/* * 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 "common.hpp" #include "saturate_cast.hpp" #include "separable_filter.hpp" namespace CAROTENE_NS { bool isGaussianBlur3x3Supported(const Size2D &size, BORDER_MODE border) { return isSupportedConfiguration() && size.width >= 8 && (border == BORDER_MODE_CONSTANT || border == BORDER_MODE_REPLICATE); } void gaussianBlur3x3(const Size2D &size, const u8 * srcBase, ptrdiff_t srcStride, u8 * dstBase, ptrdiff_t dstStride, BORDER_MODE border, u8 borderValue) { internal::assertSupportedConfiguration(isGaussianBlur3x3Supported(size, border)); #ifdef CAROTENE_NEON const uint16x8_t v_border_x4 = vdupq_n_u16(borderValue << 2); const uint16x8_t v_zero = vdupq_n_u16(0); const uint8x8_t v_border = vdup_n_u8(borderValue); uint16x8_t tprev = v_zero, tcurr = v_zero, tnext = v_zero; uint16x8_t t0 = v_zero, t1 = v_zero, t2 = v_zero; ptrdiff_t width = (ptrdiff_t)size.width, height = (ptrdiff_t)size.height; for (ptrdiff_t y = 0; y < height; ++y) { const u8 * srow0 = y == 0 && border == BORDER_MODE_CONSTANT ? NULL : internal::getRowPtr(srcBase, srcStride, std::max(y - 1, 0)); const u8 * srow1 = internal::getRowPtr(srcBase, srcStride, y); const u8 * srow2 = y + 1 == height && border == BORDER_MODE_CONSTANT ? NULL : internal::getRowPtr(srcBase, srcStride, std::min(y + 1, height - 1)); u8 * drow = internal::getRowPtr(dstBase, dstStride, y); s16 prevx = 0, currx = 0, nextx = 0; ptrdiff_t x = 0; const ptrdiff_t bwidth = y + 2 < height ? width : (width - 8); // perform vertical convolution for ( ; x <= bwidth; x += 8) { internal::prefetch(srow0 + x); internal::prefetch(srow1 + x); internal::prefetch(srow2 + x); uint8x8_t x0 = !srow0 ? v_border : vld1_u8(srow0 + x); uint8x8_t x1 = vld1_u8(srow1 + x); uint8x8_t x2 = !srow2 ? v_border : vld1_u8(srow2 + x); // calculate values for plain CPU part below if needed if (x + 8 >= bwidth) { ptrdiff_t x3 = x == width ? width - 1 : x; ptrdiff_t x4 = border == BORDER_MODE_CONSTANT ? x3 - 1 : std::max(x3 - 1, 0); if (border == BORDER_MODE_CONSTANT && x4 < 0) prevx = borderValue; else prevx = (srow2 ? srow2[x4] : borderValue) + (srow1[x4] << 1) + (srow0 ? srow0[x4] : borderValue); currx = (srow2 ? srow2[x3] : borderValue) + (srow1[x3] << 1) + (srow0 ? srow0[x3] : borderValue); } // make shift if (x) { tprev = tcurr; tcurr = tnext; } // and calculate next value tnext = vaddq_u16(vaddl_u8(x0, x2), vshll_n_u8(x1, 1)); // make extrapolation for the first elements if (!x) { // make border if (border == BORDER_MODE_CONSTANT) tcurr = v_border_x4; else if (border == BORDER_MODE_REPLICATE) tcurr = vdupq_n_u16(vgetq_lane_u16(tnext, 0)); continue; } // combine 3 "shifted" vectors t0 = vextq_u16(tprev, tcurr, 7); t1 = tcurr; t2 = vextq_u16(tcurr, tnext, 1); // and add them t0 = vqaddq_u16(vshlq_n_u16(t1, 1), vqaddq_u16(t0, t2)); vst1_u8(drow + x - 8, vshrn_n_u16(t0, 4)); } x -= 8; if (x == width) --x; for ( ; x < width; ++x) { // make extrapolation for the last elements if (x + 1 >= width) { if (border == BORDER_MODE_CONSTANT) nextx = borderValue << 2; else if (border == BORDER_MODE_REPLICATE) nextx = srow2[x] + (srow1[x] << 1) + srow0[x]; } else nextx = (srow2 ? srow2[x + 1] : borderValue) + (srow1[x + 1] << 1) + (srow0 ? srow0[x + 1] : borderValue); f32 val = (prevx + (currx << 1) + nextx) >> 4; drow[x] = internal::saturate_cast((s32)val); // make shift prevx = currx; currx = nextx; } } #else (void)srcBase; (void)srcStride; (void)dstBase; (void)dstStride; (void)borderValue; #endif } bool isGaussianBlur3x3MarginSupported(const Size2D &size, BORDER_MODE border, Margin borderMargin) { return isSeparableFilter3x3Supported(size, border, 0, 0, borderMargin); } void gaussianBlur3x3Margin(const Size2D &size, const u8 * srcBase, ptrdiff_t srcStride, u8 * dstBase, ptrdiff_t dstStride, BORDER_MODE border, u8 borderValue, Margin