| /* |
| * Copyright (c) 2016-2020 Arm Limited. |
| * |
| * SPDX-License-Identifier: MIT |
| * |
| * Permission is hereby granted, free of charge, to any person obtaining a copy |
| * of this software and associated documentation files (the "Software"), to |
| * deal in the Software without restriction, including without limitation the |
| * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| * sell copies of the Software, and to permit persons to whom the Software is |
| * furnished to do so, subject to the following conditions: |
| * |
| * The above copyright notice and this permission notice shall be included in all |
| * copies or substantial portions of the Software. |
| * |
| * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| * SOFTWARE. |
| */ |
| #include "src/core/NEON/kernels/NENonLinearFilterKernel.h" |
| |
| #include "arm_compute/core/Coordinates.h" |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/ITensor.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/Validate.h" |
| #include "src/core/helpers/AutoConfiguration.h" |
| #include "src/core/helpers/WindowHelpers.h" |
| |
| #include <algorithm> |
| #include <arm_neon.h> |
| #include <array> |
| #include <tuple> |
| #include <utility> |
| |
| namespace arm_compute |
| { |
| namespace |
| { |
| const uint8x16_t zero_u8 = vdupq_n_u8(0); |
| |
| template <size_t columns> |
| inline uint8x8_t min_row(uint8x16_t row_data) |
| { |
| uint8x8_t min = vget_low_u8(row_data); |
| |
| for(size_t c = 1; c < columns; ++c) |
| { |
| row_data = vextq_u8(row_data, zero_u8, 1); |
| min = vmin_u8(min, vget_low_u8(row_data)); |
| } |
| |
| return min; |
| } |
| |
| template <size_t columns> |
| inline uint8x8_t max_row(uint8x16_t row_data) |
| { |
| uint8x8_t max = vget_low_u8(row_data); |
| |
| for(size_t c = 1; c < columns; ++c) |
| { |
| row_data = vextq_u8(row_data, zero_u8, 1); |
| max = vmax_u8(max, vget_low_u8(row_data)); |
| } |
| |
| return max; |
| } |
| |
| inline void sort(uint8x8_t &a, uint8x8_t &b) |
| { |
| const uint8x8_t min = vmin_u8(a, b); |
| const uint8x8_t max = vmax_u8(a, b); |
| a = min; |
| b = max; |
| } |
| |
| // Sorting networks below were generated using http://pages.ripco.net/~jgamble/nw.html |
| // Calculations that do not affect the median were removed. |
| inline void sort5(uint8x8_t &p0, uint8x8_t &p1, uint8x8_t &p2, uint8x8_t &p3, uint8x8_t &p4) |
| { |
| sort(p0, p1); |
| sort(p2, p3); |
| sort(p0, p2); |
| sort(p1, p3); |
| sort(p1, p2); |
| sort(p0, p4); |
| sort(p1, p4); |
| sort(p2, p4); |
| } |
| |
| inline void sort9(uint8x8_t &p0, uint8x8_t &p1, uint8x8_t &p2, |
| uint8x8_t &p3, uint8x8_t &p4, uint8x8_t &p5, |
| uint8x8_t &p6, uint8x8_t &p7, uint8x8_t &p8) |
| { |
| sort(p1, p2); |
| sort(p4, p5); |
| sort(p7, p8); |
| sort(p0, p1); |
| sort(p3, p4); |
| sort(p6, p7); |
| sort(p1, p2); |
| sort(p4, p5); |
| sort(p7, p8); |
| sort(p0, p3); |
| sort(p5, p8); |
| sort(p4, p7); |
| sort(p3, p6); |
| sort(p1, p4); |
| sort(p2, p5); |
| sort(p4, p7); |
