| Line | Branch | Exec | Source |
|---|---|---|---|
| 1 | // SPDX-FileCopyrightText: 2023 - 2026 Arm Limited and/or its affiliates <open-source-office@arm.com> | ||
| 2 | // | ||
| 3 | // SPDX-License-Identifier: Apache-2.0 | ||
| 4 | |||
| 5 | #include <cassert> | ||
| 6 | #include <cstddef> | ||
| 7 | |||
| 8 | #include "kleidicv/config.h" | ||
| 9 | #include "kleidicv/ctypes.h" | ||
| 10 | #include "kleidicv/filters/gaussian_blur.h" | ||
| 11 | #include "kleidicv/filters/separable_filter_15x15_neon.h" | ||
| 12 | #include "kleidicv/filters/separable_filter_21x21_neon.h" | ||
| 13 | #include "kleidicv/filters/separable_filter_3x3_neon.h" | ||
| 14 | #include "kleidicv/filters/separable_filter_5x5_neon.h" | ||
| 15 | #include "kleidicv/filters/separable_filter_7x7_neon.h" | ||
| 16 | #include "kleidicv/filters/separable_filter_9x9_neon.h" | ||
| 17 | #include "kleidicv/filters/sigma.h" | ||
| 18 | #include "kleidicv/neon.h" | ||
| 19 | #include "kleidicv/workspace/border_types.h" | ||
| 20 | #include "kleidicv/workspace/separable.h" | ||
| 21 | |||
| 22 | namespace kleidicv::neon { | ||
| 23 | |||
| 24 | // Primary template for Gaussian Blur filters. | ||
| 25 | template <typename ScalarType, size_t KernelSize, bool IsBinomial> | ||
| 26 | class GaussianBlur; | ||
| 27 | |||
| 28 | // Template for 3x3 Gaussian Blur binomial filters. | ||
| 29 | // | ||
| 30 | // [ 1, 2, 1 ] [ 1 ] | ||
| 31 | // F = 1/16 * [ 2, 4, 2 ] = 1/16 * [ 2 ] * [ 1, 2, 1 ] | ||
| 32 | // [ 1, 2, 1 ] [ 1 ] | ||
| 33 | template <> | ||
| 34 | class GaussianBlur<uint8_t, 3, true> { | ||
| 35 | public: | ||
| 36 | using ScalarType = uint8_t; | ||
| 37 | using SourceType = ScalarType; | ||
| 38 | using SourceVectorType = typename VecTraits<SourceType>::VectorType; | ||
| 39 | using BufferType = double_element_width_t<ScalarType>; | ||
| 40 | using BufferVectorType = typename VecTraits<BufferType>::VectorType; | ||
| 41 | using DestinationType = ScalarType; | ||
| 42 | |||
| 43 | // Applies vertical filtering vector using SIMD operations. | ||
| 44 | // | ||
| 45 | // DST = [ SRC0, SRC1, SRC2 ] * [ 1, 2, 1 ]T | ||
| 46 | 114 | void vertical_vector_path(SourceVectorType src[3], BufferType *dst) const { | |
| 47 | // acc_0_2 = src[0] + src[2] | ||
| 48 | 114 | BufferVectorType acc_0_2_l = vaddl(vget_low(src[0]), vget_low(src[2])); | |
| 49 | 114 | BufferVectorType acc_0_2_h = vaddl(vget_high(src[0]), vget_high(src[2])); | |
| 50 | // acc_1 = src[1] + src[1] | ||
| 51 | 114 | BufferVectorType acc_1_l = vshll_n<1>(vget_low(src[1])); | |
| 52 | 114 | BufferVectorType acc_1_h = vshll_n<1>(vget_high(src[1])); | |
| 53 | // acc = acc_0_2 + acc_1 | ||
| 54 | 114 | BufferVectorType acc_l = vaddq(acc_0_2_l, acc_1_l); | |
| 55 | 114 | BufferVectorType acc_h = vaddq(acc_0_2_h, acc_1_h); | |
| 56 | |||
| 57 | 114 | VecTraits<BufferType>::store_consecutive(acc_l, acc_h, &dst[0]); | |
| 58 | 114 | } | |
| 59 | |||
| 60 | // Applies vertical filtering vector using scalar operations. | ||
| 61 | // | ||
| 62 | // DST = [ SRC0, SRC1, SRC2 ] * [ 1, 2, 1 ]T | ||
| 63 | 320 | void vertical_scalar_path(const SourceType src[3], BufferType *dst) const { | |
| 64 | 320 | dst[0] = src[0] + 2 * src[1] + src[2]; | |
| 65 | 320 | } | |
| 66 | |||
| 67 | // Applies horizontal filtering vector using SIMD operations. | ||
| 68 | // | ||
| 69 | // DST = 1/16 * [ SRC0, SRC1, SRC2 ] * [ 1, 2, 1 ]T | ||
| 70 | 176 | void horizontal_vector_path(BufferVectorType src[3], | |
| 71 | DestinationType *dst) const { | ||
| 72 | 176 | BufferVectorType acc_wide = vaddq(src[0], src[2]); | |
| 73 | 176 | acc_wide = vaddq(acc_wide, vshlq_n<1>(src[1])); | |
| 74 | 176 | auto acc_narrow = vrshrn_n<4>(acc_wide); | |
| 75 | 176 | vst1(&dst[0], acc_narrow); | |
| 76 | 176 | } | |
| 77 | |||
| 78 | // Applies horizontal filtering vector using scalar operations. | ||
| 79 | // | ||
| 80 | // DST = 1/16 * [ SRC0, SRC1, SRC2 ] * [ 1, 2, 1 ]T | ||
| 81 | 452 | void horizontal_scalar_path(const BufferType src[3], | |
| 82 | DestinationType *dst) const { | ||
| 83 | 452 | auto acc = src[0] + 2 * src[1] + src[2]; | |