borderMargin) { internal::assertSupportedConfiguration(isGaussianBlur3x3MarginSupported(size, border, borderMargin)); #ifdef CAROTENE_NEON internal::sepFilter3x3::process( size, srcBase, srcStride, dstBase, dstStride, 0, 0, border, borderValue, borderMargin); #else (void)srcBase; (void)srcStride; (void)dstBase; (void)dstStride; (void)borderValue; #endif } bool isGaussianBlur5x5Supported(const Size2D &size, s32 cn, BORDER_MODE border) { return isSupportedConfiguration() && cn > 0 && cn <= 4 && size.width >= 8 && size.height >= 2 && (border == BORDER_MODE_CONSTANT || border == BORDER_MODE_REFLECT101 || border == BORDER_MODE_REFLECT || border == BORDER_MODE_REPLICATE || border == BORDER_MODE_WRAP); } void gaussianBlur5x5(const Size2D &size, s32 cn, const u8 * srcBase, ptrdiff_t srcStride, u8 * dstBase, ptrdiff_t dstStride, BORDER_MODE borderType, u8 borderValue, Margin borderMargin) { internal::assertSupportedConfiguration(isGaussianBlur5x5Supported(size, cn, borderType)); #ifdef CAROTENE_NEON size_t colsn = size.width * cn; std::vector _tmp; u8 *tmp = 0; if (borderType == BORDER_MODE_CONSTANT) { _tmp.assign(colsn + 4*cn, borderValue); tmp = &_tmp[cn << 1]; } ptrdiff_t idx_l1 = internal::borderInterpolate(-1, size.width, borderType, borderMargin.left, borderMargin.right) * cn; ptrdiff_t idx_l2 = internal::borderInterpolate(-2, size.width, borderType, borderMargin.left, borderMargin.right) * cn; ptrdiff_t idx_r1 = internal::borderInterpolate(size.width + 0, size.width, borderType, borderMargin.left, borderMargin.right) * cn; ptrdiff_t idx_r2 = internal::borderInterpolate(size.width + 1, size.width, borderType, borderMargin.left, borderMargin.right) * cn; //1-line buffer std::vector _buf(cn * (size.width + 4) + 32 / sizeof(u16)); u16* lane = internal::alignPtr(&_buf[cn << 1], 32); if (borderType == BORDER_MODE_CONSTANT) for (s32 k = 0; k < cn; ++k) { lane[-cn+k] = borderValue; lane[-cn-cn+k] = borderValue; lane[colsn+k] = borderValue; lane[colsn+cn+k] = borderValue; } uint8x8_t vc6u8 = vmov_n_u8(6); uint16x8_t vc6u16 = vmovq_n_u16(6); uint16x8_t vc4u16 = vmovq_n_u16(4); for (size_t i = 0; i < size.height; ++i) { u8* dst = internal::getRowPtr(dstBase, dstStride, i); //vertical convolution ptrdiff_t idx_rm2 = internal::borderInterpolate(i - 2, size.height, borderType, borderMargin.top, borderMargin.bottom); ptrdiff_t idx_rm1 = internal::borderInterpolate(i - 1, size.height, borderType, borderMargin.top, borderMargin.bottom); ptrdiff_t idx_rp1 = internal::borderInterpolate(i + 1, size.height, borderType, borderMargin.top, borderMargin.bottom); ptrdiff_t idx_rp2 = internal::borderInterpolate(i + 2, size.height, borderType, borderMargin.top, borderMargin.bottom); const u8* ln0 = idx_rm2 >= -(ptrdiff_t)borderMargin.top ? internal::getRowPtr(srcBase, srcStride, idx_rm2) : tmp; const u8* ln1 = idx_rm1 >= -(ptrdiff_t)borderMargin.top ? internal::getRowPtr(srcBase, srcStride, idx_rm1) : tmp; const u8* ln2 = internal::getRowPtr(srcBase, srcStride, i); const u8* ln3 = idx_rp1 >= -(ptrdiff_t)borderMargin.top ? internal::getRowPtr(srcBase, srcStride, idx_rp1) : tmp; const u8* ln4 = idx_rp2 >= -(ptrdiff_t)borderMargin.top ? internal::getRowPtr(srcBase, srcStride, idx_rp2) : tmp; size_t x = 0; for (; x <= colsn - 8; x += 8) { internal::prefetch(internal::getRowPtr(ln2 + x, srcStride, x % 5 - 2)); uint8x8_t v0 = vld1_u8(ln0+x); uint8x8_t v1 = vld1_u8(ln1+x); uint8x8_t v2 = vld1_u8(ln2+x); uint8x8_t v3 = vld1_u8(ln3+x); uint8x8_t v4 = vld1_u8(ln4+x); uint16x8_t v = vaddl_u8(v0, v4); uint16x8_t v13 = vaddl_u8(v1, v3); v = vmlal_u8(v, v2, vc6u8); v = vmlaq_u16(v, v13, vc4u16); vst1q_u16(lane + x, v); } for (; x < colsn; ++x) lane[x] = ln0[x] + ln4[x] + u16(4) * (ln1[x] + ln3[x]) + u16(6) * ln2[x]; //left&right borders if (borderType != BORDER_MODE_CONSTANT) for (s32 k = 0; k < cn; ++k) { lane[-cn+k] = lane[idx_l1 + k]; lane[-cn-cn+k] = lane[idx_l2 + k]; lane[colsn+k] = lane[idx_r1 + k]; lane[colsn+cn+k] = lane[idx_r2 + k]; } //horizontal convolution x = 0; switch(cn) { case 1: for (; x <= colsn - 8; x += 8) { internal::prefetch(lane + x); uint16x8_t lane0 = vld1q_u16(lane + x - 2); uint16x8_t lane4 = vld1q_u16(lane + x + 2); uint16x8_t lane1 = vld1q_u16(lane + x - 1); uint16x8_t lane3 = vld1q_u16(lane + x + 1); uint16x8_t lane2 = vld1q_u16(lane + x + 0); uint16x8_t ln04 = vaddq_u16(lane0, lane4); uint16x8_t ln13 = vaddq_u16(lane1, lane3); uint16x8_t ln042 = vmlaq_u16(ln04, lane2, vc6u16); uint16x8_t lsw = vmlaq_u16(ln042, ln13, vc4u16); uint8x8_t ls = vrshrn_n_u16(lsw, 8); vst1_u8(dst + x, ls); } break; case 2: for (; x <= colsn - 8*2; x += 8*2) { internal::prefetch(lane + x); u16* lidx0 = lane + x - 2*2; u16* lidx1 = lane + x - 1*2; u16* lidx3 = lane + x + 1*2; u16* lidx4 = lane + x + 2*2; #if __GNUC_MINOR__ < 7 __asm__ __volatile__ ( "vld2.16 {d0, d2}, [%[in0]]! \n\t" "vld2.16 {d1, d3}, [%[in0]] \n\t" "vld2.16 {d8, d10}, [%[in4]]! \n\t" "vld2.16 {d9, d11}, [%[in4]] \n\t" "vadd.i16 q0, q4 \n\t" "vadd.i16 q1, q5 \n\t" "vld2.16 {d16, d18}, [%[in1]]! \n\t" "vld2.16 {d17, d19}, [%[in1]] \n\t" "vld2.16 {d8, d10}, [%[in3]]! \n\t" "vld2.16 {d9, d11}, [%[in3]] \n\t" "vadd.i16 q4, q8 \n\t" "vadd.i16 q5, q9 \n\t" "vld2.16 {d16, d18}, [%[in2]] \n\t" "vld2.16 {d17, d19}, [%[in22]] \n\t" "vmla.i16 q0, q4, %q[c4] \n\t" "vmla.i16 q1, q5, %q[c4] \n\t" "vmla.i16 q0, q8, %q[c6] \n\t" "vmla.i16 q1, q9, %q[c6] \n\t" "vrshrn.u16 d8, q0, #8 \n\t" "vrshrn.u16 d9, q1, #8 \n\t" "vst2.8 {d8-d9}, [%[out]] \n\t" : [in0] "=r" (lidx0), [in1] "=r" (lidx1), [in3] "=r" (lidx3), [in4] "=r" (lidx4) : [out] "r" (dst + x), "0" (lidx0), "1" (lidx1), "2" (lidx3), "3" (lidx4), [in2] "r" (lane + x), [in22] "r" (lane + x + 4*2), [c4] "w" (vc4u16), [c6] "w" (vc6u16) : "d0","d1","d2","d3","d4","d5","d6","d7","d8","d9","d10","d11","d12","d13","d14","d15","d16","d17","d18","d19","d20","d21","d22","d23" ); #else uint16x8x2_t vLane0 = vld2q_u16(lidx0); uint16x8x2_t vLane1 = vld2q_u16(lidx1); uint16x8x2_t vLane2 = vld2q_u16(lane + x); uint16x8x2_t vLane3 = vld2q_u16(lidx3); uint16x8x2_t vLane4 = vld2q_u16(lidx4); uint16x8_t vSum_0_4 = vaddq_u16(vLane0.val[0], vLane4.val[0]); uint16x8_t vSum_1_5 = vaddq_u16(vLane0.val[1], vLane4.val[1]); uint16x8_t vSum_4_8 = vaddq_u16(vLane1.val[0], vLane3.val[0]); uint16x8_t vSum_5_9 = vaddq_u16(vLane1.val[1], vLane3.val[1]); vSum_0_4 = vmlaq_u16(vSum_0_4, vSum_4_8, vc4u16); vSum_1_5 = vmlaq_u16(vSum_1_5, vSum_5_9, vc4u16); vSum_0_4 = vmlaq_u16(vSum_0_4, vLane2.val[0], vc6u16); vSum_1_5 = vmlaq_u16(vSum_1_5, vLane2.val[1], vc6u16); uint8x8x2_t vRes; vRes.val[0] = vrshrn_n_u16(vSum_0_4, 8); vRes.val[1] = vrshrn_n_u16(vSum_1_5, 8); vst2_u8(dst + x, vRes); #endif } break; case 3: for (; x <= colsn - 8*3; x += 8*3) { internal::prefetch(lane + x); u16* lidx0 = lane + x - 2*3; u16* lidx1 = lane + x - 1*3; u16* lidx3 = lane + x + 1*3; u16* lidx4 = lane + x + 2*3; #if defined(__GNUC__) && defined(__arm__) __asm__ __volatile__ ( "vld3.16 {d0, d2, d4}, [%[in0]]! \n\t" "vld3.16 {d1, d3, d5}, [%[in0]] \n\t" "vld3.16 {d8, d10, d12}, [%[in4]]! \n\t" "vld3.16 {d9, d11, d13}, [%[in4]] \n\t" "vadd.i16 q0, q4 \n\t" "vadd.i16 q1, q5 \n\t" "vadd.i16 q2, q6 \n\t" "vld3.16 {d16, d18, d20}, [%[in1]]! \n\t" "vld3.16 {d17, d19, d21}, [%[in1]] \n\t" "vld3.16 {d8, d10, d12}, [%[in3]]! \n\t" "vld3.16 {d9, d11, d13}, [%[in3]] \n\t" "vadd.i16 q4, q8 \n\t" "vadd.i16 q5, q9 \n\t" "vadd.i16 q6, q10 \n\t" "vld3.16 {d16, d18, d20}, [%[in2]] \n\t" "vld3.16 {d17, d19, d21}, [%[in22]] \n\t" "vmla.i16 q0, q4, %q[c4] \n\t" "vmla.i16 q1, q5, %q[c4] \n\t" "vmla.i16 q2, q6, %q[c4] \n\t" "vmla.i16 q0, q8, %q[c6] \n\t" "vmla.i16 q1, q9, %q[c6] \n\t" "vmla.i16 q2, q10, %q[c6] \n\t" "vrshrn.u16 d8, q0, #8 \n\t" "vrshrn.u16 d9, q1, #8 \n\t" "vrshrn.u16 d10, q2, #8 \n\t" "vst3.8 {d8-d10}, [%[out]] \n\t" : [in0] "=r" (lidx0), [in1] "=r" (lidx1), [in3] "=r" (lidx3), [in4] "=r" (lidx4) : [out] "r" (dst + x), "0" (lidx0), "1" (lidx1), "2" (lidx3), "3" (lidx4), [in2] "r" (lane + x), [in22] "r" (lane + x + 4*3), [c4] "w" (vc4u16), [c6] "w" (vc6u16) : "d0","d1","d2","d3","d4","d5","d6","d7","d8","d9","d10","d11","d12","d13","d14","d15","d16","d17","d18","d19","d20","d21","d22","d23" ); #else uint16x8x3_t vLane0 = vld3q_u16(lidx0); uint16x8x3_t vLane1 = vld3q_u16(lidx1); uint16x8x3_t vLane2 = vld3q_u16(lane + x); uint16x8x3_t vLane3 = vld3q_u16(lidx3); uint16x8x3_t vLane4 = vld3q_u16(lidx4); uint16x8_t vSum_0_4 = vaddq_u16(vLane0.val[0], vLane4.val[0]); uint16x8_t vSum_1_5 = vaddq_u16(vLane0.val[1], vLane4.val[1]); uint16x8_t vSum_2_6 = vaddq_u16(vLane0.val[2], vLane4.val[2]); uint16x8_t vSum_3_1 = vaddq_u16(vLane3.val[0], vLane1.val[0]); uint16x8_t vSum_4_2 = vaddq_u16(vLane3.val[1], vLane1.val[1]); uint16x8_t vSum_5_6 = vaddq_u16(vLane3.val[2], vLane1.val[2]); vSum_0_4 = vmlaq_u16(vSum_0_4, vSum_3_1, vc4u16); vSum_1_5 = vmlaq_u16(vSum_1_5, vSum_4_2, vc4u16); vSum_2_6 = vmlaq_u16(vSum_2_6, vSum_5_6, vc4u16); vSum_0_4 = vmlaq_u16(vSum_0_4, vLane2.val[0], vc6u16); vSum_1_5 = vmlaq_u16(vSum_1_5, vLane2.val[1], vc6u16); vSum_2_6 = vmlaq_u16(vSum_2_6, vLane2.val[2], vc6u16); uint8x8x3_t vRes; vRes.val[0] = vrshrn_n_u16(vSum_0_4, 8); vRes.val[1] = vrshrn_n_u16(vSum_1_5, 8); vRes.val[2] = vrshrn_n_u16(vSum_2_6, 8); vst3_u8(dst + x, vRes); #endif } break; case 4: for (; x <= colsn - 8*4; x += 8*4) { internal::prefetch(lane + x); internal::prefetch(lane + x + 16); u16* lidx0 = lane + x - 2*4; u16* lidx1 = lane + x - 1*4; u16* lidx3 = lane + x + 1*4; u16* lidx4 = lane + x + 2*4; #if defined(__GNUC__) && defined(__arm__) __asm__ __volatile__ ( "vld4.16 {d0, d2, d4, d6}, [%[in0]]! \n\t" "vld4.16 {d1, d3, d5, d7}, [%[in0]] \n\t" "vld4.16 {d8, d10, d12, d14}, [%[in4]]! \n\t" "vld4.16 {d9, d11, d13, d15}, [%[in4]] \n\t" "vadd.i16 q0, q4 \n\t" "vadd.i16 q1, q5 \n\t" "vadd.i16 q2, q6 \n\t" "vadd.i16 q3, q7 \n\t" "vld4.16 {d16, d18, d20, d22}, [%[in1]]! \n\t" "vld4.16 {d17, d19, d21, d23}, [%[in1]] \n\t" "vld4.16 {d8, d10, d12, d14}, [%[in3]]! \n\t" "vld4.16 {d9, d11, d13, d15}, [%[in3]] \n\t" "vadd.i16 q4, q8 \n\t" "vadd.i16 q5, q9 \n\t" "vadd.i16 q6, q10 \n\t" "vadd.i16 q7, q11 \n\t" "vld4.16 {d16, d18, d20, d22}, [%[in2],:256] \n\t" "vld4.16 {d17, d19, d21, d23}, [%[in22],:256] \n\t" "vmla.i16 q0, q4, %q[c4] \n\t" "vmla.i16 q1, q5, %q[c4] \n\t" "vmla.i16 q2, q6, %q[c4] \n\t" "vmla.i16 q3, q7, %q[c4] \n\t" "vmla.i16 q0, q8, %q[c6] \n\t" "vmla.i16 q1, q9, %q[c6] \n\t" "vmla.i16 q2, q10, %q[c6] \n\t" "vmla.i16 q3, q11, %q[c6] \n\t" "vrshrn.u16 d8, q0, #8 \n\t" "vrshrn.u16 d9, q1, #8 \n\t" "vrshrn.u16 d10, q2, #8 \n\t" "vrshrn.u16 d11, q3, #8 \n\t" "vst4.8 {d8-d11}, [%[out]] \n\t" : [in0] "=r" (lidx0), [in1] "=r" (lidx1), [in3] "=r" (lidx3), [in4] "=r" (lidx4) : [out] "r" (dst + x), "0" (lidx0), "1" (lidx1), "2" (lidx3), "3" (lidx4), [in2] "r" (lane + x), [in22] "r" (lane + x + 4*4), [c4] "w" (vc4u16), [c6] "w" (vc6u16) : "d0","d1","d2","d3","d4","d5","d6","d7","d8","d9","d10","d11","d12","d13","d14","d15","d16","d17","d18","d19","d20","d21","d22","d23" ); #else uint16x8x4_t vLane0 = vld4q_u16(lidx0); uint16x8x4_t vLane2 = vld4q_u16(lidx4); uint16x8x4_t vLane4 = vld4q_u16(lidx1); uint16x8x4_t vLane6 = vld4q_u16(lidx3); uint16x8x4_t vLane8 = vld4q_u16(lane + x); uint16x8_t vSum_0_4 = vaddq_u16(vLane0.val[0], vLane2.val[0]); uint16x8_t vSum_1_5 = vaddq_u16(vLane0.val[1], vLane2.val[1]); uint16x8_t vSum_2_6 = vaddq_u16(vLane0.val[2], vLane2.val[2]); uint16x8_t vSum_3_7 = vaddq_u16(vLane0.val[3], vLane2.val[3]); uint16x8_t vSum_4_8 = vaddq_u16(vLane4.val[0], vLane6.val[0]); uint16x8_t vSum_5_9 = vaddq_u16(vLane4.val[1], vLane6.val[1]); uint16x8_t vSum_6_10 = vaddq_u16(vLane4.val[2], vLane6.val[2]); uint16x8_t vSum_7_11 = vaddq_u16(vLane4.val[3], vLane6.val[3]); vSum_0_4 = vmlaq_u16(vSum_0_4, vSum_4_8, vc4u16); vSum_1_5 = vmlaq_u16(vSum_1_5, vSum_5_9, vc4u16); vSum_2_6 = vmlaq_u16(vSum_2_6, vSum_6_10, vc4u16); vSum_3_7 = vmlaq_u16(vSum_3_7, vSum_7_11, vc4u16); vSum_0_4 = vmlaq_u16(vSum_0_4, vLane8.val[0], vc6u16); vSum_1_5 = vmlaq_u16(vSum_1_5, vLane8.val[1], vc6u16); vSum_2_6 = vmlaq_u16(vSum_2_6, vLane8.val[2], vc6u16); vSum_3_7 = vmlaq_u16(vSum_3_7, vLane8.val[3], vc6u16); uint8x8x4_t vRes; vRes.val[0] = vrshrn_n_u16(vSum_0_4, 8); vRes.val[1] = vrshrn_n_u16(vSum_1_5, 8); vRes.val[2] = vrshrn_n_u16(vSum_2_6, 8); vRes.val[3] = vrshrn_n_u16(vSum_3_7, 8); vst4_u8(dst + x, vRes); #endif } break; } for (s32 h = 0; h < cn; ++h) { u16* ln = lane + h; u8* dt = dst + h; for (size_t k = x; k < colsn; k += cn) { dt[k] = (u8)((ln[k-2*cn] + ln[k+2*cn] + u16(4) * (ln[k-cn] + ln[k+cn]) + u16(6) * ln[k] + (1 << 7)) >> 8); } } } #else (void)srcBase; (void)srcStride; (void)dstBase; (void)dstStride; (void)borderValue; (void)borderMargin; #endif } void gaussianBlur5x5(const Size2D &size, s32 cn, const u16 * srcBase, ptrdiff_t srcStride, u16 * dstBase, ptrdiff_t dstStride, BORDER_MODE borderType, u16 borderValue, Margin borderMargin) { internal::assertSupportedConfiguration(isGaussianBlur5x5Supported(size, cn, borderType)); #ifdef CAROTENE_NEON size_t colsn = size.width * cn; std::vector _tmp; u16 *tmp = 0; if (borderType == BORDER_MODE_CONSTANT) { _tmp.assign(colsn + 4*cn, borderValue); tmp = &_tmp[cn << 1]; } ptrdiff_t idx_l1 = internal::borderInterpolate(-1, size.width, borderType, borderMargin.left, borderMargin.right) * cn; ptrdiff_t idx_l2 = internal::borderInterpolate(-2, size.width, borderType, borderMargin.left, borderMargin.right) * cn; ptrdiff_t idx_r1 = internal::borderInterpolate(size.width + 0, size.width, borderType, borderMargin.left, borderMargin.right) * cn; ptrdiff_t idx_r2 = internal::borderInterpolate(size.width + 1, size.width, borderType, borderMargin.left, borderMargin.right) * cn; //1-line buffer std::vector _buf(cn * (size.width + 4) + 32 / sizeof(u32)); u32* lane = internal::alignPtr(&_buf[cn << 1], 32); if (borderType == BORDER_MODE_CONSTANT) for (s32 k = 0; k < cn; ++k) { lane[-cn+k] = borderValue; lane[-cn-cn+k] = borderValue; lane[colsn+k] = borderValue; lane[colsn+cn+k] = borderValue; } uint16x4_t vc6u16 = vmov_n_u16(6); uint32x4_t vc6u32 = vmovq_n_u32(6); uint32x4_t vc4u32 = vmovq_n_u32(4); for (size_t i = 0; i < size.height; ++i) { u16* dst = internal::getRowPtr(dstBase, dstStride, i); //vertical convolution ptrdiff_t idx_rm2 = internal::borderInterpolate(i - 2, size.height, borderType, borderMargin.top, borderMargin.bottom); ptrdiff_t idx_rm1 = internal::borderInterpolate(i - 1, size.height, borderType, borderMargin.top, borderMargin.bottom); ptrdiff_t idx_rp1 = internal::borderInterpolate(i + 1, size.height, borderType, borderMargin.top, borderMargin.bottom); ptrdiff_t idx_rp2 = internal::borderInterpolate(i + 2, size.height, borderType, borderMargin.top, borderMargin.bottom); const u16* ln0 = idx_rm2 >= -(ptrdiff_t)borderMargin.top ? internal::getRowPtr(srcBase, srcStride, idx_rm2) : tmp; const u16* ln1 = idx_rm1 >= -(ptrdiff_t)borderMargin.top ? internal::getRowPtr(srcBase, srcStride, idx_rm1) : tmp; const u16* ln2 = internal::getRowPtr(srcBase, srcStride, i); const u16* ln3 = idx_rp1 >= -(ptrdiff_t)borderMargin.top ? internal::getRowPtr(srcBase, srcStride, idx_rp1) : tmp; const u16* ln4 = idx_rp2 >= -(ptrdiff_t)borderMargin.top ? internal::getRowPtr(srcBase, srcStride, idx_rp2) : tmp; size_t x = 0; for (; x <= colsn - 4; x += 4) { internal::prefetch(internal::getRowPtr(ln2 + x, srcStride, x % 5 - 2)); uint16x4_t v0 = vld1_u16(ln0+x); uint16x4_t v1 = vld1_u16(ln1+x); uint16x4_t v2 = vld1_u16(ln2+x); uint16x4_t v3 = vld1_u16(ln3+x); uint16x4_t v4 = vld1_u16(ln4+x); uint32x4_t v = vaddl_u16(v0, v4); uint32x4_t v13 = vaddl_u16(v1, v3); v = vmlal_u16(v, v2, vc6u16); v = vmlaq_u32(v, v13, vc4u32); vst1q_u32(lane + x, v); } for (; x < colsn; ++x) lane[x] = ln0[x] + ln4[x] + 