[i] - b[i], v1 = a[i+1] - b[i+1], v2 = a[i+2] - b[i+2], v3 = a[i+3] - b[i+3];
s += v0*v0 + v1*v1 + v2*v2 + v3*v3;
}
for( ; i < n; i++ )
{
_Tp s = 0;
for( int i = 0; i < m*n; i++ )
s = std::max(s, std::abs(M.val[i]));
return s;
_AccTp v = a[i] - b[i];
s += v*v;
}
return s;
}
CV_EXPORTS float normL2Sqr_(const float* a, const float* b, int n);
CV_EXPORTS float normL1_(const float* a, const float* b, int n);
CV_EXPORTS int normL1_(const uchar* a, const uchar* b, int n);
CV_EXPORTS int normHamming(const uchar* a, const uchar* b, int n);
CV_EXPORTS int normHamming(const uchar* a, const uchar* b, int n, int cellSize);
if( normType == NORM_L1 )
template<> static inline float normL2Sqr(const float* a, const float* b, int n)
{
if( n >= 8 )
return normL2Sqr_(a, b, n);
float s = 0;
for( int i = 0; i < n; i++ )
{
_Tp s = 0;
for( int i = 0; i < m*n; i++ )
s += std::abs(M.val[i]);
return s;
float v = a[i] - b[i];
s += v*v;
}
return s;
}
CV_DbgAssert( normType == NORM_L2 );
return norm(M);
template<typename _Tp, typename _AccTp> static inline
_AccTp normL1(const _Tp* a, const _Tp* b, int n)
{
_AccTp s = 0;
int i;
for( i = 0; i <= n - 4; i += 4 )
{
_AccTp v0 = a[i] - b[i], v1 = a[i+1] - b[i+1], v2 = a[i+2] - b[i+2], v3 = a[i+3] - b[i+3];
s += std::abs(v0) + std::abs(v1) + std::abs(v2) + std::abs(v3);
}
for( ; i < n; i++ )
{
_AccTp v = a[i] - b[i];
s += std::abs(v);
}
return s;
}
template<> static inline float normL1(const float* a, const float* b, int n)
{
if( n >= 8 )
return normL1_(a, b, n);
float s = 0;
for( int i = 0; i < n; i++ )
{
float v = a[i] - b[i];
s += std::abs(v);
}
return s;
}
template<> static inline int normL1(const uchar* a, const uchar* b, int n)
{
return normL1_(a, b, n);
}
template<typename _Tp, typename _AccTp> static inline
_AccTp normInf(const _Tp* a, const _Tp* b, int n)
{
_AccTp s = 0;
for( int i = 0; i < n; i++ )
{
_AccTp v0 = a[i] - b[i];
s = std::max(s, std::abs(v0));
}
return s;
}
template<typename _Tp, int m, int n> static inline
double norm(const Matx<_Tp, m, n>& M)
{
return std::sqrt(normL2Sqr<_Tp, double>(M.val, m*n));
}
template<typename _Tp, int m, int n> static inline
double norm(const Matx<_Tp, m, n>& M, int normType)
{
return normType == NORM_INF ? (double)normInf<_Tp, DataType<_Tp>::work_type>(M.val, m*n) :
normType == NORM_L1 ? (double)normL1<_Tp, DataType<_Tp>::work_type>(M.val, m*n) :
std::sqrt((double)normL2Sqr<_Tp, DataType<_Tp>::work_type>(M.val, m*n));
}
......@@ -1056,7 +1177,37 @@ template<typename _Tp, int cn> inline Vec<_Tp, cn> Vec<_Tp, cn>::mul(const Vec<_
for( int i = 0; i < cn; i++ ) w.val[i] = saturate_cast<_Tp>(this->val[i]*v.val[i]);
return w;
}
template<typename _Tp> Vec<_Tp, 2> conjugate(const Vec<_Tp, 2>& v)
{
return Vec<_Tp, 2>(v[0], -v[1]);
}
template<typename _Tp> Vec<_Tp, 4> conjugate(const Vec<_Tp, 4>& v)
{
return Vec<_Tp, 4>(v[0], -v[1], -v[2], -v[3]);
}
template<> inline Vec<float, 2> Vec<float, 2>::conj() const
{
return conjugate(*this);
}
template<> inline Vec<double, 2> Vec<double, 2>::conj() const
{
return conjugate(*this);
}
template<> inline Vec<float, 4> Vec<float, 4>::conj() const
{
return conjugate(*this);
}
template<> inline Vec<double, 4> Vec<double, 4>::conj() const
{
return conjugate(*this);
}
template<typename _Tp, int cn> inline Vec<_Tp, cn> Vec<_Tp, cn>::cross(const Vec<_Tp, cn>& v) const
{
CV_Error(CV_StsError, "for arbitrary-size vector there is no cross-product defined");
......@@ -1155,7 +1306,33 @@ Vec<_Tp, cn>& operator *= (Vec<_Tp, cn>& a, double alpha)
a[i] = saturate_cast<_Tp>(a[i]*alpha);
return a;
}
template<typename _Tp, int cn> static inline
Vec<_Tp, cn>& operator /= (Vec<_Tp, cn>& a, int alpha)
{
double ialpha = 1./alpha;
for( int i = 0; i < cn; i++ )
a[i] = saturate_cast<_Tp>(a[i]*ialpha);
return a;
}
template<typename _Tp, int cn> static inline
Vec<_Tp, cn>& operator /= (Vec<_Tp, cn>& a, float alpha)
{
float ialpha = 1.f/alpha;
for( int i = 0; i < cn; i++ )
a[i] = saturate_cast<_Tp>(a[i]*ialpha);
return a;
}
template<typename _Tp, int cn> static inline
Vec<_Tp, cn>& operator /= (Vec<_Tp, cn>& a, double alpha)
{
double ialpha = 1./alpha;
for( int i = 0; i < cn; i++ )
a[i] = saturate_cast<_Tp>(a[i]*ialpha);