| 84 | 452 | dst[0] = rounding_shift_right(acc, 4); | |
| 85 | 452 | } | |
| 86 | }; // end of class GaussianBlur<uint8_t, 3, true> | ||
| 87 | |||
| 88 | // Template for 5x5 Gaussian Blur binomial filters. | ||
| 89 | // | ||
| 90 | // [ 1, 4, 6, 4, 1 ] [ 1 ] | ||
| 91 | // [ 4, 16, 24, 16, 4 ] [ 4 ] | ||
| 92 | // F = 1/256 * [ 6, 24, 36, 24, 6 ] = 1/256 * [ 6 ] * [ 1, 4, 6, 4, 1 ] | ||
| 93 | // [ 4, 16, 24, 16, 4 ] [ 4 ] | ||
| 94 | // [ 1, 4, 6, 4, 1 ] [ 1 ] | ||
| 95 | template <> | ||
| 96 | class GaussianBlur<uint8_t, 5, true> { | ||
| 97 | public: | ||
| 98 | using SourceType = uint8_t; | ||
| 99 | using BufferType = uint16_t; | ||
| 100 | using DestinationType = uint8_t; | ||
| 101 | |||
| 102 | 61 | GaussianBlur() | |
| 103 | 61 | : const_6_u8_half_{vdup_n_u8(6)}, | |
| 104 | 61 | const_6_u16_{vdupq_n_u16(6)}, | |
| 105 | 61 | const_4_u16_{vdupq_n_u16(4)} {} | |
| 106 | |||
| 107 | // Applies vertical filtering vector using SIMD operations. | ||
| 108 | // | ||
| 109 | // DST = [ SRC0, SRC1, SRC2, SRC3, SRC4 ] * [ 1, 4, 6, 4, 1 ]T | ||
| 110 | 300 | void vertical_vector_path(uint8x16_t src[5], BufferType *dst) const { | |
| 111 | 300 | uint16x8_t acc_0_4_l = vaddl_u8(vget_low_u8(src[0]), vget_low_u8(src[4])); | |
| 112 | 300 | uint16x8_t acc_0_4_h = vaddl_u8(vget_high_u8(src[0]), vget_high_u8(src[4])); | |
| 113 | 300 | uint16x8_t acc_1_3_l = vaddl_u8(vget_low_u8(src[1]), vget_low_u8(src[3])); | |
| 114 | 300 | uint16x8_t acc_1_3_h = vaddl_u8(vget_high_u8(src[1]), vget_high_u8(src[3])); | |
| 115 | 600 | uint16x8_t acc_l = | |
| 116 | 300 | vmlal_u8(acc_0_4_l, vget_low_u8(src[2]), const_6_u8_half_); | |
| 117 | 600 | uint16x8_t acc_h = | |
| 118 | 300 | vmlal_u8(acc_0_4_h, vget_high_u8(src[2]), const_6_u8_half_); | |
| 119 | 300 | acc_l = vmlaq_u16(acc_l, acc_1_3_l, const_4_u16_); | |
| 120 | 300 | acc_h = vmlaq_u16(acc_h, acc_1_3_h, const_4_u16_); | |
| 121 | 300 | vst1q(&dst[0], acc_l); | |
| 122 | 300 | vst1q(&dst[8], acc_h); | |
| 123 | 300 | } | |
| 124 | |||
| 125 | // Applies vertical filtering vector using scalar operations. | ||
| 126 | // | ||
| 127 | // DST = [ SRC0, SRC1, SRC2, SRC3, SRC4 ] * [ 1, 4, 6, 4, 1 ]T | ||
| 128 | 3820 | void vertical_scalar_path(const SourceType src[5], BufferType *dst) const { | |
| 129 | 3820 | dst[0] = src[0] + src[4] + 4 * (src[1] + src[3]) + 6 * src[2]; | |
| 130 | 3820 | } | |
| 131 | |||
| 132 | // Applies horizontal filtering vector using SIMD operations. | ||
| 133 | // | ||
| 134 | // DST = 1/256 * [ SRC0, SRC1, SRC2, SRC3, SRC4 ] * [ 1, 4, 6, 4, 1 ]T | ||
| 135 | 604 | void horizontal_vector_path(uint16x8_t src[5], DestinationType *dst) const { | |
| 136 | 604 | uint16x8_t acc_0_4 = vaddq_u16(src[0], src[4]); | |
| 137 | 604 | uint16x8_t acc_1_3 = vaddq_u16(src[1], src[3]); | |
| 138 | 604 | uint16x8_t acc_u16 = vmlaq_u16(acc_0_4, src[2], const_6_u16_); | |
| 139 | 604 | acc_u16 = vmlaq_u16(acc_u16, acc_1_3, const_4_u16_); | |
| 140 | 604 | uint8x8_t acc_u8 = vrshrn_n_u16(acc_u16, 8); | |
| 141 | 604 | vst1(&dst[0], acc_u8); | |
| 142 | 604 | } | |
| 143 | |||
| 144 | // Applies horizontal filtering vector using scalar operations. | ||
| 145 | // | ||
| 146 | // DST = 1/256 * [ SRC0, SRC1, SRC2, SRC3, SRC4 ] * [ 1, 4, 6, 4, 1 ]T | ||
| 147 | 3068 | void horizontal_scalar_path(const BufferType src[5], | |
| 148 | DestinationType *dst) const { | ||
| 149 | 3068 | auto acc = src[0] + src[4] + 4 * (src[1] + src[3]) + 6 * src[2]; | |
| 150 | 3068 | dst[0] = rounding_shift_right(acc, 8); | |
| 151 | 3068 | } | |
| 152 | |||
| 153 | private: | ||
| 154 | uint8x8_t const_6_u8_half_; | ||
| 155 | uint16x8_t const_6_u16_; | ||
| 156 | uint16x8_t const_4_u16_; | ||
| 157 | }; // end of class GaussianBlur<uint8_t, 5, true> | ||
| 158 | |||
| 159 | // Template for 7x7 Gaussian Blur binomial filters. | ||
| 160 | // | ||
| 161 | // [ 4, 14, 28, 36, 28, 14, 4 ] | ||
| 162 | // [ 14, 49, 98, 126, 98, 49, 14 ] | ||
| 163 | // [ 28, 98, 196, 252, 196, 98, 28 ] | ||
| 164 | // F = 1/4096 * [ 36, 126, 252, 324, 252, 126, 36 ] = | ||
| 165 | // [ 28, 98, 196, 252, 196, 98, 28 ] | ||
