| Line | Branch | Exec | Source |
|---|---|---|---|
| 1 | // SPDX-FileCopyrightText: 2023 - 2025 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/sigma.h" | ||
| 17 | #include "kleidicv/neon.h" | ||
| 18 | #include "kleidicv/workspace/border_types.h" | ||
| 19 | #include "kleidicv/workspace/separable.h" | ||
| 20 | |||
| 21 | namespace kleidicv::neon { | ||
| 22 | |||
| 23 | // Primary template for Gaussian Blur filters. | ||
| 24 | template <typename ScalarType, size_t KernelSize, bool IsBinomial> | ||
| 25 | class GaussianBlur; | ||
| 26 | |||
| 27 | // Template for 3x3 Gaussian Blur binomial filters. | ||
| 28 | // | ||
| 29 | // [ 1, 2, 1 ] [ 1 ] | ||
| 30 | // F = 1/16 * [ 2, 4, 2 ] = 1/16 * [ 2 ] * [ 1, 2, 1 ] | ||
| 31 | // [ 1, 2, 1 ] [ 1 ] | ||
| 32 | template <> | ||
| 33 | class GaussianBlur<uint8_t, 3, true> { | ||
| 34 | public: | ||
| 35 | using ScalarType = uint8_t; | ||
| 36 | using SourceType = ScalarType; | ||
| 37 | using SourceVectorType = typename VecTraits<SourceType>::VectorType; | ||
| 38 | using BufferType = double_element_width_t<ScalarType>; | ||
| 39 | using BufferVectorType = typename VecTraits<BufferType>::VectorType; | ||
| 40 | using DestinationType = ScalarType; | ||
| 41 | |||
| 42 | // Applies vertical filtering vector using SIMD operations. | ||
| 43 | // | ||
| 44 | // DST = [ SRC0, SRC1, SRC2 ] * [ 1, 2, 1 ]T | ||
| 45 | 114 | void vertical_vector_path(SourceVectorType src[3], BufferType *dst) const { | |
| 46 | // acc_0_2 = src[0] + src[2] | ||
| 47 | 114 | BufferVectorType acc_0_2_l = vaddl(vget_low(src[0]), vget_low(src[2])); | |
| 48 | 114 | BufferVectorType acc_0_2_h = vaddl(vget_high(src[0]), vget_high(src[2])); | |
| 49 | // acc_1 = src[1] + src[1] | ||
| 50 | 114 | BufferVectorType acc_1_l = vshll_n<1>(vget_low(src[1])); | |
| 51 | 114 | BufferVectorType acc_1_h = vshll_n<1>(vget_high(src[1])); | |
| 52 | // acc = acc_0_2 + acc_1 | ||
| 53 | 114 | BufferVectorType acc_l = vaddq(acc_0_2_l, acc_1_l); | |
| 54 | 114 | BufferVectorType acc_h = vaddq(acc_0_2_h, acc_1_h); | |
| 55 | |||
| 56 | 114 | VecTraits<BufferType>::store_consecutive(acc_l, acc_h, &dst[0]); | |
| 57 | 114 | } | |
| 58 | |||
| 59 | // Applies vertical filtering vector using scalar operations. | ||
| 60 | // | ||
| 61 | // DST = [ SRC0, SRC1, SRC2 ] * [ 1, 2, 1 ]T | ||
| 62 | 320 | void vertical_scalar_path(const SourceType src[3], BufferType *dst) const { | |
| 63 | 320 | dst[0] = src[0] + 2 * src[1] + src[2]; | |
| 64 | 320 | } | |
| 65 | |||
| 66 | // Applies horizontal filtering vector using SIMD operations. | ||
| 67 | // | ||
| 68 | // DST = 1/16 * [ SRC0, SRC1, SRC2 ] * [ 1, 2, 1 ]T | ||
| 69 | 176 | void horizontal_vector_path(BufferVectorType src[3], | |
| 70 | DestinationType *dst) const { | ||
| 71 | 176 | BufferVectorType acc_wide = vaddq(src[0], src[2]); | |
| 72 | 176 | acc_wide = vaddq(acc_wide, vshlq_n<1>(src[1])); | |