return a;
}
template<typename _Tp, int cn> static inline Vec<_Tp, cn>
operator * (const Vec<_Tp, cn>& a, int alpha)
......@@ -1193,6 +1370,24 @@ operator * (double alpha, const Vec<_Tp, cn>& a)
return Vec<_Tp, cn>(a, alpha, Matx_ScaleOp());
}
template<typename _Tp, int cn> static inline Vec<_Tp, cn>
operator / (const Vec<_Tp, cn>& a, int alpha)
{
return Vec<_Tp, cn>(a, 1./alpha, Matx_ScaleOp());
}
template<typename _Tp, int cn> static inline Vec<_Tp, cn>
operator / (const Vec<_Tp, cn>& a, float alpha)
{
return Vec<_Tp, cn>(a, 1.f/alpha, Matx_ScaleOp());
}
template<typename _Tp, int cn> static inline Vec<_Tp, cn>
operator / (const Vec<_Tp, cn>& a, double alpha)
{
return Vec<_Tp, cn>(a, 1./alpha, Matx_ScaleOp());
}
template<typename _Tp, int cn> static inline Vec<_Tp, cn>
operator - (const Vec<_Tp, cn>& a)
{
......@@ -1200,6 +1395,20 @@ operator - (const Vec<_Tp, cn>& a)
for( int i = 0; i < cn; i++ ) t.val[i] = saturate_cast<_Tp>(-a.val[i]);
return t;
}
template<typename _Tp> inline Vec<_Tp, 4> operator * (const Vec<_Tp, 4>& v1, const Vec<_Tp, 4>& v2)
{
return Vec<_Tp, 4>(saturate_cast<_Tp>(v1[0]*v2[0] - v1[1]*v2[1] - v1[2]*v2[2] - v1[3]*v2[3]),
saturate_cast<_Tp>(v1[0]*v2[1] + v1[1]*v2[0] + v1[2]*v2[3] - v1[3]*v2[2]),
saturate_cast<_Tp>(v1[0]*v2[2] - v1[1]*v2[3] + v1[2]*v2[0] + v1[3]*v2[1]),
saturate_cast<_Tp>(v1[0]*v2[3] + v1[1]*v2[2] - v1[2]*v2[1] + v1[3]*v2[0]));
}
template<typename _Tp> inline Vec<_Tp, 4>& operator *= (Vec<_Tp, 4>& v1, const Vec<_Tp, 4>& v2)
{
v1 = v1 * v2;
return v1;
}
template<> inline Vec<float, 3> Vec<float, 3>::cross(const Vec<float, 3>& v) const
{
......@@ -1215,35 +1424,12 @@ template<> inline Vec<double, 3> Vec<double, 3>::cross(const Vec<double, 3>& v)
val[0]*v.val[1] - val[1]*v.val[0]);
}
template<typename T1, typename T2> static inline
Vec<T1, 2>& operator += (Vec<T1, 2>& a, const Vec<T2, 2>& b)
template<typename _Tp, int cn> inline Vec<_Tp, cn> normalize(const Vec<_Tp, cn>& v)
{
a[0] = saturate_cast<T1>(a[0] + b[0]);
a[1] = saturate_cast<T1>(a[1] + b[1]);
return a;
double nv = norm(v);
return v * (nv ? 1./nv : 0.);
}
template<typename T1, typename T2> static inline
Vec<T1, 3>& operator += (Vec<T1, 3>& a, const Vec<T2, 3>& b)
{
a[0] = saturate_cast<T1>(a[0] + b[0]);
a[1] = saturate_cast<T1>(a[1] + b[1]);
a[2] = saturate_cast<T1>(a[2] + b[2]);
return a;
}
template<typename T1, typename T2> static inline
Vec<T1, 4>& operator += (Vec<T1, 4>& a, const Vec<T2, 4>& b)
{
a[0] = saturate_cast<T1>(a[0] + b[0]);
a[1] = saturate_cast<T1>(a[1] + b[1]);
a[2] = saturate_cast<T1>(a[2] + b[2]);
a[3] = saturate_cast<T1>(a[3] + b[3]);
return a;
}
template<typename _Tp, typename _T2, int cn> static inline
VecCommaInitializer<_Tp, cn> operator << (const Vec<_Tp, cn>& vec, _T2 val)
{
......@@ -1898,8 +2084,8 @@ operator * (const Scalar_<_Tp>& a, const Scalar_<_Tp>& b)
{
return Scalar_<_Tp>(saturate_cast<_Tp>(a[0]*b[0] - a[1]*b[1] - a[2]*b[2] - a[3]*b[3]),
saturate_cast<_Tp>(a[0]*b[1] + a[1]*b[0] + a[2]*b[3] - a[3]*b[2]),
saturate_cast<_Tp>(a[0]*b[2] - a[1]*b[3] + a[2]*b[0] - a[3]*b[1]),
saturate_cast<_Tp>(a[0]*b[3] + a[1]*b[2] - a[2]*b[1] - a[3]*b[0]));
saturate_cast<_Tp>(a[0]*b[2] - a[1]*b[3] + a[2]*b[0] + a[3]*b[1]),
saturate_cast<_Tp>(a[0]*b[3] + a[1]*b[2] - a[2]*b[1] + a[3]*b[0]));
}
template<typename _Tp> static inline Scalar_<_Tp>&
......
modules/core/src/cmdparser.cpp
浏览文件 @ b74116e6
......@@ -282,7 +282,7 @@ template<typename _Tp>
cout << setw(col_p-2) << left << buf;
if (buf.length() > col_p-2)
if ((int)buf.length() > col_p-2)
{
cout << endl << " ";
cout << setw(col_p-2) << left << " ";
......@@ -293,7 +293,7 @@ template<typename _Tp>
while (true)
{
bool tr = (buf.length() > col_d-2) ? true: false;
bool tr = ((int)buf.length() > col_d-2) ? true: false;
int pos;
if (tr)
......@@ -301,7 +301,8 @@ template<typename _Tp>
pos = buf.find_first_of(' ');
while (true)
{
if (buf.find_first_of(' ', pos + 1 ) < col_d-2 && buf.find_first_of(' ', pos + 1 ) != std::string::npos)
if ((int)buf.find_first_of(' ', pos + 1 ) < col_d-2 &&
(int)buf.find_first_of(' ', pos + 1 ) != (int)std::string::npos)
pos = buf.find_first_of(' ', pos + 1);
else
break;
......