| 166 | // [ 14, 49, 98, 126, 98, 49, 14 ] | ||
| 167 | // [ 4, 14, 28, 36, 28, 14, 4 ] | ||
| 168 | // | ||
| 169 | // [ 2 ] | ||
| 170 | // [ 7 ] | ||
| 171 | // [ 14 ] | ||
| 172 | // = 1/4096 * [ 18 ] * [ 2, 7, 14, 18, 14, 7, 2 ] | ||
| 173 | // [ 14 ] | ||
| 174 | // [ 7 ] | ||
| 175 | // [ 2 ] | ||
| 176 | template <> | ||
| 177 | class GaussianBlur<uint8_t, 7, true> { | ||
| 178 | public: | ||
| 179 | using SourceType = uint8_t; | ||
| 180 | using BufferType = uint16_t; | ||
| 181 | using DestinationType = uint8_t; | ||
| 182 | |||
| 183 | 33 | GaussianBlur() | |
| 184 | 33 | : const_7_u16_{vdupq_n_u16(7)}, | |
| 185 | 33 | const_7_u32_{vdupq_n_u32(7)}, | |
| 186 | 33 | const_9_u16_{vdupq_n_u16(9)} {} | |
| 187 | |||
| 188 | // Applies vertical filtering vector using SIMD operations. | ||
| 189 | // | ||
| 190 | // DST = [ SRC0, SRC1, SRC2, SRC3, SRC4, SRC5, SRC6 ] * | ||
| 191 | // * [ 2, 7, 14, 18, 14, 7, 2 ]T | ||
| 192 | 240 | void vertical_vector_path(uint8x16_t src[7], BufferType *dst) const { | |
| 193 | 240 | uint16x8_t acc_0_6_l = vaddl_u8(vget_low_u8(src[0]), vget_low_u8(src[6])); | |
| 194 | 240 | uint16x8_t acc_0_6_h = vaddl_u8(vget_high_u8(src[0]), vget_high_u8(src[6])); | |
| 195 | |||
| 196 | 240 | uint16x8_t acc_1_5_l = vaddl_u8(vget_low_u8(src[1]), vget_low_u8(src[5])); | |
| 197 | 240 | uint16x8_t acc_1_5_h = vaddl_u8(vget_high_u8(src[1]), vget_high_u8(src[5])); | |
| 198 | |||
| 199 | 240 | uint16x8_t acc_2_4_l = vaddl_u8(vget_low_u8(src[2]), vget_low_u8(src[4])); | |
| 200 | 240 | uint16x8_t acc_2_4_h = vaddl_u8(vget_high_u8(src[2]), vget_high_u8(src[4])); | |
| 201 | |||
| 202 | 240 | uint16x8_t acc_3_l = vmovl_u8(vget_low_u8(src[3])); | |
| 203 | 240 | uint16x8_t acc_3_h = vmovl_u8(vget_high_u8(src[3])); | |
| 204 | |||
| 205 | 240 | uint16x8_t acc_0_2_4_6_l = vmlaq_u16(acc_0_6_l, acc_2_4_l, const_7_u16_); | |
| 206 | 240 | uint16x8_t acc_0_2_4_6_h = vmlaq_u16(acc_0_6_h, acc_2_4_h, const_7_u16_); | |
| 207 | |||
| 208 | 480 | uint16x8_t acc_0_2_3_4_6_l = | |
| 209 | 240 | vmlaq_u16(acc_0_2_4_6_l, acc_3_l, const_9_u16_); | |
| 210 | 480 | uint16x8_t acc_0_2_3_4_6_h = | |
| 211 | 240 | vmlaq_u16(acc_0_2_4_6_h, acc_3_h, const_9_u16_); | |
| 212 | |||
| 213 | 240 | acc_0_2_3_4_6_l = vshlq_n_u16(acc_0_2_3_4_6_l, 1); | |
| 214 | 240 | acc_0_2_3_4_6_h = vshlq_n_u16(acc_0_2_3_4_6_h, 1); | |
| 215 | |||
| 216 | 480 | uint16x8_t acc_0_1_2_3_4_5_6_l = | |
| 217 | 240 | vmlaq_u16(acc_0_2_3_4_6_l, acc_1_5_l, const_7_u16_); | |
| 218 | 480 | uint16x8_t acc_0_1_2_3_4_5_6_h = | |
| 219 | 240 | vmlaq_u16(acc_0_2_3_4_6_h, acc_1_5_h, const_7_u16_); | |
| 220 | |||
| 221 | 240 | vst1q(&dst[0], acc_0_1_2_3_4_5_6_l); | |
| 222 | 240 | vst1q(&dst[8], acc_0_1_2_3_4_5_6_h); | |
| 223 | 240 | } | |
| 224 | |||
| 225 | // Applies vertical filtering vector using scalar operations. | ||
| 226 | // | ||
| 227 | // DST = [ SRC0, SRC1, SRC2, SRC3, SRC4, SRC5, SRC6 ] * | ||
| 228 | // * [ 2, 7, 14, 18, 14, 7, 2 ]T | ||
| 229 | 664 | void vertical_scalar_path(const SourceType src[7], BufferType *dst) const { | |
| 230 | 1992 | uint16_t acc = src[0] * 2 + src[1] * 7 + src[2] * 14 + src[3] * 18 + | |
| 231 | 1328 | src[4] * 14 + src[5] * 7 + src[6] * 2; | |
| 232 | 664 | dst[0] = acc; | |
| 233 | 664 | } | |
| 234 | |||
| 235 | // Applies horizontal filtering vector using SIMD operations. | ||
| 236 | // | ||
| 237 | // DST = 1/4096 * [ SRC0, SRC1, SRC2, SRC3, SRC4, SRC5, SRC6 ] * | ||
| 238 | // * [ 2, 7, 14, 18, 14, 7, 2 ]T | ||
| 239 | 216 | void horizontal_vector_path(uint16x8_t src[7], DestinationType *dst) const { | |
| 240 | 432 | uint32x4_t acc_0_6_l = | |
| 241 | 216 | vaddl_u16(vget_low_u16(src[0]), vget_low_u16(src[6])); | |
| 242 | 432 | uint32x4_t acc_0_6_h = | |
| 243 | 216 | vaddl_u16(vget_high_u16(src[0]), vget_high_u16(src[6])); | |
| 244 | |||
| 245 | 432 | uint32x4_t acc_1_5_l = | |
| 246 | 216 | vaddl_u16(vget_low_u16(src[1]), vget_low_u16(src[5])); | |
| 247 | 432 | uint32x4_t acc_1_5_h = | |
| 248 | 216 | vaddl_u16(vget_high_u16(src[1]), vget_high_u16(src[5])); | |
| 249 | |||
| 250 | 216 | uint16x8_t acc_2_4 = vaddq_u16(src[2], src[4]); | |