4*(ln1[x] + ln3[x]) + 6*ln2[x]; //left&right borders if (borderType != BORDER_MODE_CONSTANT) for (s32 k = 0; k < cn; ++k) { lane[-cn+k] = lane[idx_l1 + k]; lane[-cn-cn+k] = lane[idx_l2 + k]; lane[colsn+k] = lane[idx_r1 + k]; lane[colsn+cn+k] = lane[idx_r2 + k]; } //horizontal convolution x = 0; for (; x <= colsn - 4; x += 4) { internal::prefetch(lane + x); uint32x4_t lane0 = vld1q_u32(lane + x - 2); uint32x4_t lane4 = vld1q_u32(lane + x + 2); uint32x4_t lane1 = vld1q_u32(lane + x - 1); uint32x4_t lane3 = vld1q_u32(lane + x + 1); uint32x4_t lane2 = vld1q_u32(lane + x + 0); uint32x4_t ln04 = vaddq_u32(lane0, lane4); uint32x4_t ln13 = vaddq_u32(lane1, lane3); uint32x4_t ln042 = vmlaq_u32(ln04, lane2, vc6u32); uint32x4_t lsw = vmlaq_u32(ln042, ln13, vc4u32); uint16x4_t ls = vrshrn_n_u32(lsw, 8); vst1_u16(dst + x, ls); } for (s32 h = 0; h < cn; ++h) { u32* ln = lane + h; u16* dt = dst + h; for (size_t k = x; k < colsn; k += cn) { dt[k] = (u16)((ln[k-2*cn] + ln[k+2*cn] + 4*(ln[k-cn] + ln[k+cn]) + 6*ln[k] + (1<<7))>>8); } } } #else (void)srcBase; (void)srcStride; (void)dstBase; (void)dstStride; (void)borderValue; (void)borderMargin; #endif } void gaussianBlur5x5(const Size2D &size, s32 cn, const s16 * srcBase, ptrdiff_t srcStride, s16 * dstBase, ptrdiff_t dstStride, BORDER_MODE borderType, s16 borderValue, Margin borderMargin) { internal::assertSupportedConfiguration(isGaussianBlur5x5Supported(size, cn, borderType)); #ifdef CAROTENE_NEON size_t colsn = size.width * cn; std::vector _tmp; s16 *tmp = 0; if (borderType == BORDER_MODE_CONSTANT) { _tmp.assign(colsn + 4*cn, borderValue); tmp = &_tmp[cn << 1]; } ptrdiff_t idx_l1 = internal::borderInterpolate(-1, size.width, borderType, borderMargin.left, borderMargin.right) * cn; ptrdiff_t idx_l2 = internal::borderInterpolate(-2, size.width, borderType, borderMargin.left, borderMargin.right) * cn; ptrdiff_t idx_r1 = internal::borderInterpolate(size.width + 0, size.width, borderType, borderMargin.left, borderMargin.right) * cn; ptrdiff_t idx_r2 = internal::borderInterpolate(size.width + 1, size.width, borderType, borderMargin.left, borderMargin.right) * cn; //1-line buffer std::vector _buf(cn * (size.width + 4) + 32 / sizeof(s32)); s32* lane = internal::alignPtr(&_buf[cn << 1], 32); if (borderType == BORDER_MODE_CONSTANT) for (s32 k = 0; k < cn; ++k) { lane[-cn+k] = borderValue; lane[-cn-cn+k] = borderValue; lane[colsn+k] = borderValue; lane[colsn+cn+k] = borderValue; } int16x4_t vc6s16 = vmov_n_s16(6); int32x4_t vc6s32 = vmovq_n_s32(6); int32x4_t vc4s32 = vmovq_n_s32(4); for (size_t i = 0; i < size.height; ++i) { s16* dst = internal::getRowPtr(dstBase, dstStride, i); //vertical convolution ptrdiff_t idx_rm2 = internal::borderInterpolate(i - 2, size.height, borderType, borderMargin.top, borderMargin.bottom); ptrdiff_t idx_rm1 = internal::borderInterpolate(i - 1, size.height, borderType, borderMargin.top, borderMargin.bottom); ptrdiff_t idx_rp1 = internal::borderInterpolate(i + 1, size.height, borderType, borderMargin.top, borderMargin.bottom); ptrdiff_t idx_rp2 = internal::borderInterpolate(i + 2, size.height, borderType, borderMargin.top, borderMargin.bottom); const s16* ln0 = idx_rm2 >= -(ptrdiff_t)borderMargin.top ? internal::getRowPtr(srcBase, srcStride, idx_rm2) : tmp; const s16* ln1 = idx_rm1 >= -(ptrdiff_t)borderMargin.top ? internal::getRowPtr(srcBase, srcStride, idx_rm1) : tmp; const s16* ln2 = internal::getRowPtr(srcBase, srcStride, i); const s16* ln3 = idx_rp1 >= -(ptrdiff_t)borderMargin.top ? internal::getRowPtr(srcBase, srcStride, idx_rp1) : tmp; const s16* ln4 = idx_rp2 >= -(ptrdiff_t)borderMargin.top ? internal::getRowPtr(srcBase, srcStride, idx_rp2) : tmp; size_t x = 0; for (; x <= colsn - 4; x += 4) { internal::prefetch(internal::getRowPtr(ln2 + x, srcStride, x % 5 - 2)); int16x4_t v0 = vld1_s16(ln0+x); int16x4_t v1 = vld1_s16(ln1+x); int16x4_t v2 = vld1_s16(ln2+x); int16x4_t v3 = vld1_s16(ln3+x); int16x4_t v4 = vld1_s16(ln4+x); int32x4_t v = vaddl_s16(v0, v4); int32x4_t v13 = vaddl_s16(v1, v3); v = vmlal_s16(v, v2, vc6s16); v = vmlaq_s32(v, v13, vc4s32); vst1q_s32(lane + x, v); } for (; x < colsn; ++x) lane[x] = ln0[x] + ln4[x] + 4*(ln1[x] + ln3[x]) + 6*ln2[x]; //left&right borders if (borderType != BORDER_MODE_CONSTANT) for (s32 k = 0; k < cn; ++k) { lane[-cn+k] = lane[idx_l1 + k]; lane[-cn-cn+k] = lane[idx_l2 + k]; lane[colsn+k] = lane[idx_r1 + k]; lane[colsn+cn+k] = lane[idx_r2 + k]; } //horizontal convolution x = 0; switch(cn) { case 1: case 2: case 3: for (; x <= colsn - 4; x += 4) { internal::prefetch(lane + x); int32x4_t lane0 = vld1q_s32(lane + x - 2); int32x4_t lane4 = vld1q_s32(lane + x + 2); int32x4_t lane1 = vld1q_s32(lane + x - 1); int32x4_t lane3 = vld1q_s32(lane + x + 1); int32x4_t lane2 = vld1q_s32(lane + x + 0); int32x4_t ln04 = vaddq_s32(lane0, lane4); int32x4_t ln13 = vaddq_s32(lane1, lane3); int32x4_t ln042 = vmlaq_s32(ln04, lane2, vc6s32); int32x4_t lsw = vmlaq_s32(ln042, ln13, vc4s32); int16x4_t ls = vrshrn_n_s32(lsw, 8); vst1_s16(dst + x, ls); } break; case 4: /* for (; x <= colsn - 4*4; x += 4*4) { internal::prefetch(lane + x); internal::prefetch(lane + x + 16); ptrdiff_t* lidx0 = lane + x - 2*4; ptrdiff_t* lidx1 = lane + x - 1*4; ptrdiff_t* lidx3 = lane + x + 1*4; ptrdiff_t* lidx4 = lane + x + 2*4; __asm__ __volatile__ ( "vld4.32 {d0, d2, d4, d6}, [%[in0]]! \n\t" "vld4.32 {d1, d3, d5, d7}, [%[in0]] \n\t" "vld4.32 {d8, d10, d12, d14}, [%[in4]]! \n\t" "vld4.32 {d9, d11, d13, d15}, [%[in4]] \n\t" "vadd.i32 q0, q4 \n\t" "vadd.i32 q1, q5 \n\t" "vadd.i32 q2, q6 \n\t" "vadd.i32 q3, q7 \n\t" "vld4.32 {d16, d18, d20, d22}, [%[in1]]! \n\t" "vld4.32 {d17, d19, d21, d23}, [%[in1]] \n\t" "vld4.32 {d8, d10, d12, d14}, [%[in3]]! \n\t" "vld4.32 {d9, d11, d13, d15}, [%[in3]] \n\t" "vadd.i32 q4, q8 \n\t" "vadd.i32 q5, q9 \n\t" "vadd.i32 q6, q10 \n\t" "vadd.i32 q7, q11 \n\t" "vld4.32 {d16, d18, d20, d22}, [%[in2],:256] \n\t" "vld4.32 {d17, d19, d21, d23}, [%[in22],:256] \n\t" "vmla.i32 q0, q4, %q[c4] \n\t" "vmla.i32 q1, q5, %q[c4] \n\t" "vmla.i32 q2, q6, %q[c4] \n\t" "vmla.i32 q3, q7, %q[c4] \n\t" "vmla.i32 q0, q8, %q[c6] \n\t" "vmla.i32 q1, q9, %q[c6] \n\t" "vmla.i32 q2, q10, %q[c6] \n\t" "vmla.i32 q3, q11, %q[c6] \n\t" "vrshrn.i32 d8, q0, #8 \n\t" "vrshrn.i32 d9, q1, #8 \n\t" "vrshrn.i32 d10, q2, #8 \n\t" "vrshrn.i32 d11, q3, #8 \n\t" "vst4.16 {d8-d11}, [%[out]] \n\t" : [in0] "=r" (lidx0), [in1] "=r" (lidx1), [in3] "=r" (lidx3), [in4] "=r" (lidx4) : [out] "r" (dst + x), "0" (lidx0), "1" (lidx1), "2" (lidx3), "3" (lidx4), [in2] "r" (lane + x), [in22] "r" (lane + x + 4*2), [c4] "w" (vc4s32), [c6] "w" (vc6s32) : "d0","d1","d2","d3","d4","d5","d6","d7","d8","d9","d10","d11","d12","d13","d14","d15","d16","d17","d18","d19","d20","d21","d22","d23" ); */ for (; x <= colsn - 4; x += 4) { internal::prefetch(lane + x); int32x4_t lane0 = vld1q_s32(lane + x - 2); int32x4_t lane4 = vld1q_s32(lane + x + 2); int32x4_t lane1 = vld1q_s32(lane + x - 1); int32x4_t lane3 = vld1q_s32(lane + x + 1); int32x4_t lane2 = vld1q_s32(lane + x + 0); int32x4_t ln04 = vaddq_s32(lane0, lane4); int32x4_t ln13 = vaddq_s32(lane1, lane3); int32x4_t ln042 = vmlaq_s32(ln04, lane2, vc6s32); int32x4_t lsw = vmlaq_s32(ln042, ln13, vc4s32); int16x4_t ls = vrshrn_n_s32(lsw, 8); vst1_s16(dst + x, ls); } break; } for (s32 h = 0; h < cn; ++h) { s32* ln = lane + h; s16* dt = dst + h; for (size_t k = x; k < colsn; k += cn) { dt[k] = (s16)((ln[k-2*cn] + ln[k+2*cn] + 4*(ln[k-cn] + ln[k+cn]) + 6*ln[k] + (1<<7))>>8); } } } #else (void)srcBase; (void)srcStride; (void)dstBase; (void)dstStride; (void)borderValue; (void)borderMargin; #endif } void gaussianBlur5x5(const Size2D &size, s32 cn, const s32 * srcBase, ptrdiff_t srcStride, s32 * dstBase, ptrdiff_t dstStride, BORDER_MODE borderType, s32 borderValue, Margin