modules/core/src/matrix.cpp
浏览文件 @ b74116e6
......@@ -2161,43 +2161,6 @@ static void generateRandomCenter(const vector<Vec2f>& box, float* center, RNG& r
}
static inline float distance(const float* a, const float* b, int n)
{
int j = 0; float d = 0.f;
#if CV_SSE
if( USE_SSE2 )
{
float CV_DECL_ALIGNED(16) buf[4];
__m128 d0 = _mm_setzero_ps(), d1 = _mm_setzero_ps();
for( ; j <= n - 8; j += 8 )
{
__m128 t0 = _mm_sub_ps(_mm_loadu_ps(a + j), _mm_loadu_ps(b + j));
__m128 t1 = _mm_sub_ps(_mm_loadu_ps(a + j + 4), _mm_loadu_ps(b + j + 4));
d0 = _mm_add_ps(d0, _mm_mul_ps(t0, t0));
d1 = _mm_add_ps(d1, _mm_mul_ps(t1, t1));
}
_mm_store_ps(buf, _mm_add_ps(d0, d1));
d = buf[0] + buf[1] + buf[2] + buf[3];
}
else
#endif
{
for( ; j <= n - 4; j += 4 )
{
float t0 = a[j] - b[j], t1 = a[j+1] - b[j+1], t2 = a[j+2] - b[j+2], t3 = a[j+3] - b[j+3];
d += t0*t0 + t1*t1 + t2*t2 + t3*t3;
}
}
for( ; j < n; j++ )
{
float t = a[j] - b[j];
d += t*t;
}
return d;
}
/*
k-means center initialization using the following algorithm:
Arthur & Vassilvitskii (2007) k-means++: The Advantages of Careful Seeding
......@@ -2218,7 +2181,7 @@ static void generateCentersPP(const Mat& _data, Mat& _out_centers,
for( i = 0; i < N; i++ )
{
dist[i] = distance(data + step*i, data + step*centers[0], dims);
dist[i] = normL2Sqr_(data + step*i, data + step*centers[0], dims);
sum0 += dist[i];
}
......@@ -2236,7 +2199,7 @@ static void generateCentersPP(const Mat& _data, Mat& _out_centers,
int ci = i;
for( i = 0; i < N; i++ )
{
tdist2[i] = std::min(distance(data + step*i, data + step*ci, dims), dist[i]);
tdist2[i] = std::min(normL2Sqr_(data + step*i, data + step*ci, dims), dist[i]);
s += tdist2[i];
}
......@@ -2434,7 +2397,7 @@ double cv::kmeans( InputArray _data, int K,
for( k = 0; k < K; k++ )
{
const float* center = centers.ptr<float>(k);
double dist = distance(sample, center, dims);
double dist = normL2Sqr_(sample, center, dims);
if( min_dist > dist )
{
......
modules/core/src/stat.cpp
浏览文件 @ b74116e6
......@@ -810,15 +810,218 @@ void cv::minMaxLoc( InputArray _img, double* minVal, double* maxVal,
namespace cv
{
float normL2Sqr_(const float* a, const float* b, int n)
{
int j = 0; float d = 0.f;
#if CV_SSE
if( USE_SSE2 )
{
float CV_DECL_ALIGNED(16) buf[4];
__m128 d0 = _mm_setzero_ps(), d1 = _mm_setzero_ps();
for( ; j <= n - 8; j += 8 )
{
__m128 t0 = _mm_sub_ps(_mm_loadu_ps(a + j), _mm_loadu_ps(b + j));
__m128 t1 = _mm_sub_ps(_mm_loadu_ps(a + j + 4), _mm_loadu_ps(b + j + 4));
d0 = _mm_add_ps(d0, _mm_mul_ps(t0, t0));
d1 = _mm_add_ps(d1, _mm_mul_ps(t1, t1));
}
_mm_store_ps(buf, _mm_add_ps(d0, d1));
d = buf[0] + buf[1] + buf[2] + buf[3];
}
else
#endif
{
for( ; j <= n - 4; j += 4 )
{
float t0 = a[j] - b[j], t1 = a[j+1] - b[j+1], t2 = a[j+2] - b[j+2], t3 = a[j+3] - b[j+3];
d += t0*t0 + t1*t1 + t2*t2 + t3*t3;
}
}
for( ; j < n; j++ )
{
float t = a[j] - b[j];
d += t*t;
}
return d;
}
float normL1_(const float* a, const float* b, int n)
{
int j = 0; float d = 0.f;
#if CV_SSE
if( USE_SSE2 )
{
float CV_DECL_ALIGNED(16) buf[4];
static const float CV_DECL_ALIGNED(16) absbuf[4] = {0x7fffffff, 0x7fffffff, 0x7fffffff, 0x7fffffff};
__m128 d0 = _mm_setzero_ps(), d1 = _mm_setzero_ps();
__m128 absmask = _mm_load_ps(absbuf);
for( ; j <= n - 8; j += 8 )
{
__m128 t0 = _mm_sub_ps(_mm_loadu_ps(a + j), _mm_loadu_ps(b + j));
__m128 t1 = _mm_sub_ps(_mm_loadu_ps(a + j + 4), _mm_loadu_ps(b + j + 4));
d0 = _mm_add_ps(d0, _mm_and_ps(t0, absmask));
d1 = _mm_add_ps(d1, _mm_and_ps(t1, absmask));
}
_mm_store_ps(buf, _mm_add_ps(d0, d1));
d = buf[0] + buf[1] + buf[2] + buf[3];
}
else
#endif
{
for( ; j <= n - 4; j += 4 )
{
d += std::abs(a[j] - b[j]) + std::abs(a[j+1] - b[j+1]) +
std::abs(a[j+2] - b[j+2]) + std::abs(a[j+3] - b[j+3]);
}
}
for( ; j < n; j++ )
d += std::abs(a[j] - b[j]);
return d;
}
int normL1_(const uchar* a, const uchar* b, int n)
{
int j = 0, d = 0;
#if CV_SSE
if( USE_SSE2 )
{
__m128i d0 = _mm_setzero_si128();
for( ; j <= n - 16; j += 16 )
{
__m128i t0 = _mm_loadu_si128((const __m128i*)(a + j));
__m128i t1 = _mm_loadu_si128((const __m128i*)(b + j));
d0 = _mm_add_epi32(d0, _mm_sad_epu8(t0, t1));
}
for( ; j <= n - 4; j += 4 )
{
__m128i t0 = _mm_cvtsi32_si128(*(const int*)(a + j));
__m128i t1 = _mm_cvtsi32_si128(*(const int*)(b + j));
d0 = _mm_add_epi32(d0, _mm_sad_epu8(t0, t1));
}
d = _mm_cvtsi128_si32(_mm_add_epi32(d0, _mm_unpackhi_epi64(d0, d0)));
}
else
#endif
{
for( ; j <= n - 4; j += 4 )
{
d += std::abs(a[j] - b[j]) + std::abs(a[j+1] - b[j+1]) +
std::abs(a[j+2] - b[j+2]) + std::abs(a[j+3] - b[j+3]);
}
}
for( ; j < n; j++ )
d += std::abs(a[j] - b[j]);
return d;
}
static const uchar popCountTable[] =
{