| 251 | |||
| 252 | 432 | uint32x4_t acc_0_2_4_6_l = | |
| 253 | 216 | vmlal_u16(acc_0_6_l, vget_low_u16(acc_2_4), vget_low_u16(const_7_u16_)); | |
| 254 | 432 | uint32x4_t acc_0_2_4_6_h = vmlal_u16(acc_0_6_h, vget_high_u16(acc_2_4), | |
| 255 | 216 | vget_high_u16(const_7_u16_)); | |
| 256 | |||
| 257 | 432 | uint32x4_t acc_0_2_3_4_6_l = vmlal_u16(acc_0_2_4_6_l, vget_low_u16(src[3]), | |
| 258 | 216 | vget_low_u16(const_9_u16_)); | |
| 259 | 432 | uint32x4_t acc_0_2_3_4_6_h = vmlal_u16(acc_0_2_4_6_h, vget_high_u16(src[3]), | |
| 260 | 216 | vget_high_u16(const_9_u16_)); | |
| 261 | |||
| 262 | 216 | acc_0_2_3_4_6_l = vshlq_n_u32(acc_0_2_3_4_6_l, 1); | |
| 263 | 216 | acc_0_2_3_4_6_h = vshlq_n_u32(acc_0_2_3_4_6_h, 1); | |
| 264 | |||
| 265 | 432 | uint32x4_t acc_0_1_2_3_4_5_6_l = | |
| 266 | 216 | vmlaq_u32(acc_0_2_3_4_6_l, acc_1_5_l, const_7_u32_); | |
| 267 | 432 | uint32x4_t acc_0_1_2_3_4_5_6_h = | |
| 268 | 216 | vmlaq_u32(acc_0_2_3_4_6_h, acc_1_5_h, const_7_u32_); | |
| 269 | |||
| 270 | 216 | uint16x4_t acc_0_1_2_3_4_5_6_u16_l = vrshrn_n_u32(acc_0_1_2_3_4_5_6_l, 12); | |
| 271 | 216 | uint16x4_t acc_0_1_2_3_4_5_6_u16_h = vrshrn_n_u32(acc_0_1_2_3_4_5_6_h, 12); | |
| 272 | |||
| 273 | 432 | uint16x8_t acc_0_1_2_3_4_5_6_u16 = | |
| 274 | 216 | vcombine_u16(acc_0_1_2_3_4_5_6_u16_l, acc_0_1_2_3_4_5_6_u16_h); | |
| 275 | 216 | uint8x8_t acc_0_1_2_3_4_5_6_u8 = vmovn_u16(acc_0_1_2_3_4_5_6_u16); | |
| 276 | |||
| 277 | 216 | vst1(&dst[0], acc_0_1_2_3_4_5_6_u8); | |
| 278 | 216 | } | |
| 279 | |||
| 280 | // Applies horizontal filtering vector using scalar operations. | ||
| 281 | // | ||
| 282 | // DST = 1/4096 * [ SRC0, SRC1, SRC2, SRC3, SRC4, SRC5, SRC6 ] * | ||
| 283 | // * [ 2, 7, 14, 18, 14, 7, 2 ]T | ||
| 284 | 1672 | void horizontal_scalar_path(const BufferType src[7], | |
| 285 | DestinationType *dst) const { | ||
| 286 | 5016 | uint32_t acc = src[0] * 2 + src[1] * 7 + src[2] * 14 + src[3] * 18 + | |
| 287 | 3344 | src[4] * 14 + src[5] * 7 + src[6] * 2; | |
| 288 | 1672 | dst[0] = static_cast<DestinationType>(rounding_shift_right(acc, 12)); | |
| 289 | 1672 | } | |
| 290 | |||
| 291 | private: | ||
| 292 | uint16x8_t const_7_u16_; | ||
| 293 | uint32x4_t const_7_u32_; | ||
| 294 | uint16x8_t const_9_u16_; | ||
| 295 | }; // end of class GaussianBlur<uint8_t, 7, true> | ||
| 296 | |||
| 297 | // Template for 9x9 Gaussian Blur binomial filters. | ||
| 298 | // | ||
| 299 | // [ 16, 52, 120, 204, 240, 204, 120, 52, 16 ] | ||
| 300 | // [ 52, 169, 390, 663, 780, 663, 390, 169, 52 ] | ||
| 301 | // [ 120, 390, 900, 1530, 1800, 1530, 900, 390, 120 ] | ||
| 302 | // F = 1/65536 * [ 204, 663, 1530, 2601, 3060, 2601, 1530, 663, 204 ] = | ||
| 303 | // [ 240, 780, 1800, 3060, 3600, 3060, 1800, 780, 240 ] | ||
| 304 | // [ 204, 663, 1530, 2601, 3060, 2601, 1530, 663, 204 ] | ||
| 305 | // [ 120, 390, 900, 1530, 1800, 1530, 900, 390, 120 ] | ||
| 306 | // [ 52, 169, 390, 663, 780, 663, 390, 169, 52 ] | ||
| 307 | // [ 16, 52, 120, 204, 240, 204, 120, 52, 16 ] | ||
| 308 | // | ||
| 309 | // [ 4 ] | ||
| 310 | // [ 13 ] | ||
| 311 | // [ 30 ] | ||
| 312 | // = 1/65536 * [ 51 ] * [ 4, 13, 30, 51, 60, 51, 30, 13, 4 ] | ||
| 313 | // [ 60 ] | ||
| 314 | // [ 51 ] | ||
| 315 | // [ 30 ] | ||
| 316 | // [ 13 ] | ||
| 317 | // [ 4 ] | ||
| 318 | template <> | ||
| 319 | class GaussianBlur<uint8_t, 9, true> { | ||
| 320 | public: | ||
| 321 | using SourceType = uint8_t; | ||
| 322 | using BufferType = uint16_t; | ||
| 323 | using DestinationType = uint8_t; | ||
| 324 | |||
| 325 | 51 | GaussianBlur() | |
| 326 | 51 | : const_13_u16_{vdupq_n_u16(13)}, | |
| 327 | 51 | const_30_u16_{vdupq_n_u16(30)}, | |
| 328 | 51 | const_51_u16_{vdupq_n_u16(51)}, | |
| 329 | 51 | const_60_u16_{vdupq_n_u16(60)}, | |
| 330 | 51 | const_13_u32_{vdupq_n_u32(13)}, | |
| 331 | 51 | const_30_u32_{vdupq_n_u32(30)}, | |
| 332 | 51 | const_51_u32_{vdupq_n_u32(51)}, | |
| 333 | 51 | const_60_u32_{vdupq_n_u32(60)} {} | |
| 334 | |||
| 335 | // Applies vertical filtering vector using SIMD operations. | ||
| 336 | // | ||
| 337 | // DST = [ SRC0, SRC1, SRC2, SRC3, SRC4, SRC5, SRC6, SRC7, SRC8 ] * | ||
