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use universal intrinsic implementation for calcSharrDeriv

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pull/7455/head
Tomoaki Teshima 8 years ago
parent 0f03f692a9
commit 1ef740fa2c
2 changed files with 38 additions and 74 deletions
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  1. 9
      modules/core/include/opencv2/core/hal/intrin_sse.hpp
  2. 103
      modules/video/src/lkpyramid.cpp

9
modules/core/include/opencv2/core/hal/intrin_sse.hpp
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@ -1425,6 +1425,15 @@ inline void v_load_deinterleave(const float* ptr, v_float32x4& a, v_float32x4& b
b.val = _mm_shuffle_ps(u0, u1, mask_hi); // b0 b1 ab b3
}
inline void v_store_interleave( short* ptr, const v_int16x8& a, const v_int16x8& b )
{
__m128i t0, t1;
t0 = _mm_unpacklo_epi16(a.val, b.val);
t1 = _mm_unpackhi_epi16(a.val, b.val);
_mm_storeu_si128((__m128i*)(ptr), t0);
_mm_storeu_si128((__m128i*)(ptr + 8), t1);
}
inline void v_store_interleave( uchar* ptr, const v_uint8x16& a, const v_uint8x16& b,
const v_uint8x16& c )
{

103
modules/video/src/lkpyramid.cpp
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@ -44,6 +44,7 @@
#include <stdio.h>
#include "lkpyramid.hpp"
#include "opencl_kernels_video.hpp"
#include "opencv2/core/hal/intrin.hpp"
#define CV_DESCALE(x,n) (((x) + (1 << ((n)-1))) >> (n))
@ -66,16 +67,9 @@ static void calcSharrDeriv(const cv::Mat& src, cv::Mat& dst)
AutoBuffer<deriv_type> _tempBuf(delta*2 + 64);
deriv_type *trow0 = alignPtr(_tempBuf + cn, 16), *trow1 = alignPtr(trow0 + delta, 16);
#if CV_SSE2
__m128i z = _mm_setzero_si128(), c3 = _mm_set1_epi16(3), c10 = _mm_set1_epi16(10);
#endif
#if CV_NEON
const uint16x8_t q8 = vdupq_n_u16(3);
const uint8x8_t d18 = vdup_n_u8(10);
const int16x8_t q8i = vdupq_n_s16(3);
const int16x8_t q9 = vdupq_n_s16(10);
#if CV_SIMD128
v_int16x8 c3 = v_setall_s16(3), c10 = v_setall_s16(10);
bool haveSIMD = checkHardwareSupport(CV_CPU_SSE2) || checkHardwareSupport(CV_CPU_NEON);
#endif
for( y = 0; y < rows; y++ )
@ -87,33 +81,21 @@ static void calcSharrDeriv(const cv::Mat& src, cv::Mat& dst)
// do vertical convolution
x = 0;
#if CV_SSE2
for( ; x <= colsn - 8; x += 8 )
#if CV_SIMD128
if(haveSIMD)
{
__m128i s0 = _mm_unpacklo_epi8(_mm_loadl_epi64((const __m128i*)(srow0 + x)), z);
__m128i s1 = _mm_unpacklo_epi8(_mm_loadl_epi64((const __m128i*)(srow1 + x)), z);
__m128i s2 = _mm_unpacklo_epi8(_mm_loadl_epi64((const __m128i*)(srow2 + x)), z);
__m128i t0 = _mm_add_epi16(_mm_mullo_epi16(_mm_add_epi16(s0, s2), c3), _mm_mullo_epi16(s1, c10));
__m128i t1 = _mm_sub_epi16(s2, s0);
_mm_store_si128((__m128i*)(trow0 + x), t0);
_mm_store_si128((__m128i*)(trow1 + x), t1);
}
#endif
for( ; x <= colsn - 8; x += 8 )
{
v_int16x8 s0 = v_reinterpret_as_s16(v_load_expand(srow0 + x));
v_int16x8 s1 = v_reinterpret_as_s16(v_load_expand(srow1 + x));