0, 1, 1, 2, 1, 2, 2, 3, 1, 2, 2, 3, 2, 3, 3, 4, 1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5, 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5, 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6, 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5, 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6, 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6, 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7, 4, 5, 5, 6, 5, 6, 6, 7, 5, 6, 6, 7, 6, 7, 7, 8
};
static const uchar popCountTable2[] =
{
0, 1, 1, 1, 1, 2, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 3, 3,
1, 2, 2, 2, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 3, 3, 1, 2, 2, 2, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 3, 3,
1, 2, 2, 2, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 3, 3, 3, 4, 4, 4, 3, 4, 4, 4, 3, 4, 4, 4,
2, 3, 3, 3, 3, 4, 4, 4, 3, 4, 4, 4, 3, 4, 4, 4, 2, 3, 3, 3, 3, 4, 4, 4, 3, 4, 4, 4, 3, 4, 4, 4,
1, 2, 2, 2, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 3, 3, 3, 4, 4, 4, 3, 4, 4, 4, 3, 4, 4, 4,
2, 3, 3, 3, 3, 4, 4, 4, 3, 4, 4, 4, 3, 4, 4, 4, 2, 3, 3, 3, 3, 4, 4, 4, 3, 4, 4, 4, 3, 4, 4, 4,
1, 2, 2, 2, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 3, 3, 3, 4, 4, 4, 3, 4, 4, 4, 3, 4, 4, 4,
2, 3, 3, 3, 3, 4, 4, 4, 3, 4, 4, 4, 3, 4, 4, 4, 2, 3, 3, 3, 3, 4, 4, 4, 3, 4, 4, 4, 3, 4, 4, 4
};
static const uchar popCountTable4[] =
{
0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2
};
int normHamming(const uchar* a, const uchar* b, int n)
{
int i = 0, result = 0;
#if defined __GNUC__ && CV_NEON
if (CPU_HAS_NEON_FEATURE)
{
result = 0;
for( ; i <= n - 16; i += 16 )
{
uint8x16_t A_vec = vld1q_u8 (a + i);
uint8x16_t B_vec = vld1q_u8 (b + i);
//uint8x16_t veorq_u8 (uint8x16_t, uint8x16_t)
uint8x16_t AxorB = veorq_u8 (A_vec, B_vec);
uint8x16_t bitsSet = vcntq_u8 (AxorB);
//uint16x8_t vpadalq_u8 (uint16x8_t, uint8x16_t)
uint16x8_t bitSet8 = vpaddlq_u8 (bitsSet);
uint32x4_t bitSet4 = vpaddlq_u16 (bitSet8);
uint64x2_t bitSet2 = vpaddlq_u32 (bitSet4);
result += vgetq_lane_u64 (bitSet2,0);
result += vgetq_lane_u64 (bitSet2,1);
}
}
else
#endif
for( ; i <= n - 4; i += 4 )
result += popCountTable[a[i] ^ b[i]] + popCountTable[a[i+1] ^ b[i+1]] +
popCountTable[a[i+2] ^ b[i+2]] + popCountTable[a[i+3] ^ b[i+3]];
for( ; i < n; i++ )
result += popCountTable[a[i] ^ b[i]];
return result;
}
int normHamming(const uchar* a, const uchar* b, int n, int cellSize)
{
if( cellSize == 1 )
return normHamming(a, b, n);
const uchar* tab = 0;
if( cellSize == 2 )
tab = popCountTable2;
else if( cellSize == 4 )
tab = popCountTable4;
else
CV_Error( CV_StsBadSize, "bad cell size (not 1, 2 or 4) in normHamming" );
int i = 0, result = 0;
for( ; i <= n - 4; i += 4 )
result += tab[a[i] ^ b[i]] + tab[a[i+1] ^ b[i+1]] +
tab[a[i+2] ^ b[i+2]] + tab[a[i+3] ^ b[i+3]];
for( ; i < n; i++ )
result += tab[a[i] ^ b[i]];
return result;
}
template<typename T, typename ST> int
normInf_(const T* src, const uchar* mask, ST* _result, int len, int cn)
{
ST result = *_result;
if( !mask )
{
len *= cn;
for( int i = 0; i < len; i++ )
result = std::max(result, ST(std::abs(src[i])));
result = std::max(result, normInf<T, ST>(src, len*cn));
}
else
{
......@@ -826,7 +1029,7 @@ normInf_(const T* src, const uchar* mask, ST* _result, int len, int cn)
if( mask[i] )
{
for( int k = 0; k < cn; k++ )
result = std::max(result, ST(std::abs(src[k])));
result = std::max(result, ST(fast_abs(src[k])));
}
}
*_result = result;
......@@ -839,9 +1042,7 @@ normL1_(const T* src, const uchar* mask, ST* _result, int len, int cn)
ST result = *_result;
if( !mask )
{
len *= cn;
for( int i = 0; i < len; i++ )
result += std::abs(src[i]);
result += normL1<T, ST>(src, len*cn);
}
else
{
......@@ -849,7 +1050,7 @@ normL1_(const T* src, const uchar* mask, ST* _result, int len, int cn)
if( mask[i] )
{
for( int k = 0; k < cn; k++ )
result += std::abs(src[k]);
result += fast_abs(src[k]);
}
}
*_result = result;
......@@ -862,12 +1063,7 @@ normL2_(const T* src, const uchar* mask, ST* _result, int len, int cn)
ST result = *_result;
if( !mask )
{
len *= cn;
for( int i = 0; i < len; i++ )
{
T v = src[i];
result += (ST)v*v;
}
result += normL2Sqr<T, ST>(src, len*cn);
}
else
{
......@@ -891,9 +1087,7 @@ normDiffInf_(const T* src1, const T* src2, const uchar* mask, ST* _result, int l
ST result = *_result;
if( !mask )
{
len *= cn;
for( int i = 0; i < len; i++ )
result = std::max(result, (ST)std::abs(src1[i] - src2[i]));
result = std::max(result, normInf<T, ST>(src1, src2, len*cn));
}
else
{
......@@ -914,9 +1108,7 @@ normDiffL1_(const T* src1, const T* src2, const uchar* mask, ST* _result, int le
ST result = *_result;
if( !mask )
{
len *= cn;
for( int i = 0; i < len; i++ )
result += std::abs(src1[i] - src2[i]);
result += normL1<T, ST>(src1, src2, len*cn);
}
else
{
......@@ -937,12 +1129,7 @@ normDiffL2_(const T* src1, const T* src2, const uchar* mask, ST* _result, int le
ST result = *_result;
if( !mask )
{
len *= cn;
for( int i = 0; i < len; i++ )
{
ST v = src1[i] - src2[i];
result += v*v;
}
result += normL2Sqr<T, ST>(src1, src2, len*cn);
}
else
{
......