| 338 | // * [ 4, 13, 30, 51, 60, 51, 30, 13, 4 ]T | ||
| 339 | 556 | void vertical_vector_path(uint8x16_t src[9], BufferType *dst) const { | |
| 340 | 556 | uint16x8_t acc_0_8_l = vaddl_u8(vget_low_u8(src[0]), vget_low_u8(src[8])); | |
| 341 | 556 | uint16x8_t acc_0_8_h = vaddl_u8(vget_high_u8(src[0]), vget_high_u8(src[8])); | |
| 342 | |||
| 343 | 556 | uint16x8_t acc_1_7_l = vaddl_u8(vget_low_u8(src[1]), vget_low_u8(src[7])); | |
| 344 | 556 | uint16x8_t acc_1_7_h = vaddl_u8(vget_high_u8(src[1]), vget_high_u8(src[7])); | |
| 345 | |||
| 346 | 556 | uint16x8_t acc_2_6_l = vaddl_u8(vget_low_u8(src[2]), vget_low_u8(src[6])); | |
| 347 | 556 | uint16x8_t acc_2_6_h = vaddl_u8(vget_high_u8(src[2]), vget_high_u8(src[6])); | |
| 348 | |||
| 349 | 556 | uint16x8_t acc_3_5_l = vaddl_u8(vget_low_u8(src[3]), vget_low_u8(src[5])); | |
| 350 | 556 | uint16x8_t acc_3_5_h = vaddl_u8(vget_high_u8(src[3]), vget_high_u8(src[5])); | |
| 351 | |||
| 352 | 556 | uint16x8_t acc_4_l = vmovl_u8(vget_low_u8(src[4])); | |
| 353 | 556 | uint16x8_t acc_4_h = vmovl_u8(vget_high_u8(src[4])); | |
| 354 | |||
| 355 | // Split the work into two independent accumulators. | ||
| 356 | 556 | uint16x8_t acc_l_even = vshlq_n_u16(acc_0_8_l, 2); | |
| 357 | 556 | uint16x8_t acc_h_even = vshlq_n_u16(acc_0_8_h, 2); | |
| 358 | 556 | uint16x8_t acc_l_odd = vmulq_u16(acc_1_7_l, const_13_u16_); | |
| 359 | 556 | uint16x8_t acc_h_odd = vmulq_u16(acc_1_7_h, const_13_u16_); | |
| 360 | |||
| 361 | 556 | acc_l_even = vmlaq_u16(acc_l_even, acc_2_6_l, const_30_u16_); | |
| 362 | 556 | acc_h_even = vmlaq_u16(acc_h_even, acc_2_6_h, const_30_u16_); | |
| 363 | 556 | acc_l_odd = vmlaq_u16(acc_l_odd, acc_3_5_l, const_51_u16_); | |
| 364 | 556 | acc_h_odd = vmlaq_u16(acc_h_odd, acc_3_5_h, const_51_u16_); | |
| 365 | 556 | acc_l_even = vmlaq_u16(acc_l_even, acc_4_l, const_60_u16_); | |
| 366 | 556 | acc_h_even = vmlaq_u16(acc_h_even, acc_4_h, const_60_u16_); | |
| 367 | |||
| 368 | 556 | uint16x8_t acc_l = vaddq_u16(acc_l_even, acc_l_odd); | |
| 369 | 556 | uint16x8_t acc_h = vaddq_u16(acc_h_even, acc_h_odd); | |
| 370 | |||
| 371 | 556 | vst1q(&dst[0], acc_l); | |
| 372 | 556 | vst1q(&dst[8], acc_h); | |
| 373 | 556 | } | |
| 374 | |||
| 375 | // Applies vertical filtering vector using scalar operations. | ||
| 376 | // | ||
| 377 | // DST = [ SRC0, SRC1, SRC2, SRC3, SRC4, SRC5, SRC6, SRC7, SRC8 ] * | ||
| 378 | // * [ 4, 13, 30, 51, 60, 51, 30, 13, 4 ]T | ||
| 379 | 2276 | void vertical_scalar_path(const SourceType src[9], BufferType *dst) const { | |
| 380 | 6828 | uint16_t acc = src[0] * 4 + src[1] * 13 + src[2] * 30 + src[3] * 51 + | |
| 381 | 6828 | src[4] * 60 + src[5] * 51 + src[6] * 30 + src[7] * 13 + | |
| 382 | 2276 | src[8] * 4; | |
| 383 | 2276 | dst[0] = acc; | |
| 384 | 2276 | } | |
| 385 | |||
| 386 | // Applies horizontal filtering vector using SIMD operations. | ||
| 387 | // | ||
| 388 | // DST = 1/65536 * [ SRC0, SRC1, SRC2, SRC3, SRC4, SRC5, SRC6, SRC7, SRC8 ] * | ||
| 389 | // * [ 4, 13, 30, 51, 60, 51, 30, 13, 4 ]T | ||
| 390 | 528 | void horizontal_vector_path(uint16x8_t src[9], DestinationType *dst) const { | |
| 391 | 1056 | uint32x4_t acc_0_8_l = | |
| 392 | 528 | vaddl_u16(vget_low_u16(src[0]), vget_low_u16(src[8])); | |
| 393 | 1056 | uint32x4_t acc_0_8_h = | |
| 394 | 528 | vaddl_u16(vget_high_u16(src[0]), vget_high_u16(src[8])); | |
| 395 | |||
| 396 | 1056 | uint32x4_t acc_1_7_l = | |
| 397 | 528 | vaddl_u16(vget_low_u16(src[1]), vget_low_u16(src[7])); | |
| 398 | 1056 | uint32x4_t acc_1_7_h = | |
| 399 | 528 | vaddl_u16(vget_high_u16(src[1]), vget_high_u16(src[7])); | |
| 400 | |||
| 401 | 1056 | uint32x4_t acc_2_6_l = | |
| 402 | 528 | vaddl_u16(vget_low_u16(src[2]), vget_low_u16(src[6])); | |
| 403 | 1056 | uint32x4_t acc_2_6_h = | |
| 404 | 528 | vaddl_u16(vget_high_u16(src[2]), vget_high_u16(src[6])); | |
| 405 | |||
| 406 | 1056 | uint32x4_t acc_3_5_l = | |
| 407 | 528 | vaddl_u16(vget_low_u16(src[3]), vget_low_u16(src[5])); | |
| 408 | 1056 | uint32x4_t acc_3_5_h = | |
| 409 | 528 | vaddl_u16(vget_high_u16(src[3]), vget_high_u16(src[5])); | |
