TheTest & test_loadstore()
{
AlignedData<R> data;
AlignedData<R> out;
// check if addresses are aligned and unaligned respectively
EXPECT_EQ((size_t)0, (size_t)&data.a.d % 16);
EXPECT_NE((size_t)0, (size_t)&data.u.d % 16);
EXPECT_EQ((size_t)0, (size_t)&out.a.d % 16);
EXPECT_NE((size_t)0, (size_t)&out.u.d % 16);
// check some initialization methods
R r1 = data.a;
R r2 = v_load(data.u.d);
R r3 = v_load_aligned(data.a.d);
R r4(r2);
EXPECT_EQ(data.a[0], r1.get0());
EXPECT_EQ(data.u[0], r2.get0());
EXPECT_EQ(data.a[0], r3.get0());
EXPECT_EQ(data.u[0], r4.get0());
R r_low = v_load_low((LaneType*)data.u.d);
EXPECT_EQ(data.u[0], r_low.get0());
v_store(out.u.d, r_low);
for (int i = 0; i < R::nlanes/2; ++i)
{
EXPECT_EQ((LaneType)data.u[i], (LaneType)out.u[i]);
}
R r_low_align8byte = v_load_low((LaneType*)((char*)data.u.d + 8));
EXPECT_EQ(data.u[R::nlanes/2], r_low_align8byte.get0());
v_store(out.u.d, r_low_align8byte);
for (int i = 0; i < R::nlanes/2; ++i)
{
EXPECT_EQ((LaneType)data.u[i + R::nlanes/2], (LaneType)out.u[i]);
}
// check some store methods
out.u.clear();
out.a.clear();
v_store(out.u.d, r1);
v_store_aligned(out.a.d, r2);
EXPECT_EQ(data.a, out.a);
EXPECT_EQ(data.u, out.u);
// check more store methods
Data<R> d, res(0);
R r5 = d;
v_store_high(res.mid(), r5);
v_store_low(res.d, r5);
EXPECT_EQ(d, res);
// check halves load correctness
res.clear();
R r6 = v_load_halves(d.d, d.mid());
v_store(res.d, r6);
EXPECT_EQ(d, res);
// zero, all
Data<R> resZ = V_RegTrait128<LaneType>::zero();
Data<R> resV = V_RegTrait128<LaneType>::all(8);
for (int i = 0; i < R::nlanes; ++i)
{
EXPECT_EQ((LaneType)0, resZ[i]);
EXPECT_EQ((LaneType)8, resV[i]);
}
// reinterpret_as
v_uint8x16 vu8 = v_reinterpret_as_u8(r1); out.a.clear(); v_store((uchar*)out.a.d, vu8); EXPECT_EQ(data.a, out.a);
v_int8x16 vs8 = v_reinterpret_as_s8(r1); out.a.clear(); v_store((schar*)out.a.d, vs8); EXPECT_EQ(data.a, out.a);
v_uint16x8 vu16 = v_reinterpret_as_u16(r1); out.a.clear(); v_store((ushort*)out.a.d, vu16); EXPECT_EQ(data.a, out.a);
v_int16x8 vs16 = v_reinterpret_as_s16(r1); out.a.clear(); v_store((short*)out.a.d, vs16); EXPECT_EQ(data.a, out.a);
v_uint32x4 vu32 = v_reinterpret_as_u32(r1); out.a.clear(); v_store((unsigned*)out.a.d, vu32); EXPECT_EQ(data.a, out.a);
v_int32x4 vs32 = v_reinterpret_as_s32(r1); out.a.clear(); v_store((int*)out.a.d, vs32); EXPECT_EQ(data.a, out.a);
v_uint64x2 vu64 = v_reinterpret_as_u64(r1); out.a.clear(); v_store((uint64*)out.a.d, vu64); EXPECT_EQ(data.a, out.a);
v_int64x2 vs64 = v_reinterpret_as_s64(r1); out.a.clear(); v_store((int64*)out.a.d, vs64); EXPECT_EQ(data.a, out.a);
v_float32x4 vf32 = v_reinterpret_as_f32(r1); out.a.clear(); v_store((float*)out.a.d, vf32); EXPECT_EQ(data.a, out.a);