| 73 | 176 | auto acc_narrow = vrshrn_n<4>(acc_wide); | |
| 74 | 176 | vst1(&dst[0], acc_narrow); | |
| 75 | 176 | } | |
| 76 | |||
| 77 | // Applies horizontal filtering vector using scalar operations. | ||
| 78 | // | ||
| 79 | // DST = 1/16 * [ SRC0, SRC1, SRC2 ] * [ 1, 2, 1 ]T | ||
| 80 | 452 | void horizontal_scalar_path(const BufferType src[3], | |
| 81 | DestinationType *dst) const { | ||
| 82 | 452 | auto acc = src[0] + 2 * src[1] + src[2]; | |
| 83 | 452 | dst[0] = rounding_shift_right(acc, 4); | |
| 84 | 452 | } | |
| 85 | }; // end of class GaussianBlur<uint8_t, 3, true> | ||
| 86 | |||
| 87 | // Template for 5x5 Gaussian Blur binomial filters. | ||
| 88 | // | ||
| 89 | // [ 1, 4, 6, 4, 1 ] [ 1 ] | ||
| 90 | // [ 4, 16, 24, 16, 4 ] [ 4 ] | ||
| 91 | // F = 1/256 * [ 6, 24, 36, 24, 6 ] = 1/256 * [ 6 ] * [ 1, 4, 6, 4, 1 ] | ||
| 92 | // [ 4, 16, 24, 16, 4 ] [ 4 ] | ||
| 93 | // [ 1, 4, 6, 4, 1 ] [ 1 ] | ||
| 94 | template <> | ||
| 95 | class GaussianBlur<uint8_t, 5, true> { | ||
| 96 | public: | ||
| 97 | using SourceType = uint8_t; | ||
| 98 | using BufferType = uint16_t; | ||
| 99 | using DestinationType = uint8_t; | ||
| 100 | |||
| 101 | 51 | GaussianBlur() | |
| 102 | 51 | : const_6_u8_half_{vdup_n_u8(6)}, | |
| 103 | 51 | const_6_u16_{vdupq_n_u16(6)}, | |
| 104 | 51 | const_4_u16_{vdupq_n_u16(4)} {} | |
| 105 | |||
| 106 | // Applies vertical filtering vector using SIMD operations. | ||
| 107 | // | ||
| 108 | // DST = [ SRC0, SRC1, SRC2, SRC3, SRC4 ] * [ 1, 4, 6, 4, 1 ]T | ||
| 109 | 300 | void vertical_vector_path(uint8x16_t src[5], BufferType *dst) const { | |
| 110 | 300 | uint16x8_t acc_0_4_l = vaddl_u8(vget_low_u8(src[0]), vget_low_u8(src[4])); | |
| 111 | 300 | uint16x8_t acc_0_4_h = vaddl_u8(vget_high_u8(src[0]), vget_high_u8(src[4])); | |
| 112 | 300 | uint16x8_t acc_1_3_l = vaddl_u8(vget_low_u8(src[1]), vget_low_u8(src[3])); | |
| 113 | 300 | uint16x8_t acc_1_3_h = vaddl_u8(vget_high_u8(src[1]), vget_high_u8(src[3])); | |
| 114 | 600 | uint16x8_t acc_l = | |
| 115 | 300 | vmlal_u8(acc_0_4_l, vget_low_u8(src[2]), const_6_u8_half_); | |
| 116 | 600 | uint16x8_t acc_h = | |
| 117 | 300 | vmlal_u8(acc_0_4_h, vget_high_u8(src[2]), const_6_u8_half_); | |
| 118 | 300 | acc_l = vmlaq_u16(acc_l, acc_1_3_l, const_4_u16_); | |
| 119 | 300 | acc_h = vmlaq_u16(acc_h, acc_1_3_h, const_4_u16_); | |
| 120 | 300 | vst1q(&dst[0], acc_l); | |
| 121 | 300 | vst1q(&dst[8], acc_h); | |
| 122 | 300 | } | |
| 123 | |||
| 124 | // Applies vertical filtering vector using scalar operations. | ||
| 125 | // | ||
| 126 | // DST = [ SRC0, SRC1, SRC2, SRC3, SRC4 ] * [ 1, 4, 6, 4, 1 ]T | ||
| 127 | 3820 | void vertical_scalar_path(const SourceType src[5], BufferType *dst) const { | |
| 128 | 3820 | dst[0] = src[0] + src[4] + 4 * (src[1] + src[3]) + 6 * src[2]; | |
| 129 | 3820 | } | |
| 130 | |||
| 131 | // Applies horizontal filtering vector using SIMD operations. | ||
| 132 | // | ||