| 410 | |||
| 411 | 528 | uint32x4_t acc_4_l = vmovl_u16(vget_low_u16(src[4])); | |
| 412 | 528 | uint32x4_t acc_4_h = vmovl_u16(vget_high_u16(src[4])); | |
| 413 | |||
| 414 | // Split the work into two independent accumulators. | ||
| 415 | 528 | uint32x4_t acc_l_even = vshlq_n_u32(acc_0_8_l, 2); | |
| 416 | 528 | uint32x4_t acc_h_even = vshlq_n_u32(acc_0_8_h, 2); | |
| 417 | 528 | uint32x4_t acc_l_odd = vmulq_u32(acc_1_7_l, const_13_u32_); | |
| 418 | 528 | uint32x4_t acc_h_odd = vmulq_u32(acc_1_7_h, const_13_u32_); | |
| 419 | |||
| 420 | 528 | acc_l_even = vmlaq_u32(acc_l_even, acc_2_6_l, const_30_u32_); | |
| 421 | 528 | acc_h_even = vmlaq_u32(acc_h_even, acc_2_6_h, const_30_u32_); | |
| 422 | 528 | acc_l_odd = vmlaq_u32(acc_l_odd, acc_3_5_l, const_51_u32_); | |
| 423 | 528 | acc_h_odd = vmlaq_u32(acc_h_odd, acc_3_5_h, const_51_u32_); | |
| 424 | 528 | acc_l_even = vmlaq_u32(acc_l_even, acc_4_l, const_60_u32_); | |
| 425 | 528 | acc_h_even = vmlaq_u32(acc_h_even, acc_4_h, const_60_u32_); | |
| 426 | |||
| 427 | 528 | uint32x4_t acc_l = vaddq_u32(acc_l_even, acc_l_odd); | |
| 428 | 528 | uint32x4_t acc_h = vaddq_u32(acc_h_even, acc_h_odd); | |
| 429 | |||
| 430 | 528 | uint16x4_t acc_u16_l = vrshrn_n_u32(acc_l, 16); | |
| 431 | 528 | uint16x4_t acc_u16_h = vrshrn_n_u32(acc_h, 16); | |
| 432 | 528 | uint16x8_t acc_u16 = vcombine_u16(acc_u16_l, acc_u16_h); | |
| 433 | 528 | uint8x8_t acc_u8 = vmovn_u16(acc_u16); | |
| 434 | |||
| 435 | 528 | vst1(&dst[0], acc_u8); | |
| 436 | 528 | } | |
| 437 | |||
| 438 | // Applies horizontal filtering vector using scalar operations. | ||
| 439 | // | ||
| 440 | // DST = 1/65536 * [ SRC0, SRC1, SRC2, SRC3, SRC4, SRC5, SRC6, SRC7, SRC8 ] * | ||
| 441 | // * [ 4, 13, 30, 51, 60, 51, 30, 13, 4 ]T | ||
| 442 | 5124 | void horizontal_scalar_path(const BufferType src[9], | |
| 443 | DestinationType *dst) const { | ||
| 444 | 15372 | uint32_t acc = src[0] * 4 + src[1] * 13 + src[2] * 30 + src[3] * 51 + | |
| 445 | 15372 | src[4] * 60 + src[5] * 51 + src[6] * 30 + src[7] * 13 + | |
| 446 | 5124 | src[8] * 4; | |
| 447 | 5124 | dst[0] = static_cast<DestinationType>(rounding_shift_right(acc, 16)); | |
| 448 | 5124 | } | |
| 449 | |||
| 450 | private: | ||
| 451 | uint16x8_t const_13_u16_; | ||
| 452 | uint16x8_t const_30_u16_; | ||
| 453 | uint16x8_t const_51_u16_; | ||
| 454 | uint16x8_t const_60_u16_; | ||
| 455 | uint32x4_t const_13_u32_; | ||
| 456 | uint32x4_t const_30_u32_; | ||
| 457 | uint32x4_t const_51_u32_; | ||
| 458 | uint32x4_t const_60_u32_; | ||
| 459 | }; // end of class GaussianBlur<uint8_t, 9, true> | ||
| 460 | |||
| 461 | template <size_t KernelSize> | ||
| 462 | class GaussianBlur<uint8_t, KernelSize, false> { | ||
| 463 | public: | ||
| 464 | using SourceType = uint8_t; | ||
| 465 | using BufferType = uint8_t; | ||
| 466 | using DestinationType = uint8_t; | ||
| 467 | |||
| 468 | static constexpr size_t kHalfKernelSize = get_half_kernel_size(KernelSize); | ||
| 469 | |||
| 470 | 132 | explicit GaussianBlur(const uint8_t *half_kernel) | |
| 471 | 132 | : half_kernel_(half_kernel) {} | |
| 472 | |||
| 473 | 3760 | void vertical_vector_path(uint8x16_t src[KernelSize], BufferType *dst) const { | |
| 474 | 3760 | common_vector_path(src, dst); | |
| 475 | 3760 | } | |
| 476 | |||
| 477 | 42784 | void vertical_scalar_path(const SourceType src[KernelSize], | |
| 478 | BufferType *dst) const { | ||
| 479 | 42784 | uint16_t acc = src[kHalfKernelSize - 1] * half_kernel_[kHalfKernelSize - 1]; | |
| 480 | |||
| 481 | // Optimization to avoid unnecessary branching in vector code. | ||
| 482 | KLEIDICV_FORCE_LOOP_UNROLL | ||
| 483 |
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390808 | for (size_t i = 0; i < kHalfKernelSize - 1; i++) { |
| 484 | 348024 | acc += (src[i] + src[KernelSize - i - 1]) * half_kernel_[i]; | |
| 485 | 348024 | } | |
| 486 | |||
| 487 | 42784 | dst[0] = static_cast<DestinationType>(rounding_shift_right(acc, 8)); | |
| 488 | 42784 | } | |
| 489 | |||
| 490 | 1056 | void horizontal_vector_path(uint8x16_t src[KernelSize], | |
| 491 | DestinationType *dst) const { | ||