modules/features2d/include/opencv2/features2d/features2d.hpp
浏览文件 @ b74116e6
......@@ -2104,13 +2104,7 @@ struct CV_EXPORTS SL2
ResultType operator()( const T* a, const T* b, int size ) const
{
ResultType result = ResultType();
for( int i = 0; i < size; i++ )
{
ResultType diff = (ResultType)(a[i] - b[i]);
result += diff*diff;
}
return result;
return normL2Sqr<ValueType, ResultType>(a, b, size);
}
};
......@@ -2125,13 +2119,7 @@ struct CV_EXPORTS L2
ResultType operator()( const T* a, const T* b, int size ) const
{
ResultType result = ResultType();
for( int i = 0; i < size; i++ )
{
ResultType diff = (ResultType)(a[i] - b[i]);
result += diff*diff;
}
return (ResultType)sqrt((double)result);
return (ResultType)sqrt((double)normL2Sqr<ValueType, ResultType>(a, b, size));
}
};
......@@ -2146,13 +2134,7 @@ struct CV_EXPORTS L1
ResultType operator()( const T* a, const T* b, int size ) const
{
ResultType result = ResultType();
for( int i = 0; i < size; i++ )
{
ResultType diff = a[i] - b[i];
result += (ResultType)fabs( diff );
}
return result;
return normL1<ValueType, ResultType>(a, b, size);
}
};
......@@ -2160,40 +2142,20 @@ struct CV_EXPORTS L1
* Hamming distance functor - counts the bit differences between two strings - useful for the Brief descriptor
* bit count of A exclusive XOR'ed with B
*/
struct CV_EXPORTS HammingLUT
struct CV_EXPORTS Hamming
{
typedef unsigned char ValueType;
typedef int ResultType;
/** this will count the bits in a ^ b
*/
ResultType operator()( const unsigned char* a, const unsigned char* b, int size ) const;
/** \brief given a byte, count the bits using a compile time generated look up table
* \param b the byte to count bits. The look up table has an entry for all
* values of b, where that entry is the number of bits.
* \return the number of bits in byte b
*/
static unsigned char byteBitsLookUp(unsigned char b);
};
/// Hamming distance functor, this one will try to use gcc's __builtin_popcountl
/// but will fall back on HammingLUT if not available
/// bit count of A exclusive XOR'ed with B
struct CV_EXPORTS Hamming
{
typedef unsigned char ValueType;
//! important that this is signed as weird behavior happens
// in BruteForce if not
typedef int ResultType;
/** this will count the bits in a ^ b, using __builtin_popcountl try compiling with sse4
*/
ResultType operator()(const unsigned char* a, const unsigned char* b, int size) const;
ResultType operator()( const unsigned char* a, const unsigned char* b, int size ) const
{
return normHamming(a, b, size);
}
};
typedef Hamming HammingLUT;
/****************************************************************************************\
* DMatch *
......
modules/features2d/src/brief.cpp
浏览文件 @ b74116e6
......@@ -96,46 +96,6 @@ void pixelTests64(const Mat& sum, const std::vector<KeyPoint>& keypoints, Mat& d
namespace cv
{
HammingLUT::ResultType HammingLUT::operator()( const unsigned char* a, const unsigned char* b, int size ) const
{
ResultType result = 0;
for (int i = 0; i < size; i++)
{
result += byteBitsLookUp(a[i] ^ b[i]);
}
return result;
}
Hamming::ResultType Hamming::operator()(const unsigned char* a, const unsigned char* b, int size) const
{
ResultType result;
#if defined __GNUC__ && CV_NEON
if (CPU_HAS_NEON_FEATURE)
{
result = 0;
for (size_t i = 0; i < size; i += 16)
{
uint8x16_t A_vec = vld1q_u8 (a + i);
uint8x16_t B_vec = vld1q_u8 (b + i);
//uint8x16_t veorq_u8 (uint8x16_t, uint8x16_t)
uint8x16_t AxorB = veorq_u8 (A_vec, B_vec);
uint8x16_t bitsSet = vcntq_u8 (AxorB);
//uint16x8_t vpadalq_u8 (uint16x8_t, uint8x16_t)
uint16x8_t bitSet8 = vpaddlq_u8 (bitsSet);
uint32x4_t bitSet4 = vpaddlq_u16 (bitSet8);
uint64x2_t bitSet2 = vpaddlq_u32 (bitSet4);
result += vgetq_lane_u64 (bitSet2,0);
result += vgetq_lane_u64 (bitSet2,1);
}
}
else
#endif
result = HammingLUT()(a,b,size);
return result;
}
BriefDescriptorExtractor::BriefDescriptorExtractor(int bytes) :
bytes_(bytes), test_fn_(NULL)
{
......@@ -212,292 +172,4 @@ void BriefDescriptorExtractor::computeImpl(const Mat& image, std::vector<KeyPoin