| 133 | // DST = 1/256 * [ SRC0, SRC1, SRC2, SRC3, SRC4 ] * [ 1, 4, 6, 4, 1 ]T | ||
| 134 | 604 | void horizontal_vector_path(uint16x8_t src[5], DestinationType *dst) const { | |
| 135 | 604 | uint16x8_t acc_0_4 = vaddq_u16(src[0], src[4]); | |
| 136 | 604 | uint16x8_t acc_1_3 = vaddq_u16(src[1], src[3]); | |
| 137 | 604 | uint16x8_t acc_u16 = vmlaq_u16(acc_0_4, src[2], const_6_u16_); | |
| 138 | 604 | acc_u16 = vmlaq_u16(acc_u16, acc_1_3, const_4_u16_); | |
| 139 | 604 | uint8x8_t acc_u8 = vrshrn_n_u16(acc_u16, 8); | |
| 140 | 604 | vst1(&dst[0], acc_u8); | |
| 141 | 604 | } | |
| 142 | |||
| 143 | // Applies horizontal filtering vector using scalar operations. | ||
| 144 | // | ||
| 145 | // DST = 1/256 * [ SRC0, SRC1, SRC2, SRC3, SRC4 ] * [ 1, 4, 6, 4, 1 ]T | ||
| 146 | 3068 | void horizontal_scalar_path(const BufferType src[5], | |
| 147 | DestinationType *dst) const { | ||
| 148 | 3068 | auto acc = src[0] + src[4] + 4 * (src[1] + src[3]) + 6 * src[2]; | |
| 149 | 3068 | dst[0] = rounding_shift_right(acc, 8); | |
| 150 | 3068 | } | |
| 151 | |||
| 152 | private: | ||
| 153 | uint8x8_t const_6_u8_half_; | ||
| 154 | uint16x8_t const_6_u16_; | ||
| 155 | uint16x8_t const_4_u16_; | ||
| 156 | }; // end of class GaussianBlur<uint8_t, 5, true> | ||
| 157 | |||
| 158 | // Template for 7x7 Gaussian Blur binomial filters. | ||
| 159 | // | ||
| 160 | // [ 4, 14, 28, 36, 28, 14, 4 ] | ||
| 161 | // [ 14, 49, 98, 126, 98, 49, 14 ] | ||
| 162 | // [ 28, 98, 196, 252, 196, 98, 28 ] | ||
| 163 | // F = 1/4096 * [ 36, 126, 252, 324, 252, 126, 36 ] = | ||
| 164 | // [ 28, 98, 196, 252, 196, 98, 28 ] | ||
| 165 | // [ 14, 49, 98, 126, 98, 49, 14 ] | ||
| 166 | // [ 4, 14, 28, 36, 28, 14, 4 ] | ||
| 167 | // | ||
| 168 | // [ 2 ] | ||
| 169 | // [ 7 ] | ||
| 170 | // [ 14 ] | ||
| 171 | // = 1/4096 * [ 18 ] * [ 2, 7, 14, 18, 14, 7, 2 ] | ||
| 172 | // [ 14 ] | ||
| 173 | // [ 7 ] | ||
| 174 | // [ 2 ] | ||
| 175 | template <> | ||
| 176 | class GaussianBlur<uint8_t, 7, true> { | ||
| 177 | public: | ||
| 178 | using SourceType = uint8_t; | ||
| 179 | using BufferType = uint16_t; | ||
| 180 | using DestinationType = uint8_t; | ||
| 181 | |||
| 182 | 33 | GaussianBlur() | |
| 183 | 33 | : const_7_u16_{vdupq_n_u16(7)}, | |
| 184 | 33 | const_7_u32_{vdupq_n_u32(7)}, | |
| 185 | 33 | const_9_u16_{vdupq_n_u16(9)} {} | |
| 186 | |||
| 187 | // Applies vertical filtering vector using SIMD operations. | ||
| 188 | // | ||
| 189 | // DST = [ SRC0, SRC1, SRC2, SRC3, SRC4, SRC5, SRC6 ] * | ||
| 190 | // * [ 2, 7, 14, 18, 14, 7, 2 ]T | ||
| 191 | 240 | void vertical_vector_path(uint8x16_t src[7], BufferType *dst) const { | |
| 192 | 240 | uint16x8_t acc_0_6_l = vaddl_u8(vget_low_u8(src[0]), vget_low_u8(src[6])); | |
| 193 | 240 | uint16x8_t acc_0_6_h = vaddl_u8(vget_high_u8(src[0]), vget_high_u8(src[6])); | |
| 194 | |||
| 195 | 240 | uint16x8_t acc_1_5_l = vaddl_u8(vget_low_u8(src[1]), vget_low_u8(src[5])); | |
