Open Source Computer Vision Library https://opencv.org/
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/*
* 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
* (3-clause BSD License)
*
* Copyright (C) 2012-2015, NVIDIA Corporation, 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:
*
* * 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 names of the copyright holders nor the names of the 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 copyright holders 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.
*/
#include <vector>
#include "common.hpp"
namespace CAROTENE_NS {
bool isScharr3x3Supported(const Size2D &size, BORDER_MODE border, s32 dx, s32 dy, Margin borderMargin)
{
return (dx == 0 && dy == 1 &&
isSeparableFilter3x3Supported(size, border, 3, 1, borderMargin)) ||
(dx == 1 && dy == 0 &&
isSeparableFilter3x3Supported(size, border, 1, 3, borderMargin));
}
void Scharr3x3(const Size2D &size,
const u8 * srcBase, ptrdiff_t srcStride,
s16 * dstBase, ptrdiff_t dstStride,
s32 dx, s32 dy,
BORDER_MODE border, u8 borderValue, Margin borderMargin)
{
internal::assertSupportedConfiguration(isScharr3x3Supported(size, border, dx, dy, borderMargin));
#ifdef CAROTENE_NEON
static s16 dw[] = {3, 10, 3};
if (dy == 1)
SeparableFilter3x3(size, srcBase, srcStride, dstBase, dstStride,
3, 1, dw, 0,
border, borderValue, borderMargin);
else
SeparableFilter3x3(size, srcBase, srcStride, dstBase, dstStride,
1, 3, 0, dw,
border, borderValue, borderMargin);
#else
(void)srcBase;
(void)srcStride;
(void)dstBase;
(void)dstStride;
(void)borderValue;
#endif
}
void ScharrDeriv(const Size2D &size, s32 cn,
const u8 * srcBase, ptrdiff_t srcStride,
s16 * dstBase, ptrdiff_t dstStride)
{
internal::assertSupportedConfiguration();
#ifdef CAROTENE_NEON
size_t colsn = size.width*cn;
size_t roiw8 = colsn > 7 ? colsn - 7 : 0;
ptrdiff_t delta = (ptrdiff_t)(((size.width + 2)*cn + 15) & -16);//align size
std::vector<s16> _tempBuf((delta << 1) + 64);
s16 *trow0 = internal::alignPtr(&_tempBuf[cn], 16), *trow1 = internal::alignPtr(trow0 + delta, 16);
int16x8_t vc3 = vmovq_n_s16(3);
int16x8_t vc10 = vmovq_n_s16(10);
uint8x8_t v8c10 = vmov_n_u8(10);
for(size_t y = 0; y < size.height; y++ )
{
const u8* srow0 = internal::getRowPtr(srcBase, srcStride, y > 0 ? y-1 : size.height > 1 ? 1 : 0);
const u8* srow1 = internal::getRowPtr(srcBase, srcStride, y);
const u8* srow2 = internal::getRowPtr(srcBase, srcStride, y < size.height-1 ? y+1 : size.height > 1 ? size.height-2 : 0);
s16* drow = internal::getRowPtr(dstBase, dstStride, y);
// do vertical convolution
size_t x = 0;
for( ; x < roiw8; x += 8 )
{
internal::prefetch(srow0 + x);
internal::prefetch(srow1 + x);
internal::prefetch(srow2 + x);
#if !defined(__aarch64__) && defined(__GNUC__) && __GNUC__ == 4 && __GNUC_MINOR__ < 7 && !defined(__clang__)
__asm__ (
"vld1.8 {d0}, [%[src0]] \n\t"