#if CV_SIMD128_64F
v_float64x2 vf64 = v_reinterpret_as_f64(r1); out.a.clear(); v_store((double*)out.a.d, vf64); EXPECT_EQ(data.a, out.a);
#endif
return *this;
}
inline bool v_check_any(const v_int8x16& a)
{ return v_check_all(v_reinterpret_as_u8(a)); }
void FAST_t(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bool nonmax_suppression)
{
Mat img = _img.getMat();
const int K = patternSize/2, N = patternSize + K + 1;
int i, j, k, pixel[25];
makeOffsets(pixel, (int)img.step, patternSize);
#if CV_SIMD128
const int quarterPatternSize = patternSize/4;
v_uint8x16 delta = v_setall_u8(0x80), t = v_setall_u8((char)threshold), K16 = v_setall_u8((char)K);
bool hasSimd = hasSIMD128();
#if CV_TRY_AVX2
Ptr<opt_AVX2::FAST_t_patternSize16_AVX2> fast_t_impl_avx2;
if(CV_CPU_HAS_SUPPORT_AVX2)
fast_t_impl_avx2 = opt_AVX2::FAST_t_patternSize16_AVX2::getImpl(img.cols, threshold, nonmax_suppression, pixel);
#endif
#endif
keypoints.clear();
threshold = std::min(std::max(threshold, 0), 255);
uchar threshold_tab[512];
for( i = -255; i <= 255; i++ )
threshold_tab[i+255] = (uchar)(i < -threshold ? 1 : i > threshold ? 2 : 0);
AutoBuffer<uchar> _buf((img.cols+16)*3*(sizeof(int) + sizeof(uchar)) + 128);
uchar* buf[3];
buf[0] = _buf.data(); buf[1] = buf[0] + img.cols; buf[2] = buf[1] + img.cols;
int* cpbuf[3];
cpbuf[0] = (int*)alignPtr(buf[2] + img.cols, sizeof(int)) + 1;
cpbuf[1] = cpbuf[0] + img.cols + 1;
cpbuf[2] = cpbuf[1] + img.cols + 1;
memset(buf[0], 0, img.cols*3);
for(i = 3; i < img.rows-2; i++)
{
const uchar* ptr = img.ptr<uchar>(i) + 3;
uchar* curr = buf[(i - 3)%3];
int* cornerpos = cpbuf[(i - 3)%3];
memset(curr, 0, img.cols);
int ncorners = 0;
if( i < img.rows - 3 )
{
j = 3;
#if CV_SIMD128
if( hasSimd )
{
if( patternSize == 16 )
{
#if CV_TRY_AVX2
if (fast_t_impl_avx2)
fast_t_impl_avx2->process(j, ptr, curr, cornerpos, ncorners);
#endif
//vz if (j <= (img.cols - 27)) //it doesn't make sense using vectors for less than 8 elements
{
for (; j < img.cols - 16 - 3; j += 16, ptr += 16)
{
v_uint8x16 v = v_load(ptr);
v_int8x16 v0 = v_reinterpret_as_s8((v + t) ^ delta);
v_int8x16 v1 = v_reinterpret_as_s8((v - t) ^ delta);
v_int8x16 x0 = v_reinterpret_as_s8(v_sub_wrap(v_load(ptr + pixel[0]), delta));
v_int8x16 x1 = v_reinterpret_as_s8(v_sub_wrap(v_load(ptr + pixel[quarterPatternSize]), delta));
v_int8x16 x2 = v_reinterpret_as_s8(v_sub_wrap(v_load(ptr + pixel[2*quarterPatternSize]), delta));
v_int8x16 x3 = v_reinterpret_as_s8(v_sub_wrap(v_load(ptr + pixel[3*quarterPatternSize]), delta));
v_int8x16 m0, m1;
m0 = (v0 < x0) & (v0 < x1);
m1 = (x0 < v1) & (x1 < v1);
m0 = m0 | ((v0 < x1) & (v0 < x2));