| sort(p4, p2); |
| sort(p6, p4); |
| sort(p4, p2); |
| } |
| |
| inline void sort21(std::array<uint8x8_t, 21> &p) |
| { |
| sort(p[0], p[1]); |
| sort(p[2], p[3]); |
| sort(p[4], p[5]); |
| sort(p[6], p[7]); |
| sort(p[8], p[9]); |
| sort(p[10], p[11]); |
| sort(p[12], p[13]); |
| sort(p[14], p[15]); |
| sort(p[16], p[17]); |
| sort(p[18], p[19]); |
| sort(p[0], p[2]); |
| sort(p[1], p[3]); |
| sort(p[4], p[6]); |
| sort(p[5], p[7]); |
| sort(p[8], p[10]); |
| sort(p[9], p[11]); |
| sort(p[12], p[14]); |
| sort(p[13], p[15]); |
| sort(p[16], p[18]); |
| sort(p[17], p[19]); |
| sort(p[1], p[2]); |
| sort(p[5], p[6]); |
| sort(p[0], p[4]); |
| sort(p[3], p[7]); |
| sort(p[9], p[10]); |
| sort(p[13], p[14]); |
| sort(p[8], p[12]); |
| sort(p[11], p[15]); |
| sort(p[17], p[18]); |
| sort(p[16], p[20]); |
| sort(p[1], p[5]); |
| sort(p[2], p[6]); |
| sort(p[9], p[13]); |
| sort(p[10], p[14]); |
| sort(p[0], p[8]); |
| sort(p[7], p[15]); |
| sort(p[17], p[20]); |
| sort(p[1], p[4]); |
| sort(p[3], p[6]); |
| sort(p[9], p[12]); |
| sort(p[11], p[14]); |
| sort(p[18], p[20]); |
| sort(p[0], p[16]); |
| sort(p[2], p[4]); |
| sort(p[3], p[5]); |
| sort(p[10], p[12]); |
| sort(p[11], p[13]); |
| sort(p[1], p[9]); |
| sort(p[6], p[14]); |
| sort(p[19], p[20]); |
| sort(p[3], p[4]); |
| sort(p[11], p[12]); |
| sort(p[1], p[8]); |
| sort(p[2], p[10]); |
| sort(p[5], p[13]); |
| sort(p[7], p[14]); |
| sort(p[3], p[11]); |
| sort(p[2], p[8]); |
| sort(p[4], p[12]); |
| sort(p[7], p[13]); |
| sort(p[1], p[17]); |
| sort(p[3], p[10]); |
| sort(p[5], p[12]); |
| sort(p[1], p[16]); |
| sort(p[2], p[18]); |
| sort(p[3], p[9]); |
| sort(p[6], p[12]); |
| sort(p[2], p[16]); |
| sort(p[3], p[8]); |
| sort(p[7], p[12]); |
| sort(p[5], p[9]); |
| sort(p[6], p[10]); |
| sort(p[4], p[8]); |
| sort(p[7], p[11]); |
| sort(p[3], p[19]); |
| sort(p[5], p[8]); |
| sort(p[7], p[10]); |
| sort(p[3], p[18]); |
| sort(p[4], p[20]); |
| sort(p[6], p[8]); |
| sort(p[7], p[9]); |
| sort(p[3], p[17]); |
| sort(p[5], p[20]); |
| sort(p[7], p[8]); |
| sort(p[3], p[16]); |
| sort(p[6], p[20]); |
| sort(p[5], p[17]); |
| sort(p[7], p[20]); |
| sort(p[4], p[16]); |
| sort(p[6], p[18]); |
| sort(p[5], p[16]); |
| sort(p[7], p[19]); |
| sort(p[7], p[18]); |
| sort(p[6], p[16]); |
| sort(p[7], p[17]); |
| sort(p[10], p[18]); |
| sort(p[7], p[16]); |
| sort(p[9], p[17]); |
| sort(p[8], p[16]); |
| sort(p[9], p[16]); |
| sort(p[10], p[16]); |
| } |
| |
| inline void sort25(std::array<uint8x8_t, 25> &p) |
| { |
| sort(p[1], p[2]); |
| sort(p[0], p[1]); |
| sort(p[1], p[2]); |
| sort(p[4], p[5]); |
| sort(p[3], p[4]); |
| sort(p[4], p[5]); |
| sort(p[0], p[3]); |
| sort(p[2], p[5]); |
| sort(p[2], p[3]); |
| sort(p[1], p[4]); |
| sort(p[1], p[2]); |
| sort(p[3], p[4]); |
| sort(p[7], p[8]); |
| sort(p[6], p[7]); |
| sort(p[7], p[8]); |
| sort(p[10], p[11]); |
| sort(p[9], p[10]); |
| sort(p[10], p[11]); |
| sort(p[6], p[9]); |
| sort(p[8], p[11]); |
| sort(p[8], p[9]); |