| 196 | 240 | uint16x8_t acc_1_5_h = vaddl_u8(vget_high_u8(src[1]), vget_high_u8(src[5])); | |
| 197 | |||
| 198 | 240 | uint16x8_t acc_2_4_l = vaddl_u8(vget_low_u8(src[2]), vget_low_u8(src[4])); | |
| 199 | 240 | uint16x8_t acc_2_4_h = vaddl_u8(vget_high_u8(src[2]), vget_high_u8(src[4])); | |
| 200 | |||
| 201 | 240 | uint16x8_t acc_3_l = vmovl_u8(vget_low_u8(src[3])); | |
| 202 | 240 | uint16x8_t acc_3_h = vmovl_u8(vget_high_u8(src[3])); | |
| 203 | |||
| 204 | 240 | uint16x8_t acc_0_2_4_6_l = vmlaq_u16(acc_0_6_l, acc_2_4_l, const_7_u16_); | |
| 205 | 240 | uint16x8_t acc_0_2_4_6_h = vmlaq_u16(acc_0_6_h, acc_2_4_h, const_7_u16_); | |
| 206 | |||
| 207 | 480 | uint16x8_t acc_0_2_3_4_6_l = | |
| 208 | 240 | vmlaq_u16(acc_0_2_4_6_l, acc_3_l, const_9_u16_); | |
| 209 | 480 | uint16x8_t acc_0_2_3_4_6_h = | |
| 210 | 240 | vmlaq_u16(acc_0_2_4_6_h, acc_3_h, const_9_u16_); | |
| 211 | |||
| 212 | 240 | acc_0_2_3_4_6_l = vshlq_n_u16(acc_0_2_3_4_6_l, 1); | |
| 213 | 240 | acc_0_2_3_4_6_h = vshlq_n_u16(acc_0_2_3_4_6_h, 1); | |
| 214 | |||
| 215 | 480 | uint16x8_t acc_0_1_2_3_4_5_6_l = | |
| 216 | 240 | vmlaq_u16(acc_0_2_3_4_6_l, acc_1_5_l, const_7_u16_); | |
| 217 | 480 | uint16x8_t acc_0_1_2_3_4_5_6_h = | |
| 218 | 240 | vmlaq_u16(acc_0_2_3_4_6_h, acc_1_5_h, const_7_u16_); | |
| 219 | |||
| 220 | 240 | vst1q(&dst[0], acc_0_1_2_3_4_5_6_l); | |
| 221 | 240 | vst1q(&dst[8], acc_0_1_2_3_4_5_6_h); | |
| 222 | 240 | } | |
| 223 | |||
| 224 | // Applies vertical filtering vector using scalar operations. | ||
| 225 | // | ||
| 226 | // DST = [ SRC0, SRC1, SRC2, SRC3, SRC4, SRC5, SRC6 ] * | ||
| 227 | // * [ 2, 7, 14, 18, 14, 7, 2 ]T | ||
| 228 | 664 | void vertical_scalar_path(const SourceType src[7], BufferType *dst) const { | |
| 229 | 1992 | uint16_t acc = src[0] * 2 + src[1] * 7 + src[2] * 14 + src[3] * 18 + | |
| 230 | 1328 | src[4] * 14 + src[5] * 7 + src[6] * 2; | |
| 231 | 664 | dst[0] = acc; | |
| 232 | 664 | } | |
| 233 | |||
| 234 | // Applies horizontal filtering vector using SIMD operations. | ||
| 235 | // | ||
| 236 | // DST = 1/4096 * [ SRC0, SRC1, SRC2, SRC3, SRC4, SRC5, SRC6 ] * | ||
| 237 | // * [ 2, 7, 14, 18, 14, 7, 2 ]T | ||
| 238 | 216 | void horizontal_vector_path(uint16x8_t src[7], DestinationType *dst) const { | |
| 239 | 432 | uint32x4_t acc_0_6_l = | |
| 240 | 216 | vaddl_u16(vget_low_u16(src[0]), vget_low_u16(src[6])); | |
| 241 | 432 | uint32x4_t acc_0_6_h = | |
| 242 | 216 | vaddl_u16(vget_high_u16(src[0]), vget_high_u16(src[6])); | |
| 243 | |||
| 244 | 432 | uint32x4_t acc_1_5_l = | |
| 245 | 216 | vaddl_u16(vget_low_u16(src[1]), vget_low_u16(src[5])); | |
| 246 | 432 | uint32x4_t acc_1_5_h = | |
| 247 | 216 | vaddl_u16(vget_high_u16(src[1]), vget_high_u16(src[5])); | |
| 248 | |||
| 249 | 216 | uint16x8_t acc_2_4 = vaddq_u16(src[2], src[4]); | |
| 250 | |||
| 251 | 432 | uint32x4_t acc_0_2_4_6_l = | |