m1 = m1 | ((x1 < v1) & (x2 < v1));
m0 = m0 | ((v0 < x2) & (v0 < x3));
m1 = m1 | ((x2 < v1) & (x3 < v1));
m0 = m0 | ((v0 < x3) & (v0 < x0));
m1 = m1 | ((x3 < v1) & (x0 < v1));
m0 = m0 | m1;
int mask = v_signmask(m0);
if( mask == 0 )
continue;
if( (mask & 255) == 0 )
{
j -= 8;
ptr -= 8;
continue;
}
v_int8x16 c0 = v_setzero_s8();
v_int8x16 c1 = v_setzero_s8();
v_uint8x16 max0 = v_setzero_u8();
v_uint8x16 max1 = v_setzero_u8();
for( k = 0; k < N; k++ )
{
v_int8x16 x = v_reinterpret_as_s8(v_load((ptr + pixel[k])) ^ delta);
m0 = v0 < x;
m1 = x < v1;
c0 = v_sub_wrap(c0, m0) & m0;
c1 = v_sub_wrap(c1, m1) & m1;
max0 = v_max(max0, v_reinterpret_as_u8(c0));
max1 = v_max(max1, v_reinterpret_as_u8(c1));
}
max0 = v_max(max0, max1);
int m = v_signmask(K16 < max0);
for( k = 0; m > 0 && k < 16; k++, m >>= 1 )
{
if(m & 1)
{
cornerpos[ncorners++] = j+k;
if(nonmax_suppression)
curr[j+k] = (uchar)cornerScore<patternSize>(ptr+k, pixel, threshold);
}
}
}
}
}
}
#endif
for( ; j < img.cols - 3; j++, ptr++ )
{
int v = ptr[0];
const uchar* tab = &threshold_tab[0] - v + 255;
int d = tab[ptr[pixel[0]]] | tab[ptr[pixel[8]]];
if( d == 0 )
continue;
d &= tab[ptr[pixel[2]]] | tab[ptr[pixel[10]]];
d &= tab[ptr[pixel[4]]] | tab[ptr[pixel[12]]];
d &= tab[ptr[pixel[6]]] | tab[ptr[pixel[14]]];
if( d == 0 )
continue;
d &= tab[ptr[pixel[1]]] | tab[ptr[pixel[9]]];
d &= tab[ptr[pixel[3]]] | tab[ptr[pixel[11]]];
d &= tab[ptr[pixel[5]]] | tab[ptr[pixel[13]]];
d &= tab[ptr[pixel[7]]] | tab[ptr[pixel[15]]];
if( d & 1 )
{
int vt = v - threshold, count = 0;
for( k = 0; k < N; k++ )
{
int x = ptr[pixel[k]];
if(x < vt)
{
if( ++count > K )
{
cornerpos[ncorners++] = j;
if(nonmax_suppression)
curr[j] = (uchar)cornerScore<patternSize>(ptr, pixel, threshold);
break;
}
}
else
count = 0;
}
}
if( d & 2 )
{
int vt = v + threshold, count = 0;
for( k = 0; k < N; k++ )
{
int x = ptr[pixel[k]];
if(x > vt)
{
if( ++count > K )
{
cornerpos[ncorners++] = j;
if(nonmax_suppression)
curr[j] = (uchar)cornerScore<patternSize>(ptr, pixel, threshold);
break;
}
}
else
count = 0;
}
}
}
}
cornerpos[-1] = ncorners;
if( i == 3 )
continue;
const uchar* prev = buf[(i - 4 + 3)%3];
const uchar* pprev = buf[(i - 5 + 3)%3];
cornerpos = cpbuf[(i - 4 + 3)%3];
ncorners = cornerpos[-1];
for( k = 0; k < ncorners; k++ )
{
j = cornerpos[k];
int score = prev[j];
if( !nonmax_suppression ||
(score > prev[j+1] && score > prev[j-1] &&
score > pprev[j-1] && score > pprev[j] && score > pprev[j+1] &&
score > curr[j-1] && score > curr[j] && score > curr[j+1]) )
{
keypoints.push_back(KeyPoint((float)j, (float)(i-1), 7.f, -1, (float)score));
}
}
}
inline int v_signmask(const v_int8x16& a)
{ return v_signmask(v_reinterpret_as_u8(a)); }