| sort(p[7], p[10]); |
| sort(p[7], p[8]); |
| sort(p[9], p[10]); |
| sort(p[0], p[6]); |
| sort(p[4], p[10]); |
| sort(p[4], p[6]); |
| sort(p[2], p[8]); |
| sort(p[2], p[4]); |
| sort(p[6], p[8]); |
| sort(p[1], p[7]); |
| sort(p[5], p[11]); |
| sort(p[5], p[7]); |
| sort(p[3], p[9]); |
| sort(p[3], p[5]); |
| sort(p[7], p[9]); |
| sort(p[1], p[2]); |
| sort(p[3], p[4]); |
| sort(p[5], p[6]); |
| sort(p[7], p[8]); |
| sort(p[9], p[10]); |
| sort(p[13], p[14]); |
| sort(p[12], p[13]); |
| sort(p[13], p[14]); |
| sort(p[16], p[17]); |
| sort(p[15], p[16]); |
| sort(p[16], p[17]); |
| sort(p[12], p[15]); |
| sort(p[14], p[17]); |
| sort(p[14], p[15]); |
| sort(p[13], p[16]); |
| sort(p[13], p[14]); |
| sort(p[15], p[16]); |
| sort(p[19], p[20]); |
| sort(p[18], p[19]); |
| sort(p[19], p[20]); |
| sort(p[21], p[22]); |
| sort(p[23], p[24]); |
| sort(p[21], p[23]); |
| sort(p[22], p[24]); |
| sort(p[22], p[23]); |
| sort(p[18], p[21]); |
| sort(p[20], p[23]); |
| sort(p[20], p[21]); |
| sort(p[19], p[22]); |
| sort(p[22], p[24]); |
| sort(p[19], p[20]); |
| sort(p[21], p[22]); |
| sort(p[23], p[24]); |
| sort(p[12], p[18]); |
| sort(p[16], p[22]); |
| sort(p[16], p[18]); |
| sort(p[14], p[20]); |
| sort(p[20], p[24]); |
| sort(p[14], p[16]); |
| sort(p[18], p[20]); |
| sort(p[22], p[24]); |
| sort(p[13], p[19]); |
| sort(p[17], p[23]); |
| sort(p[17], p[19]); |
| sort(p[15], p[21]); |
| sort(p[15], p[17]); |
| sort(p[19], p[21]); |
| sort(p[13], p[14]); |
| sort(p[15], p[16]); |
| sort(p[17], p[18]); |
| sort(p[19], p[20]); |
| sort(p[21], p[22]); |
| sort(p[23], p[24]); |
| sort(p[0], p[12]); |
| sort(p[8], p[20]); |
| sort(p[8], p[12]); |
| sort(p[4], p[16]); |
| sort(p[16], p[24]); |
| sort(p[12], p[16]); |
| sort(p[2], p[14]); |
| sort(p[10], p[22]); |
| sort(p[10], p[14]); |
| sort(p[6], p[18]); |
| sort(p[6], p[10]); |
| sort(p[10], p[12]); |
| sort(p[1], p[13]); |
| sort(p[9], p[21]); |
| sort(p[9], p[13]); |
| sort(p[5], p[17]); |
| sort(p[13], p[17]); |
| sort(p[3], p[15]); |
| sort(p[11], p[23]); |
| sort(p[11], p[15]); |
| sort(p[7], p[19]); |
| sort(p[7], p[11]); |
| sort(p[11], p[13]); |
| sort(p[11], p[12]); |
| } |
| } // namespace |
| |
| NENonLinearFilterKernel::NENonLinearFilterKernel() |
| : _border_width(0), _input(nullptr), _output(nullptr), _mask(nullptr), _pattern(MatrixPattern::BOX), _function(NonLinearFilterFunction::MIN), _func_idx(0), _border_size() |
| { |
| } |
| |
| BorderSize NENonLinearFilterKernel::border_size() const |
| { |
| return _border_size; |
| } |
| |
| void NENonLinearFilterKernel::configure(const ITensor *input, ITensor *output, NonLinearFilterFunction function, unsigned int mask_size, MatrixPattern pattern, const uint8_t *mask, |
| bool border_undefined) |
| { |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8); |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8); |
| ARM_COMPUTE_ERROR_ON(3 != mask_size && 5 != mask_size); |
| ARM_COMPUTE_ERROR_ON(MatrixPattern::OTHER == pattern && nullptr == mask); |