| 252 | 216 | vmlal_u16(acc_0_6_l, vget_low_u16(acc_2_4), vget_low_u16(const_7_u16_)); | |
| 253 | 432 | uint32x4_t acc_0_2_4_6_h = vmlal_u16(acc_0_6_h, vget_high_u16(acc_2_4), | |
| 254 | 216 | vget_high_u16(const_7_u16_)); | |
| 255 | |||
| 256 | 432 | uint32x4_t acc_0_2_3_4_6_l = vmlal_u16(acc_0_2_4_6_l, vget_low_u16(src[3]), | |
| 257 | 216 | vget_low_u16(const_9_u16_)); | |
| 258 | 432 | uint32x4_t acc_0_2_3_4_6_h = vmlal_u16(acc_0_2_4_6_h, vget_high_u16(src[3]), | |
| 259 | 216 | vget_high_u16(const_9_u16_)); | |
| 260 | |||
| 261 | 216 | acc_0_2_3_4_6_l = vshlq_n_u32(acc_0_2_3_4_6_l, 1); | |
| 262 | 216 | acc_0_2_3_4_6_h = vshlq_n_u32(acc_0_2_3_4_6_h, 1); | |
| 263 | |||
| 264 | 432 | uint32x4_t acc_0_1_2_3_4_5_6_l = | |
| 265 | 216 | vmlaq_u32(acc_0_2_3_4_6_l, acc_1_5_l, const_7_u32_); | |
| 266 | 432 | uint32x4_t acc_0_1_2_3_4_5_6_h = | |
| 267 | 216 | vmlaq_u32(acc_0_2_3_4_6_h, acc_1_5_h, const_7_u32_); | |
| 268 | |||
| 269 | 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); | |
| 270 | 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); | |
| 271 | |||
| 272 | 432 | uint16x8_t acc_0_1_2_3_4_5_6_u16 = | |
| 273 | 216 | vcombine_u16(acc_0_1_2_3_4_5_6_u16_l, acc_0_1_2_3_4_5_6_u16_h); | |
| 274 | 216 | uint8x8_t acc_0_1_2_3_4_5_6_u8 = vmovn_u16(acc_0_1_2_3_4_5_6_u16); | |
| 275 | |||
| 276 | 216 | vst1(&dst[0], acc_0_1_2_3_4_5_6_u8); | |
| 277 | 216 | } | |
| 278 | |||
| 279 | // Applies horizontal filtering vector using scalar operations. | ||
| 280 | // | ||
| 281 | // DST = 1/4096 * [ SRC0, SRC1, SRC2, SRC3, SRC4, SRC5, SRC6 ] * | ||
| 282 | // * [ 2, 7, 14, 18, 14, 7, 2 ]T | ||
| 283 | 1672 | void horizontal_scalar_path(const BufferType src[7], | |
| 284 | DestinationType *dst) const { | ||
| 285 | 5016 | uint32_t acc = src[0] * 2 + src[1] * 7 + src[2] * 14 + src[3] * 18 + | |
| 286 | 3344 | src[4] * 14 + src[5] * 7 + src[6] * 2; | |
| 287 | 1672 | dst[0] = static_cast<DestinationType>(rounding_shift_right(acc, 12)); | |
| 288 | 1672 | } | |
| 289 | |||
| 290 | private: | ||
| 291 | uint16x8_t const_7_u16_; | ||
| 292 | uint32x4_t const_7_u32_; | ||
| 293 | uint16x8_t const_9_u16_; | ||
| 294 | }; // end of class GaussianBlur<uint8_t, 7, true> | ||
| 295 | |||
| 296 | template <size_t KernelSize> | ||
| 297 | class GaussianBlur<uint8_t, KernelSize, false> { | ||
| 298 | public: | ||
| 299 | using SourceType = uint8_t; | ||
| 300 | using BufferType = uint8_t; | ||
| 301 | using DestinationType = uint8_t; | ||
| 302 | |||
| 303 | static constexpr size_t kHalfKernelSize = get_half_kernel_size(KernelSize); | ||
| 304 | |||
| 305 | 115 | explicit GaussianBlur(const uint16_t *half_kernel) | |
| 306 | 115 | : half_kernel_(half_kernel) {} | |
| 307 | |||
| 308 | 3504 | void vertical_vector_path(uint8x16_t src[KernelSize], BufferType *dst) const { | |
| 309 | 3504 | common_vector_path(src, dst); | |
| 310 | 3504 | } | |
| 311 | |||