| 492 | 1056 | common_vector_path(src, dst); | |
| 493 | 1056 | } | |
| 494 | |||
| 495 | 39352 | void horizontal_scalar_path(const BufferType src[KernelSize], | |
| 496 | DestinationType *dst) const { | ||
| 497 | 39352 | vertical_scalar_path(src, dst); | |
| 498 | 39352 | } | |
| 499 | |||
| 500 | private: | ||
| 501 | 4816 | void common_vector_path(uint8x16_t src[KernelSize], BufferType *dst) const { | |
| 502 | 4816 | uint8x8_t half_kernel_mid = vdup_n_u8(half_kernel_[kHalfKernelSize - 1]); | |
| 503 | 9632 | uint16x8_t acc_l = | |
| 504 | 9632 | vmlal_u8(vdupq_n_u16(128), vget_low_u8(src[kHalfKernelSize - 1]), | |
| 505 | 4816 | half_kernel_mid); | |
| 506 | 9632 | uint16x8_t acc_h = | |
| 507 | 9632 | vmlal_u8(vdupq_n_u16(128), vget_high_u8(src[kHalfKernelSize - 1]), | |
| 508 | 4816 | half_kernel_mid); | |
| 509 | |||
| 510 | // Optimization to avoid unnecessary branching in vector code. | ||
| 511 | KLEIDICV_FORCE_LOOP_UNROLL | ||
| 512 |
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43920 | for (size_t i = 0; i < kHalfKernelSize - 1; i++) { |
| 513 | 39104 | const size_t j = KernelSize - i - 1; | |
| 514 | 39104 | uint16x8_t vec_l = vaddl_u8(vget_low_u8(src[i]), vget_low_u8(src[j])); | |
| 515 | 39104 | uint16x8_t vec_h = vaddl_high_u8(src[i], src[j]); | |
| 516 | 39104 | uint16x8_t coeff = vdupq_n_u16(half_kernel_[i]); | |
| 517 | |||
| 518 | 39104 | acc_l = vmlaq_u16(acc_l, vec_l, coeff); | |
| 519 | 39104 | acc_h = vmlaq_u16(acc_h, vec_h, coeff); | |
| 520 | 39104 | } | |
| 521 | |||
| 522 | // Keep only the highest 8 bits | ||
| 523 | 9632 | uint8x16_t result = | |
| 524 | 4816 | vuzp2q_u8(vreinterpretq_u8_u16(acc_l), vreinterpretq_u8_u16(acc_h)); | |
| 525 | 4816 | neon::VecTraits<uint8_t>::store(result, &dst[0]); | |
| 526 | 4816 | } | |
| 527 | |||
| 528 | const uint8_t *half_kernel_; | ||
| 529 | }; // end of class GaussianBlur<uint8_t, KernelSize, false> | ||
| 530 | |||
| 531 | template <size_t KernelSize, bool IsBinomial, typename ScalarType> | ||
| 532 | 430 | static kleidicv_error_t gaussian_blur_fixed_kernel_size( | |
| 533 | const ScalarType *src, size_t src_stride, ScalarType *dst, | ||
| 534 | size_t dst_stride, Rectangle &rect, size_t y_begin, size_t y_end, | ||
| 535 | size_t channels, float sigma, FixedBorderType border_type) { | ||
| 536 | using GaussianBlurFilter = GaussianBlur<ScalarType, KernelSize, IsBinomial>; | ||
| 537 | 430 | constexpr size_t intermediate_size{ | |
| 538 | sizeof(typename GaussianBlurFilter::BufferType)}; | ||
| 539 | |||
| 540 | 430 | auto workspace_variant = | |
| 541 | 430 | SeparableFilterWorkspace::create(rect, channels, intermediate_size); | |
| 542 |
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440 | if (auto *err = std::get_if<kleidicv_error_t>(&workspace_variant)) { |
| 543 | 10 | return *err; | |
| 544 | } | ||
| 545 | 420 | auto &workspace = *std::get_if<SeparableFilterWorkspace>(&workspace_variant); | |
| 546 | |||
| 547 | 420 | Rows<const ScalarType> src_rows{src, src_stride, channels}; | |
| 548 | 420 | Rows<ScalarType> dst_rows{dst, dst_stride, channels}; | |
| 549 | |||
| 550 | if constexpr (IsBinomial) { | ||
| 551 | 192 | GaussianBlurFilter blur; | |
| 552 | 192 | SeparableFilter<GaussianBlurFilter, KernelSize> filter{blur}; | |
| 553 | 192 | workspace.process(y_begin, y_end, src_rows, dst_rows, border_type, filter); | |
| 554 | 192 | return KLEIDICV_OK; | |
| 555 | 192 | } else { | |
| 556 | 228 | constexpr size_t kHalfKernelSize = get_half_kernel_size(KernelSize); | |
| 557 | 228 | uint8_t half_kernel[128]; | |
| 558 | 456 | bool success = | |
| 559 | 228 | generate_gaussian_half_kernel(half_kernel, kHalfKernelSize, sigma); | |
| 560 |
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228 | if (success) { |
| 561 | 132 | GaussianBlurFilter blur(half_kernel); | |
| 562 | 132 | SeparableFilter<GaussianBlurFilter, KernelSize> filter{blur}; | |
| 563 | 264 | workspace.process(y_begin, y_end, src_rows, dst_rows, border_type, | |
| 564 | 132 | filter); | |
| 565 | 132 | } else { | |
| 566 | // Sigma is too small that the middle point would get all the weight | ||