test_fn_(sum, keypoints, descriptors);
}
/**
* \brief template meta programming struct that gives number of bits in a byte
* @TODO Maybe unintuitive and should just use python to generate the entries in the LUT
*/
template<unsigned char b>
struct ByteBits
{
/**
* number of bits in the byte given by the template constant
*/
enum
{
COUNT = ((b >> 0) & 1) +
((b >> 1) & 1) +
((b >> 2) & 1) +
((b >> 3) & 1) +
((b >> 4) & 1) +
((b >> 5) & 1) +
((b >> 6) & 1) +
((b >> 7) & 1)
};
};
unsigned char HammingLUT::byteBitsLookUp(unsigned char b)
{
static const unsigned char table[256] =
{
ByteBits<0>::COUNT,
ByteBits<1>::COUNT,
ByteBits<2>::COUNT,
ByteBits<3>::COUNT,
ByteBits<4>::COUNT,
ByteBits<5>::COUNT,
ByteBits<6>::COUNT,
ByteBits<7>::COUNT,
ByteBits<8>::COUNT,
ByteBits<9>::COUNT,
ByteBits<10>::COUNT,
ByteBits<11>::COUNT,
ByteBits<12>::COUNT,
ByteBits<13>::COUNT,
ByteBits<14>::COUNT,
ByteBits<15>::COUNT,
ByteBits<16>::COUNT,
ByteBits<17>::COUNT,
ByteBits<18>::COUNT,
ByteBits<19>::COUNT,
ByteBits<20>::COUNT,
ByteBits<21>::COUNT,
ByteBits<22>::COUNT,
ByteBits<23>::COUNT,
ByteBits<24>::COUNT,
ByteBits<25>::COUNT,
ByteBits<26>::COUNT,
ByteBits<27>::COUNT,
ByteBits<28>::COUNT,
ByteBits<29>::COUNT,
ByteBits<30>::COUNT,
ByteBits<31>::COUNT,
ByteBits<32>::COUNT,
ByteBits<33>::COUNT,
ByteBits<34>::COUNT,
ByteBits<35>::COUNT,
ByteBits<36>::COUNT,
ByteBits<37>::COUNT,
ByteBits<38>::COUNT,
ByteBits<39>::COUNT,
ByteBits<40>::COUNT,
ByteBits<41>::COUNT,
ByteBits<42>::COUNT,
ByteBits<43>::COUNT,
ByteBits<44>::COUNT,
ByteBits<45>::COUNT,
ByteBits<46>::COUNT,
ByteBits<47>::COUNT,
ByteBits<48>::COUNT,
ByteBits<49>::COUNT,
ByteBits<50>::COUNT,
ByteBits<51>::COUNT,
ByteBits<52>::COUNT,
ByteBits<53>::COUNT,
ByteBits<54>::COUNT,
ByteBits<55>::COUNT,
ByteBits<56>::COUNT,
ByteBits<57>::COUNT,
ByteBits<58>::COUNT,
ByteBits<59>::COUNT,
ByteBits<60>::COUNT,
ByteBits<61>::COUNT,
ByteBits<62>::COUNT,
ByteBits<63>::COUNT,
ByteBits<64>::COUNT,
ByteBits<65>::COUNT,
ByteBits<66>::COUNT,
ByteBits<67>::COUNT,
ByteBits<68>::COUNT,
ByteBits<69>::COUNT,
ByteBits<70>::COUNT,
ByteBits<71>::COUNT,
ByteBits<72>::COUNT,
ByteBits<73>::COUNT,
ByteBits<74>::COUNT,
ByteBits<75>::COUNT,
ByteBits<76>::COUNT,
ByteBits<77>::COUNT,
ByteBits<78>::COUNT,
ByteBits<79>::COUNT,
ByteBits<80>::COUNT,
ByteBits<81>::COUNT,
ByteBits<82>::COUNT,
ByteBits<83>::COUNT,
ByteBits<84>::COUNT,
ByteBits<85>::COUNT,
ByteBits<86>::COUNT,
ByteBits<87>::COUNT,
ByteBits<88>::COUNT,
ByteBits<89>::COUNT,
ByteBits<90>::COUNT,
ByteBits<91>::COUNT,
ByteBits<92>::COUNT,
ByteBits<93>::COUNT,
ByteBits<94>::COUNT,
ByteBits<95>::COUNT,
ByteBits<96>::COUNT,
ByteBits<97>::COUNT,
ByteBits<98>::COUNT,
ByteBits<99>::COUNT,
ByteBits<100>::COUNT,
ByteBits<101>::COUNT,
ByteBits<102>::COUNT,
ByteBits<103>::COUNT,
ByteBits<104>::COUNT,
ByteBits<105>::COUNT,
ByteBits<106>::COUNT,
ByteBits<107>::COUNT,
ByteBits<108>::COUNT,
ByteBits<109>::COUNT,
ByteBits<110>::COUNT,
ByteBits<111>::COUNT,
ByteBits<112>::COUNT,
ByteBits<113>::COUNT,
ByteBits<114>::COUNT,
ByteBits<115>::COUNT,
ByteBits<116>::COUNT,
ByteBits<117>::COUNT,
ByteBits<118>::COUNT,
ByteBits<119>::COUNT,
ByteBits<120>::COUNT,
ByteBits<121>::COUNT,
ByteBits<122>::COUNT,
ByteBits<123>::COUNT,
ByteBits<124>::COUNT,
ByteBits<125>::COUNT,
ByteBits<126>::COUNT,
ByteBits<127>::COUNT,
ByteBits<128>::COUNT,
ByteBits<129>::COUNT,
ByteBits<130>::COUNT,
ByteBits<131>::COUNT,
ByteBits<132>::COUNT,
ByteBits<133>::COUNT,
ByteBits<134>::COUNT,
ByteBits<135>::COUNT,
ByteBits<136>::COUNT,
ByteBits<137>::COUNT,
ByteBits<138>::COUNT,
ByteBits<139>::COUNT,
ByteBits<140>::COUNT,
ByteBits<141>::COUNT,
ByteBits<142>::COUNT,
ByteBits<143>::COUNT,
ByteBits<144>::COUNT,
ByteBits<145>::COUNT,
ByteBits<146>::COUNT,
ByteBits<147>::COUNT,
ByteBits<148>::COUNT,
ByteBits<149>::COUNT,
ByteBits<150>::COUNT,
ByteBits<151>::COUNT,
ByteBits<152>::COUNT,
ByteBits<153>::COUNT,
ByteBits<154>::COUNT,
ByteBits<155>::COUNT,
ByteBits<156>::COUNT,
ByteBits<157>::COUNT,