| 312 | 40312 | void vertical_scalar_path(const SourceType src[KernelSize], | |
| 313 | BufferType *dst) const { | ||
| 314 | 80624 | uint16_t acc = static_cast<uint16_t>(src[kHalfKernelSize - 1]) * | |
| 315 | 40312 | half_kernel_[kHalfKernelSize - 1]; | |
| 316 | |||
| 317 | // Optimization to avoid unnecessary branching in vector code. | ||
| 318 | KLEIDICV_FORCE_LOOP_UNROLL | ||
| 319 |
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378448 | for (size_t i = 0; i < kHalfKernelSize - 1; i++) { |
| 320 | 1014408 | acc += (static_cast<uint16_t>(src[i]) + | |
| 321 | 676272 | static_cast<uint16_t>(src[KernelSize - i - 1])) * | |
| 322 | 338136 | half_kernel_[i]; | |
| 323 | 338136 | } | |
| 324 | |||
| 325 | 40312 | dst[0] = static_cast<DestinationType>(rounding_shift_right(acc, 8)); | |
| 326 | 40312 | } | |
| 327 | |||
| 328 | 960 | void horizontal_vector_path(uint8x16_t src[KernelSize], | |
| 329 | DestinationType *dst) const { | ||
| 330 | 960 | common_vector_path(src, dst); | |
| 331 | 960 | } | |
| 332 | |||
| 333 | 37268 | void horizontal_scalar_path(const BufferType src[KernelSize], | |
| 334 | DestinationType *dst) const { | ||
| 335 | 37268 | vertical_scalar_path(src, dst); | |
| 336 | 37268 | } | |
| 337 | |||
| 338 | private: | ||
| 339 | 4464 | void common_vector_path(uint8x16_t src[KernelSize], BufferType *dst) const { | |
| 340 | 4464 | uint8x8_t half_kernel_mid = vdup_n_u8(half_kernel_[kHalfKernelSize - 1]); | |
| 341 | 8928 | uint16x8_t acc_l = | |
| 342 | 8928 | vmlal_u8(vdupq_n_u16(128), vget_low_u8(src[kHalfKernelSize - 1]), | |
| 343 | 4464 | half_kernel_mid); | |
| 344 | 8928 | uint16x8_t acc_h = | |
| 345 | 8928 | vmlal_u8(vdupq_n_u16(128), vget_high_u8(src[kHalfKernelSize - 1]), | |
| 346 | 4464 | half_kernel_mid); | |
| 347 | |||
| 348 | // Optimization to avoid unnecessary branching in vector code. | ||
| 349 | KLEIDICV_FORCE_LOOP_UNROLL | ||
| 350 |
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42160 | for (size_t i = 0; i < kHalfKernelSize - 1; i++) { |
| 351 | 37696 | const size_t j = KernelSize - i - 1; | |
| 352 | 37696 | uint16x8_t vec_l = vaddl_u8(vget_low_u8(src[i]), vget_low_u8(src[j])); | |
| 353 | 37696 | uint16x8_t vec_h = vaddl_high_u8(src[i], src[j]); | |
| 354 | 37696 | uint16x8_t coeff = vdupq_n_u16(half_kernel_[i]); | |
| 355 | |||
| 356 | 37696 | acc_l = vmlaq_u16(acc_l, vec_l, coeff); | |
| 357 | 37696 | acc_h = vmlaq_u16(acc_h, vec_h, coeff); | |
| 358 | 37696 | } | |
| 359 | |||
| 360 | // Keep only the highest 8 bits | ||
| 361 | 8928 | uint8x16_t result = | |
| 362 | 4464 | vuzp2q_u8(vreinterpretq_u8_u16(acc_l), vreinterpretq_u8_u16(acc_h)); | |
| 363 | 4464 | neon::VecTraits<uint8_t>::store(result, &dst[0]); | |
| 364 | 4464 | } | |
| 365 | |||
| 366 | const uint16_t *half_kernel_; | ||
| 367 | }; // end of class GaussianBlur<uint8_t, KernelSize, false> | ||
| 368 | |||
| 369 | template <size_t KernelSize, bool IsBinomial, typename ScalarType> | ||