| |
| // Set class variables |
| _border_size = BorderSize(mask_size / 2); |
| _input = input; |
| _output = output; |
| _mask = mask; |
| _pattern = pattern; |
| _function = function; |
| |
| // Configure kernel window |
| const unsigned int num_elems_processed_per_iteration = (MatrixPattern::OTHER == pattern) ? 1 : 8; |
| constexpr unsigned int num_elems_read_per_iteration = 16; |
| |
| Window win = calculate_max_window(*input->info(), num_elems_processed_per_iteration, border_undefined, border_size()); |
| AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration); |
| update_window_and_padding(win, |
| AccessWindowRectangle(input->info(), -border_size().left, -border_size().top, num_elems_read_per_iteration, mask_size), |
| output_access); |
| output_access.set_valid_region(win, input->info()->valid_region(), border_undefined, border_size()); |
| |
| INEKernel::configure(win); |
| |
| // Define function index |
| _func_idx = (3 == mask_size) ? 0 : 1; |
| |
| if(MatrixPattern::OTHER != pattern) |
| { |
| _func_idx = (_func_idx) * 3 + static_cast<unsigned int>(function); |
| } |
| } |
| |
| void NENonLinearFilterKernel::fill_mask(uint8_t *mask, int cols, int rows, MatrixPattern pattern) |
| { |
| unsigned int v = 0; |
| |
| for(int r = 0; r < rows; ++r) |
| { |
| for(int c = 0; c < cols; ++c, ++v) |
| { |
| uint8_t val = 0; |
| |
| switch(pattern) |
| { |
| case MatrixPattern::BOX: |
| val = 255; |
| break; |
| case MatrixPattern::CROSS: |
| val = ((r == (rows / 2)) || (c == (cols / 2))) ? 255 : 0; |
| break; |
| case MatrixPattern::DISK: |
| val = (((r - rows / 2.0f + 0.5f) * (r - rows / 2.0f + 0.5f)) / ((rows / 2.0f) * (rows / 2.0f)) + ((c - cols / 2.0f + 0.5f) * (c - cols / 2.0f + 0.5f)) / ((cols / 2.0f) * |
| (cols / 2.0f))) <= 1.0f ? 255 : 0; |
| break; |
| default: |
| return; |
| } |
| |
| mask[v] = val; |
| } |
| } |
| } |
| |
| template <> |
| void NENonLinearFilterKernel::median_filter_box<3, 3>(const Window &win) |
| { |
| Iterator input(_input, win); |
| Iterator output(_output, win); |
| |
| const auto input_top_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-1, -1))); |
| const auto input_mid_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-1, 0))); |
| const auto input_bot_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-1, 1))); |
| |
| execute_window_loop(win, [&](const Coordinates &) |
| { |
| const uint8x16_t top_data = vld1q_u8(input_top_ptr + input.offset()); |
| const uint8x16_t mid_data = vld1q_u8(input_mid_ptr + input.offset()); |
| const uint8x16_t bot_data = vld1q_u8(input_bot_ptr + input.offset()); |
| |
| uint8x8_t p0 = vget_low_u8(top_data); |
| uint8x8_t p1 = vext_u8(vget_low_u8(top_data), vget_high_u8(top_data), 1); |
| uint8x8_t p2 = vext_u8(vget_low_u8(top_data), vget_high_u8(top_data), 2); |
| uint8x8_t p3 = vget_low_u8(mid_data); |
| uint8x8_t p4 = vext_u8(vget_low_u8(mid_data), vget_high_u8(mid_data), 1); |
| uint8x8_t p5 = vext_u8(vget_low_u8(mid_data), vget_high_u8(mid_data), 2); |