ByteBits<158>::COUNT,
ByteBits<159>::COUNT,
ByteBits<160>::COUNT,
ByteBits<161>::COUNT,
ByteBits<162>::COUNT,
ByteBits<163>::COUNT,
ByteBits<164>::COUNT,
ByteBits<165>::COUNT,
ByteBits<166>::COUNT,
ByteBits<167>::COUNT,
ByteBits<168>::COUNT,
ByteBits<169>::COUNT,
ByteBits<170>::COUNT,
ByteBits<171>::COUNT,
ByteBits<172>::COUNT,
ByteBits<173>::COUNT,
ByteBits<174>::COUNT,
ByteBits<175>::COUNT,
ByteBits<176>::COUNT,
ByteBits<177>::COUNT,
ByteBits<178>::COUNT,
ByteBits<179>::COUNT,
ByteBits<180>::COUNT,
ByteBits<181>::COUNT,
ByteBits<182>::COUNT,
ByteBits<183>::COUNT,
ByteBits<184>::COUNT,
ByteBits<185>::COUNT,
ByteBits<186>::COUNT,
ByteBits<187>::COUNT,
ByteBits<188>::COUNT,
ByteBits<189>::COUNT,
ByteBits<190>::COUNT,
ByteBits<191>::COUNT,
ByteBits<192>::COUNT,
ByteBits<193>::COUNT,
ByteBits<194>::COUNT,
ByteBits<195>::COUNT,
ByteBits<196>::COUNT,
ByteBits<197>::COUNT,
ByteBits<198>::COUNT,
ByteBits<199>::COUNT,
ByteBits<200>::COUNT,
ByteBits<201>::COUNT,
ByteBits<202>::COUNT,
ByteBits<203>::COUNT,
ByteBits<204>::COUNT,
ByteBits<205>::COUNT,
ByteBits<206>::COUNT,
ByteBits<207>::COUNT,
ByteBits<208>::COUNT,
ByteBits<209>::COUNT,
ByteBits<210>::COUNT,
ByteBits<211>::COUNT,
ByteBits<212>::COUNT,
ByteBits<213>::COUNT,
ByteBits<214>::COUNT,
ByteBits<215>::COUNT,
ByteBits<216>::COUNT,
ByteBits<217>::COUNT,
ByteBits<218>::COUNT,
ByteBits<219>::COUNT,
ByteBits<220>::COUNT,
ByteBits<221>::COUNT,
ByteBits<222>::COUNT,
ByteBits<223>::COUNT,
ByteBits<224>::COUNT,
ByteBits<225>::COUNT,
ByteBits<226>::COUNT,
ByteBits<227>::COUNT,
ByteBits<228>::COUNT,
ByteBits<229>::COUNT,
ByteBits<230>::COUNT,
ByteBits<231>::COUNT,
ByteBits<232>::COUNT,
ByteBits<233>::COUNT,
ByteBits<234>::COUNT,
ByteBits<235>::COUNT,
ByteBits<236>::COUNT,
ByteBits<237>::COUNT,
ByteBits<238>::COUNT,
ByteBits<239>::COUNT,
ByteBits<240>::COUNT,
ByteBits<241>::COUNT,
ByteBits<242>::COUNT,
ByteBits<243>::COUNT,
ByteBits<244>::COUNT,
ByteBits<245>::COUNT,
ByteBits<246>::COUNT,
ByteBits<247>::COUNT,
ByteBits<248>::COUNT,
ByteBits<249>::COUNT,
ByteBits<250>::COUNT,
ByteBits<251>::COUNT,
ByteBits<252>::COUNT,
ByteBits<253>::COUNT,
ByteBits<254>::COUNT,
ByteBits<255>::COUNT
};
return table[b];
}
} // namespace cv
modules/features2d/src/matchers.cpp
浏览文件 @ b74116e6
......@@ -342,7 +342,7 @@ Ptr<DescriptorMatcher> DescriptorMatcher::create( const string& descriptorMatche
}
else if( !descriptorMatcherType.compare( "BruteForce-HammingLUT") )
{
dm = new BruteForceMatcher<HammingLUT>();
dm = new BruteForceMatcher<Hamming>();
}
return dm;
......
modules/features2d/src/planardetect.cpp
浏览文件 @ b74116e6
......@@ -55,7 +55,7 @@ namespace cv
IEEE Transactions on Pattern Analysis and Machine Intelligence, 15 Jan. 2009.
2. Vincent Lepetit, Pascal Fua,
“Towards Recognizing Feature Points Using Classification Trees,”
"Towards Recognizing Feature Points Using Classification Trees,"
Technical Report IC/2004/74, EPFL, 2004.
*/
......
modules/flann/include/opencv2/flann/dist.h
浏览文件 @ b74116e6
......@@ -383,89 +383,23 @@ struct HammingLUT
*/
ResultType operator()(const unsigned char* a, const unsigned char* b, int size) const
{
static const uchar popCountTable[] =
{
0, 1, 1, 2, 1, 2, 2, 3, 1, 2, 2, 3, 2, 3, 3, 4, 1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5, 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5, 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6, 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5, 2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6, 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6, 3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7, 4, 5, 5, 6, 5, 6, 6, 7, 5, 6, 6, 7, 6, 7, 7, 8
};
ResultType result = 0;
for (int i = 0; i < size; i++) {
result += byteBitsLookUp(a[i] ^ b[i]);
result += popCountTable[a[i] ^ b[i]];
}
return result;
}
/** \brief given a byte, count the bits using a look up table
* \param b the byte to count bits. The look up table has an entry for all
* values of b, where that entry is the number of bits.