"vld1.8 {d2}, [%[src2]] \n\t"
"vld1.8 {d1}, [%[src1]] \n\t"
"vaddl.u8 q2, d2, d0 \n\t"
"vmull.u8 q3, d1, %[vc10] \n\t"
"vsubl.u8 q4, d2, d0 \n\t"
"vmla.s16 q3, q2, %q[vc3] \n\t"
"vst1.16 {d8-d9}, [%[out1],:128] \n\t"
"vst1.16 {d6-d7}, [%[out0],:128] \n\t"
:
: [out0] "r" (trow0 + x),
[out1] "r" (trow1 + x),
[src0] "r" (srow0 + x),
[src1] "r" (srow1 + x),
[src2] "r" (srow2 + x),
[vc10] "w" (v8c10), [vc3] "w" (vc3)
: "d0","d1","d2","d3","d4","d5","d6","d7","d8","d9","d10","d11","d12","d13","d14","d15"
);
#else
uint8x8_t s0 = vld1_u8(srow0 + x);
uint8x8_t s1 = vld1_u8(srow1 + x);
uint8x8_t s2 = vld1_u8(srow2 + x);
int16x8_t s1x10 = vreinterpretq_s16_u16(vmull_u8(s1, v8c10));
int16x8_t s02 = vreinterpretq_s16_u16(vaddl_u8(s2, s0));
int16x8_t t1 = vreinterpretq_s16_u16(vsubl_u8(s2, s0));
int16x8_t t0 = vmlaq_s16(s1x10, s02, vc3);
vst1q_s16(trow1 + x, t1);
vst1q_s16(trow0 + x, t0);
#endif
}
for( ; x < colsn; x++ )
{
trow0[x] = (s16)((srow0[x] + srow2[x])*3 + srow1[x]*10);
trow1[x] = (s16)(srow2[x] - srow0[x]);
}
// make border
size_t x0 = (size.width > 1 ? cn : 0), x1 = (size.width > 1 ? (size.width-2)*cn : 0);
for( s32 k = 0; k < cn; k++ )
{
trow0[-cn + k] = trow0[x0 + k]; trow0[colsn + k] = trow0[x1 + k];
trow1[-cn + k] = trow1[x0 + k]; trow1[colsn + k] = trow1[x1 + k];
}
// do horizontal convolution, interleave the results and store them to dst
x = 0;
for( ; x < roiw8; x += 8 )
{
#if !defined(__aarch64__) && defined(__GNUC__) && __GNUC__ == 4 && __GNUC_MINOR__ < 6 && !defined(__clang__)
__asm__ (
"vld1.16 {d4-d5}, [%[s2ptr]] \n\t"
"vld1.16 {d8-d9}, [%[s4ptr]] \n\t"
"vld1.16 {d6-d7}, [%[s3ptr],:128] \n\t"
"vld1.16 {d0-d1}, [%[s0ptr]] \n\t"
"vld1.16 {d2-d3}, [%[s1ptr]] \n\t"
"vadd.i16 q7, q2, q4 \n\t"
"vmul.s16 q6, q3, %q[vc10] \n\t"
"vsub.s16 q5, q1, q0 \n\t"
"vmla.s16 q6, q7, %q[vc3] \n\t"
"vst2.16 {d10-d13}, [%[out]] \n\t"
:
: [out] "r" (drow + x * 2),
[s0ptr] "r" (trow0 + x - cn),
[s1ptr] "r" (trow0 + x + cn),
[s2ptr] "r" (trow1 + x - cn),
[s3ptr] "r" (trow1 + x),
[s4ptr] "r" (trow1 + x + cn),
[vc10] "w" (vc10), [vc3] "w" (vc3)
: "d0","d1","d2","d3","d4","d5","d6","d7","d8","d9","d10","d11","d12","d13","d14","d15"
);
#else
int16x8_t s0 = vld1q_s16(trow0 + x - cn);
int16x8_t s1 = vld1q_s16(trow0 + x + cn);
int16x8_t s2 = vld1q_s16(trow1 + x - cn);
int16x8_t s3 = vld1q_s16(trow1 + x);
int16x8_t s4 = vld1q_s16(trow1 + x + cn);
int16x8_t s3x10 = vmulq_s16(s3, vc10);
int16x8_t s24 = vaddq_s16(s2, s4);
int16x8x2_t vr;
vr.val[0] = vsubq_s16(s1, s0);
vr.val[1] = vmlaq_s16(s3x10, s24, vc3);
vst2q_s16(drow + x*2, vr);
#endif
}
for( ; x < colsn; x++ )
{
drow[x*2] = (s16)(trow0[x+cn] - trow0[x-cn]);
drow[x*2+1] = (s16)((trow1[x+cn] + trow1[x-cn])*3 + trow1[x]*10);
}
}
#else
(void)size;
(void)cn;
(void)srcBase;
(void)srcStride;
(void)dstBase;
(void)dstStride;
#endif
}
} // namespace CAROTENE_NS