| 370 | 326 | static kleidicv_error_t gaussian_blur_fixed_kernel_size( | |
| 371 | const ScalarType *src, size_t src_stride, ScalarType *dst, | ||
| 372 | size_t dst_stride, Rectangle &rect, size_t y_begin, size_t y_end, | ||
| 373 | size_t channels, float sigma, FixedBorderType border_type, | ||
| 374 | SeparableFilterWorkspace *workspace) { | ||
| 375 | using GaussianBlurFilter = GaussianBlur<ScalarType, KernelSize, IsBinomial>; | ||
| 376 | |||
| 377 | 326 | Rows<const ScalarType> src_rows{src, src_stride, channels}; | |
| 378 | 326 | Rows<ScalarType> dst_rows{dst, dst_stride, channels}; | |
| 379 | |||
| 380 | if constexpr (IsBinomial) { | ||
| 381 | 131 | GaussianBlurFilter blur; | |
| 382 | 131 | SeparableFilter<GaussianBlurFilter, KernelSize> filter{blur}; | |
| 383 | 262 | workspace->process(rect, y_begin, y_end, src_rows, dst_rows, channels, | |
| 384 | 131 | border_type, filter); | |
| 385 | |||
| 386 | 131 | return KLEIDICV_OK; | |
| 387 | 131 | } else { | |
| 388 | 195 | constexpr size_t kHalfKernelSize = get_half_kernel_size(KernelSize); | |
| 389 | 195 | uint16_t half_kernel[128]; | |
| 390 | 195 | generate_gaussian_half_kernel(half_kernel, kHalfKernelSize, sigma); | |
| 391 | // If sigma is so small that the middle point gets all the weights, it's | ||
| 392 | // just a copy | ||
| 393 |
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195 | if (half_kernel[kHalfKernelSize - 1] < 256) { |
| 394 | 115 | GaussianBlurFilter blur(half_kernel); | |
| 395 | 115 | SeparableFilter<GaussianBlurFilter, KernelSize> filter{blur}; | |
| 396 | 230 | workspace->process(rect, y_begin, y_end, src_rows, dst_rows, channels, | |
| 397 | 115 | border_type, filter); | |
| 398 | 115 | } else { | |
| 399 |
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836 | for (size_t row = y_begin; row < y_end; ++row) { |
| 400 | 1512 | std::memcpy(static_cast<void *>(&dst_rows.at(row)[0]), | |
| 401 | 756 | static_cast<const void *>(&src_rows.at(row)[0]), | |
| 402 | 756 | rect.width() * sizeof(ScalarType) * dst_rows.channels()); | |
| 403 | 756 | } | |
| 404 | } | ||
| 405 | 195 | return KLEIDICV_OK; | |
| 406 | 195 | } | |
| 407 | 326 | } | |
| 408 | |||
| 409 | template <bool IsBinomial, typename ScalarType> | ||
| 410 | 326 | static kleidicv_error_t gaussian_blur_fixed( | |
| 411 | size_t kernel_size, const ScalarType *src, size_t src_stride, | ||
| 412 | ScalarType *dst, size_t dst_stride, Rectangle &rect, size_t y_begin, | ||
| 413 | size_t y_end, size_t channels, float sigma, FixedBorderType border_type, | ||
| 414 | SeparableFilterWorkspace *workspace) { | ||
| 415 |
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326 | switch (kernel_size) { |
| 416 | case 3: | ||
| 417 | 80 | return gaussian_blur_fixed_kernel_size<3, IsBinomial>( | |
| 418 | 80 | src, src_stride, dst, dst_stride, rect, y_begin, y_end, channels, | |
| 419 | 80 | sigma, border_type, workspace); | |