v_int16x8 s2 = v_reinterpret_as_s16(v_load_expand(srow2 + x));
#if CV_NEON
for( ; x <= colsn - 8; x += 8)
{
uint8x8_t d0 = vld1_u8((const uint8_t*)&srow0[x]);
uint8x8_t d1 = vld1_u8((const uint8_t*)&srow1[x]);
uint8x8_t d2 = vld1_u8((const uint8_t*)&srow2[x]);
uint16x8_t q4 = vaddl_u8(d0, d2);
uint16x8_t q11 = vsubl_u8(d2, d0);
uint16x8_t q5 = vmulq_u16(q4, q8);
uint16x8_t q6 = vmull_u8(d1, d18);
uint16x8_t q10 = vaddq_u16(q6, q5);
vst1q_u16((uint16_t*)&trow0[x], q10);
vst1q_u16((uint16_t*)&trow1[x], q11);
v_int16x8 t1 = s2 - s0;
v_int16x8 t0 = (s0 + s2) * c3 + s1 * c10;
v_store(trow0 + x, t0);
v_store(trow1 + x, t1);
}
}
#endif
@ -135,49 +117,22 @@ static void calcSharrDeriv(const cv::Mat& src, cv::Mat& dst)
// do horizontal convolution, interleave the results and store them to dst
x = 0;
#if CV_SSE2
for( ; x <= colsn - 8; x += 8 )
{
__m128i s0 = _mm_loadu_si128((const __m128i*)(trow0 + x - cn));
__m128i s1 = _mm_loadu_si128((const __m128i*)(trow0 + x + cn));
__m128i s2 = _mm_loadu_si128((const __m128i*)(trow1 + x - cn));
__m128i s3 = _mm_load_si128((const __m128i*)(trow1 + x));
__m128i s4 = _mm_loadu_si128((const __m128i*)(trow1 + x + cn));
__m128i t0 = _mm_sub_epi16(s1, s0);
__m128i t1 = _mm_add_epi16(_mm_mullo_epi16(_mm_add_epi16(s2, s4), c3), _mm_mullo_epi16(s3, c10));
__m128i t2 = _mm_unpacklo_epi16(t0, t1);
t0 = _mm_unpackhi_epi16(t0, t1);
// this can probably be replaced with aligned stores if we aligned dst properly.
_mm_storeu_si128((__m128i*)(drow + x*2), t2);
_mm_storeu_si128((__m128i*)(drow + x*2 + 8), t0);
}
#endif
#if CV_NEON
for( ; x <= colsn - 8; x += 8 )
#if CV_SIMD128
if(haveSIMD)
{
for( ; x <= colsn - 8; x += 8 )
{
v_int16x8 s0 = v_load(trow0 + x - cn);
v_int16x8 s1 = v_load(trow0 + x + cn);
v_int16x8 s2 = v_load(trow1 + x - cn);
v_int16x8 s3 = v_load(trow1 + x);
v_int16x8 s4 = v_load(trow1 + x + cn);
int16x8_t q0 = vld1q_s16((const int16_t*)&trow0[x+cn]);
int16x8_t q1 = vld1q_s16((const int16_t*)&trow0[x-cn]);
int16x8_t q2 = vld1q_s16((const int16_t*)&trow1[x+cn]);
int16x8_t q3 = vld1q_s16((const int16_t*)&trow1[x-cn]);
int16x8_t q5 = vsubq_s16(q0, q1);
int16x8_t q6 = vaddq_s16(q2, q3);
int16x8_t q4 = vld1q_s16((const int16_t*)&trow1[x]);
int16x8_t q7 = vmulq_s16(q6, q8i);
int16x8_t q10 = vmulq_s16(q4, q9);
int16x8_t q11 = vaddq_s16(q7, q10);
int16x4_t d22 = vget_low_s16(q11);
int16x4_t d23 = vget_high_s16(q11);
int16x4_t d11 = vget_high_s16(q5);
int16x4_t d10 = vget_low_s16(q5);
int16x4x2_t q5x2, q11x2;
q5x2.val[0] = d10; q5x2.val[1] = d22;
q11x2.val[0] = d11; q11x2.val[1] = d23;
vst2_s16((int16_t*)&drow[x*2], q5x2);
vst2_s16((int16_t*)&drow[(x*2)+8], q11x2);
v_int16x8 t0 = s1 - s0;
v_int16x8 t1 = ((s2 + s4) * c3) + (s3 * c10);
v_store_interleave((drow + x*2), t0, t1);
}
}
#endif
for( ; x < colsn; x++ )

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