borderMargin) { internal::assertSupportedConfiguration(isGaussianBlur5x5Supported(size, cn, borderType)); #ifdef CAROTENE_NEON size_t colsn = size.width * cn; std::vector _tmp; s32 *tmp = 0; if (borderType == BORDER_MODE_CONSTANT) { _tmp.assign(colsn + 4*cn, borderValue); tmp = &_tmp[cn << 1]; } ptrdiff_t idx_l1 = internal::borderInterpolate(-1, size.width, borderType, borderMargin.left, borderMargin.right) * cn; ptrdiff_t idx_l2 = internal::borderInterpolate(-2, size.width, borderType, borderMargin.left, borderMargin.right) * cn; ptrdiff_t idx_r1 = internal::borderInterpolate(size.width + 0, size.width, borderType, borderMargin.left, borderMargin.right) * cn; ptrdiff_t idx_r2 = internal::borderInterpolate(size.width + 1, size.width, borderType, borderMargin.left, borderMargin.right) * cn; //1-line buffer std::vector _buf(cn * (size.width + 4) + 32 / sizeof(s32)); s32* lane = internal::alignPtr(&_buf[cn << 1], 32); if (borderType == BORDER_MODE_CONSTANT) for (s32 k = 0; k < cn; ++k) { lane[-cn+k] = borderValue; lane[-cn-cn+k] = borderValue; lane[colsn+k] = borderValue; lane[colsn+cn+k] = borderValue; } int32x4_t vc6s32 = vmovq_n_s32(6); int32x4_t vc4s32 = vmovq_n_s32(4); for (size_t i = 0; i < size.height; ++i) { s32* dst = internal::getRowPtr(dstBase, dstStride, i); //vertical convolution ptrdiff_t idx_rm2 = internal::borderInterpolate(i - 2, size.height, borderType, borderMargin.top, borderMargin.bottom); ptrdiff_t idx_rm1 = internal::borderInterpolate(i - 1, size.height, borderType, borderMargin.top, borderMargin.bottom); ptrdiff_t idx_rp1 = internal::borderInterpolate(i + 1, size.height, borderType, borderMargin.top, borderMargin.bottom); ptrdiff_t idx_rp2 = internal::borderInterpolate(i + 2, size.height, borderType, borderMargin.top, borderMargin.bottom); const s32* ln0 = idx_rm2 >= -(ptrdiff_t)borderMargin.top ? internal::getRowPtr(srcBase, srcStride, idx_rm2) : tmp; const s32* ln1 = idx_rm1 >= -(ptrdiff_t)borderMargin.top ? internal::getRowPtr(srcBase, srcStride, idx_rm1) : tmp; const s32* ln2 = internal::getRowPtr(srcBase, srcStride, i); const s32* ln3 = idx_rp1 >= -(ptrdiff_t)borderMargin.top ? internal::getRowPtr(srcBase, srcStride, idx_rp1) : tmp; const s32* ln4 = idx_rp2 >= -(ptrdiff_t)borderMargin.top ? internal::getRowPtr(srcBase, srcStride, idx_rp2) : tmp; size_t x = 0; for (; x <= colsn - 4; x += 4) { internal::prefetch(internal::getRowPtr(ln2 + x, srcStride, x % 5 - 2)); int32x4_t v0 = vld1q_s32(ln0+x); int32x4_t v1 = vld1q_s32(ln1+x); int32x4_t v2 = vld1q_s32(ln2+x); int32x4_t v3 = vld1q_s32(ln3+x); int32x4_t v4 = vld1q_s32(ln4+x); int32x4_t v = vaddq_s32(v0, v4); int32x4_t v13 = vaddq_s32(v1, v3); v = vmlaq_s32(v, v2, vc6s32); v = vmlaq_s32(v, v13, vc4s32); vst1q_s32(lane + x, v); } for (; x < colsn; ++x) lane[x] = ln0[x] + ln4[x] + 4*(ln1[x] + ln3[x]) + 6*ln2[x]; //left&right borders if (borderType != BORDER_MODE_CONSTANT) for (s32 k = 0; k < cn; ++k) { lane[-cn+k] = lane[idx_l1 + k]; lane[-cn-cn+k] = lane[idx_l2 + k]; lane[colsn+k] = lane[idx_r1 + k]; lane[colsn+cn+k] = lane[idx_r2 + k]; } //horizontal convolution x = 0; for (; x <= colsn - 4; x += 4) { internal::prefetch(lane + x); int32x4_t lane0 = vld1q_s32(lane + x - 2); int32x4_t lane4 = vld1q_s32(lane + x + 2); int32x4_t lane1 = vld1q_s32(lane + x - 1); int32x4_t lane3 = vld1q_s32(lane + x + 1); int32x4_t lane2 = vld1q_s32(lane + x + 0); int32x4_t ln04 = vaddq_s32(lane0, lane4); int32x4_t ln13 = vaddq_s32(lane1, lane3); int32x4_t ln042 = vmlaq_s32(ln04, lane2, vc6s32); int32x4_t lsw = vmlaq_s32(ln042, ln13, vc4s32); vst1q_s32(dst + x, lsw); } for (s32 h = 0; h < cn; ++h) { s32* ln = lane + h; s32* dt = dst + h; for (size_t k = x; k < colsn; k += cn) { dt[k] = ln[k-2*cn] + ln[k+2*cn] + 4*(ln[k-cn] + ln[k+cn]) + 6*ln[k]; } } } #else (void)srcBase; (void)srcStride; (void)dstBase; (void)dstStride; (void)borderValue; (void)borderMargin; #endif } } // namespace CAROTENE_NS