| 567 | // => it's just a copy. | ||
| 568 |
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984 | for (size_t row = y_begin; row < y_end; ++row) { |
| 569 | 1776 | std::memcpy(static_cast<void *>(&dst_rows.at(row)[0]), | |
| 570 | 888 | static_cast<const void *>(&src_rows.at(row)[0]), | |
| 571 | 888 | rect.width() * sizeof(ScalarType) * dst_rows.channels()); | |
| 572 | 888 | } | |
| 573 | } | ||
| 574 | 228 | return KLEIDICV_OK; | |
| 575 | 228 | } | |
| 576 | 430 | } | |
| 577 | |||
| 578 | template <bool IsBinomial, typename ScalarType> | ||
| 579 | 430 | static kleidicv_error_t gaussian_blur_fixed( | |
| 580 | size_t kernel_size, const ScalarType *src, size_t src_stride, | ||
| 581 | ScalarType *dst, size_t dst_stride, Rectangle &rect, size_t y_begin, | ||
| 582 | size_t y_end, size_t channels, float sigma, FixedBorderType border_type) { | ||
| 583 |
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430 | switch (kernel_size) { |
| 584 | case 3: | ||
| 585 | 82 | return gaussian_blur_fixed_kernel_size<3, IsBinomial>( | |
| 586 | 82 | src, src_stride, dst, dst_stride, rect, y_begin, y_end, channels, | |
| 587 | 82 | sigma, border_type); | |
| 588 | case 5: | ||
| 589 | 96 | return gaussian_blur_fixed_kernel_size<5, IsBinomial>( | |
| 590 | 96 | src, src_stride, dst, dst_stride, rect, y_begin, y_end, channels, | |
| 591 | 96 | sigma, border_type); | |
| 592 | case 7: | ||
| 593 | 68 | return gaussian_blur_fixed_kernel_size<7, IsBinomial>( | |
| 594 | 68 | src, src_stride, dst, dst_stride, rect, y_begin, y_end, channels, | |
| 595 | 68 | sigma, border_type); | |
| 596 | case 9: | ||
| 597 | 86 | return gaussian_blur_fixed_kernel_size<9, IsBinomial>( | |
| 598 | 86 | src, src_stride, dst, dst_stride, rect, y_begin, y_end, channels, | |
| 599 | 86 | sigma, border_type); | |
| 600 | case 15: | ||
| 601 | // 15x15 does not have a binomial variant | ||
| 602 | 49 | return gaussian_blur_fixed_kernel_size<15, false>( | |
| 603 | 49 | src, src_stride, dst, dst_stride, rect, y_begin, y_end, channels, | |
| 604 | 49 | sigma, border_type); | |
| 605 | case 21: | ||
| 606 | // 21x21 does not have a binomial variant | ||
| 607 | 49 | return gaussian_blur_fixed_kernel_size<21, false>( | |
| 608 | 49 | src, src_stride, dst, dst_stride, rect, y_begin, y_end, channels, | |
| 609 | 49 | sigma, border_type); | |
| 610 | // gaussian_blur_is_implemented checked the kernel size already. | ||
| 611 | // GCOVR_EXCL_START | ||
| 612 | default: | ||
| 613 | assert(!"kernel size not implemented"); | ||
| 614 | − | return KLEIDICV_ERROR_NOT_IMPLEMENTED; | |
| 615 | // GCOVR_EXCL_STOP | ||
| 616 | } | ||
| 617 | 430 | } | |
| 618 | |||
| 619 | KLEIDICV_TARGET_FN_ATTRS | ||
| 620 | 440 | kleidicv_error_t gaussian_blur_fixed_stripe_u8( | |
| 621 | const uint8_t *src, size_t src_stride, uint8_t *dst, size_t dst_stride, | ||
| 622 | size_t width, size_t height, size_t y_begin, size_t y_end, size_t channels, | ||
| 623 | size_t kernel_width, size_t /*kernel_height*/, float sigma_x, | ||
| 624 | float /*sigma_y*/, FixedBorderType fixed_border_type) { | ||
| 625 |
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1320 | if (auto result = |
| 626 | 440 | gaussian_blur_checks(src, src_stride, dst, dst_stride, width, height); | |
| 627 |
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450 | result != KLEIDICV_OK) { |
| 628 | 10 | return result; | |
| 629 | } | ||
| 630 | |||
| 631 | 430 | Rectangle rect{width, height}; | |
| 632 | |||
| 633 |
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430 | if (sigma_x == 0.0) { |
| 634 | 456 | return gaussian_blur_fixed<true>(kernel_width, src, src_stride, dst, | |
| 635 | 228 | dst_stride, rect, y_begin, y_end, channels, | |
| 636 | 228 | sigma_x, fixed_border_type); | |
| 637 | } | ||
| 638 | |||
| 639 | 404 | return gaussian_blur_fixed<false>(kernel_width, src, src_stride, dst, | |
| 640 | 202 | dst_stride, rect, y_begin, y_end, channels, | |
| 641 | 202 | sigma_x, fixed_border_type); | |
| 642 | 440 | } | |
| 643 | |||
| 644 | } // namespace kleidicv::neon | ||
| 645 |