| 420 | case 5: | ||
| 421 | 84 | return gaussian_blur_fixed_kernel_size<5, IsBinomial>( | |
| 422 | 84 | src, src_stride, dst, dst_stride, rect, y_begin, y_end, channels, | |
| 423 | 84 | sigma, border_type, workspace); | |
| 424 | case 7: | ||
| 425 | 66 | return gaussian_blur_fixed_kernel_size<7, IsBinomial>( | |
| 426 | 66 | src, src_stride, dst, dst_stride, rect, y_begin, y_end, channels, | |
| 427 | 66 | sigma, border_type, workspace); | |
| 428 | case 15: | ||
| 429 | // 15x15 does not have a binomial variant | ||
| 430 | 48 | return gaussian_blur_fixed_kernel_size<15, false>( | |
| 431 | 48 | src, src_stride, dst, dst_stride, rect, y_begin, y_end, channels, | |
| 432 | 48 | sigma, border_type, workspace); | |
| 433 | case 21: | ||
| 434 | // 21x21 does not have a binomial variant | ||
| 435 | 48 | return gaussian_blur_fixed_kernel_size<21, false>( | |
| 436 | 48 | src, src_stride, dst, dst_stride, rect, y_begin, y_end, channels, | |
| 437 | 48 | sigma, border_type, workspace); | |
| 438 | // gaussian_blur_is_implemented checked the kernel size already. | ||
| 439 | // GCOVR_EXCL_START | ||
| 440 | default: | ||
| 441 | assert(!"kernel size not implemented"); | ||
| 442 | − | return KLEIDICV_ERROR_NOT_IMPLEMENTED; | |
| 443 | // GCOVR_EXCL_STOP | ||
| 444 | } | ||
| 445 | 326 | } | |
| 446 | |||
| 447 | KLEIDICV_TARGET_FN_ATTRS | ||
| 448 | 345 | kleidicv_error_t gaussian_blur_fixed_stripe_u8( | |
| 449 | const uint8_t *src, size_t src_stride, uint8_t *dst, size_t dst_stride, | ||
| 450 | size_t width, size_t height, size_t y_begin, size_t y_end, size_t channels, | ||
| 451 | size_t kernel_width, size_t /*kernel_height*/, float sigma_x, | ||
| 452 | float /*sigma_y*/, FixedBorderType fixed_border_type, | ||
| 453 | kleidicv_filter_context_t *context) { | ||
| 454 | 345 | auto *workspace = reinterpret_cast<SeparableFilterWorkspace *>(context); | |
| 455 | 690 | kleidicv_error_t checks_result = gaussian_blur_checks( | |
| 456 | 345 | src, src_stride, dst, dst_stride, width, height, channels, workspace); | |
| 457 | |||
| 458 |
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345 | if (checks_result != KLEIDICV_OK) { |
| 459 | 19 | return checks_result; | |
| 460 | } | ||
| 461 | |||
| 462 | 326 | Rectangle rect{width, height}; | |
| 463 | |||
| 464 |
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326 | if (sigma_x == 0.0) { |
| 465 | 326 | return gaussian_blur_fixed<true>(kernel_width, src, src_stride, dst, | |
| 466 | 163 | dst_stride, rect, y_begin, y_end, channels, | |
| 467 | 163 | sigma_x, fixed_border_type, workspace); | |
| 468 | } | ||
| 469 | |||
| 470 | 326 | return gaussian_blur_fixed<false>(kernel_width, src, src_stride, dst, | |
| 471 | 163 | dst_stride, rect, y_begin, y_end, channels, | |
| 472 | 163 | sigma_x, fixed_border_type, workspace); | |
| 473 | 345 | } | |
| 474 | |||
| 475 | } // namespace kleidicv::neon | ||
| 476 |