* \return the number of bits in byte b
*/
static unsigned char byteBitsLookUp(unsigned char b)
{
static const unsigned char table[256] = {
/* 0 */ 0, /* 1 */ 1, /* 2 */ 1, /* 3 */ 2,
/* 4 */ 1, /* 5 */ 2, /* 6 */ 2, /* 7 */ 3,
/* 8 */ 1, /* 9 */ 2, /* a */ 2, /* b */ 3,
/* c */ 2, /* d */ 3, /* e */ 3, /* f */ 4,
/* 10 */ 1, /* 11 */ 2, /* 12 */ 2, /* 13 */ 3,
/* 14 */ 2, /* 15 */ 3, /* 16 */ 3, /* 17 */ 4,
/* 18 */ 2, /* 19 */ 3, /* 1a */ 3, /* 1b */ 4,
/* 1c */ 3, /* 1d */ 4, /* 1e */ 4, /* 1f */ 5,
/* 20 */ 1, /* 21 */ 2, /* 22 */ 2, /* 23 */ 3,
/* 24 */ 2, /* 25 */ 3, /* 26 */ 3, /* 27 */ 4,
/* 28 */ 2, /* 29 */ 3, /* 2a */ 3, /* 2b */ 4,
/* 2c */ 3, /* 2d */ 4, /* 2e */ 4, /* 2f */ 5,
/* 30 */ 2, /* 31 */ 3, /* 32 */ 3, /* 33 */ 4,
/* 34 */ 3, /* 35 */ 4, /* 36 */ 4, /* 37 */ 5,
/* 38 */ 3, /* 39 */ 4, /* 3a */ 4, /* 3b */ 5,
/* 3c */ 4, /* 3d */ 5, /* 3e */ 5, /* 3f */ 6,
/* 40 */ 1, /* 41 */ 2, /* 42 */ 2, /* 43 */ 3,
/* 44 */ 2, /* 45 */ 3, /* 46 */ 3, /* 47 */ 4,
/* 48 */ 2, /* 49 */ 3, /* 4a */ 3, /* 4b */ 4,
/* 4c */ 3, /* 4d */ 4, /* 4e */ 4, /* 4f */ 5,
/* 50 */ 2, /* 51 */ 3, /* 52 */ 3, /* 53 */ 4,
/* 54 */ 3, /* 55 */ 4, /* 56 */ 4, /* 57 */ 5,
/* 58 */ 3, /* 59 */ 4, /* 5a */ 4, /* 5b */ 5,
/* 5c */ 4, /* 5d */ 5, /* 5e */ 5, /* 5f */ 6,
/* 60 */ 2, /* 61 */ 3, /* 62 */ 3, /* 63 */ 4,
/* 64 */ 3, /* 65 */ 4, /* 66 */ 4, /* 67 */ 5,
/* 68 */ 3, /* 69 */ 4, /* 6a */ 4, /* 6b */ 5,
/* 6c */ 4, /* 6d */ 5, /* 6e */ 5, /* 6f */ 6,
/* 70 */ 3, /* 71 */ 4, /* 72 */ 4, /* 73 */ 5,
/* 74 */ 4, /* 75 */ 5, /* 76 */ 5, /* 77 */ 6,
/* 78 */ 4, /* 79 */ 5, /* 7a */ 5, /* 7b */ 6,
/* 7c */ 5, /* 7d */ 6, /* 7e */ 6, /* 7f */ 7,
/* 80 */ 1, /* 81 */ 2, /* 82 */ 2, /* 83 */ 3,
/* 84 */ 2, /* 85 */ 3, /* 86 */ 3, /* 87 */ 4,
/* 88 */ 2, /* 89 */ 3, /* 8a */ 3, /* 8b */ 4,
/* 8c */ 3, /* 8d */ 4, /* 8e */ 4, /* 8f */ 5,
/* 90 */ 2, /* 91 */ 3, /* 92 */ 3, /* 93 */ 4,
/* 94 */ 3, /* 95 */ 4, /* 96 */ 4, /* 97 */ 5,
/* 98 */ 3, /* 99 */ 4, /* 9a */ 4, /* 9b */ 5,
/* 9c */ 4, /* 9d */ 5, /* 9e */ 5, /* 9f */ 6,
/* a0 */ 2, /* a1 */ 3, /* a2 */ 3, /* a3 */ 4,
/* a4 */ 3, /* a5 */ 4, /* a6 */ 4, /* a7 */ 5,
/* a8 */ 3, /* a9 */ 4, /* aa */ 4, /* ab */ 5,
/* ac */ 4, /* ad */ 5, /* ae */ 5, /* af */ 6,
/* b0 */ 3, /* b1 */ 4, /* b2 */ 4, /* b3 */ 5,
/* b4 */ 4, /* b5 */ 5, /* b6 */ 5, /* b7 */ 6,
/* b8 */ 4, /* b9 */ 5, /* ba */ 5, /* bb */ 6,
/* bc */ 5, /* bd */ 6, /* be */ 6, /* bf */ 7,
/* c0 */ 2, /* c1 */ 3, /* c2 */ 3, /* c3 */ 4,
/* c4 */ 3, /* c5 */ 4, /* c6 */ 4, /* c7 */ 5,
/* c8 */ 3, /* c9 */ 4, /* ca */ 4, /* cb */ 5,
/* cc */ 4, /* cd */ 5, /* ce */ 5, /* cf */ 6,
/* d0 */ 3, /* d1 */ 4, /* d2 */ 4, /* d3 */ 5,
/* d4 */ 4, /* d5 */ 5, /* d6 */ 5, /* d7 */ 6,
/* d8 */ 4, /* d9 */ 5, /* da */ 5, /* db */ 6,
/* dc */ 5, /* dd */ 6, /* de */ 6, /* df */ 7,
/* e0 */ 3, /* e1 */ 4, /* e2 */ 4, /* e3 */ 5,
/* e4 */ 4, /* e5 */ 5, /* e6 */ 5, /* e7 */ 6,
/* e8 */ 4, /* e9 */ 5, /* ea */ 5, /* eb */ 6,
/* ec */ 5, /* ed */ 6, /* ee */ 6, /* ef */ 7,
/* f0 */ 4, /* f1 */ 5, /* f2 */ 5, /* f3 */ 6,
/* f4 */ 5, /* f5 */ 6, /* f6 */ 6, /* f7 */ 7,
/* f8 */ 5, /* f9 */ 6, /* fa */ 6, /* fb */ 7,
/* fc */ 6, /* fd */ 7, /* fe */ 7, /* ff */ 8
};
return table[b];
}
};
/**
......
modules/gpu/include/opencv2/gpu/gpu.hpp
浏览文件 @ b74116e6
......@@ -1382,12 +1382,6 @@ namespace cv
explicit BruteForceMatcher_GPU() : BruteForceMatcher_GPU_base(L2Dist) {}
explicit BruteForceMatcher_GPU(L2<T> /*d*/) : BruteForceMatcher_GPU_base(L2Dist) {}
};
template <> class CV_EXPORTS BruteForceMatcher_GPU< HammingLUT > : public BruteForceMatcher_GPU_base
{
public:
explicit BruteForceMatcher_GPU() : BruteForceMatcher_GPU_base(HammingDist) {}
explicit BruteForceMatcher_GPU(HammingLUT /*d*/) : BruteForceMatcher_GPU_base(HammingDist) {}
};
template <> class CV_EXPORTS BruteForceMatcher_GPU< Hamming > : public BruteForceMatcher_GPU_base
{
public:
......
samples/cpp/brief_match_test.cpp
浏览文件 @ b74116e6
......@@ -103,13 +103,7 @@ int main(int argc, const char ** argv)
cout << "done computing descriptors... took " << t << " seconds" << endl;
//Do matching with 2 methods using features2d
cout << "matching with BruteForceMatcher<HammingLUT>" << endl;
BruteForceMatcher<HammingLUT> matcher;
vector<DMatch> matches_lut;
float lut_time = (float)match(kpts_1, kpts_2, matcher, desc_1, desc_2, matches_lut);
cout << "done BruteForceMatcher<HammingLUT> matching. took " << lut_time << " seconds" << endl;
//Do matching using features2d
cout << "matching with BruteForceMatcher<Hamming>" << endl;
BruteForceMatcher<Hamming> matcher_popcount;
vector<DMatch> matches_popcount;
......
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