| uint8x8_t p6 = vget_low_u8(bot_data); |
| uint8x8_t p7 = vext_u8(vget_low_u8(bot_data), vget_high_u8(bot_data), 1); |
| uint8x8_t p8 = vext_u8(vget_low_u8(bot_data), vget_high_u8(bot_data), 2); |
| |
| sort9(p0, p1, p2, p3, p4, p5, p6, p7, p8); |
| |
| vst1_u8(output.ptr(), p4); |
| }, |
| input, output); |
| } |
| template <> |
| void NENonLinearFilterKernel::median_filter_box<5, 5>(const Window &win) |
| { |
| Iterator input(_input, win); |
| Iterator output(_output, win); |
| |
| const auto input_top2_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, -2))); |
| const auto input_top_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, -1))); |
| const auto input_mid_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, 0))); |
| const auto input_bot_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, 1))); |
| const auto input_bot2_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, 2))); |
| |
| execute_window_loop(win, [&](const Coordinates &) |
| { |
| const uint8x16_t top2_data = vld1q_u8(input_top2_ptr + input.offset()); |
| const uint8x16_t top_data = vld1q_u8(input_top_ptr + input.offset()); |
| const uint8x16_t mid_data = vld1q_u8(input_mid_ptr + input.offset()); |
| const uint8x16_t bot_data = vld1q_u8(input_bot_ptr + input.offset()); |
| const uint8x16_t bot2_data = vld1q_u8(input_bot2_ptr + input.offset()); |
| |
| const std::array<uint8x8_t, 10> d = |
| { |
| vget_low_u8(top2_data), |
| vget_high_u8(top2_data), |
| vget_low_u8(top_data), |
| vget_high_u8(top_data), |
| vget_low_u8(mid_data), |
| vget_high_u8(mid_data), |
| vget_low_u8(bot_data), |
| vget_high_u8(bot_data), |
| vget_low_u8(bot2_data), |
| vget_high_u8(bot2_data) |
| }; |
| |
| std::array<uint8x8_t, 25> p{ 0 }; |
| for(unsigned int i = 0; i < 5; ++i) |
| { |
| const unsigned int idx_d = i * 2; |
| const unsigned int idx_p = i * 5; |
| |
| p[idx_p] = d[idx_d]; |
| p[idx_p + 1] = vext_u8(d[idx_d], d[idx_d + 1], 1); |
| p[idx_p + 2] = vext_u8(d[idx_d], d[idx_d + 1], 2); |
| p[idx_p + 3] = vext_u8(d[idx_d], d[idx_d + 1], 3); |
| p[idx_p + 4] = vext_u8(d[idx_d], d[idx_d + 1], 4); |
| } |
| |
| sort25(p); |
| |
| vst1_u8(output.ptr(), p[12]); |
| }, |
| input, output); |
| } |
| |
| template <int mask_w, int mask_h> |
| void NENonLinearFilterKernel::min_filter_box(const Window &win) |
| { |
| static_assert(mask_w > 0, "Mask size must not be 0"); |
| static_assert(mask_h > 0, "Mask size must not be 0"); |
| |
| Iterator input(_input, win); |
| Iterator output(_output, win); |
| |
| const int k_row_half = mask_h / 2; |
| const int k_col_half = mask_w / 2; |
| |
| // Set row pointers |
| std::array<const unsigned char *, mask_h> input_ptrs{ {} }; |
| for(int i = -k_row_half; i <= k_row_half; ++i) |
| { |
| input_ptrs[k_row_half + i] = _input->buffer() + _input->info()->offset_element_in_bytes(Coordinates(-k_col_half, i)); |
| } |
| |
| execute_window_loop(win, [&](const Coordinates &) |
| { |
| // Get min of rows |
| uint8x16_t rows_min = vld1q_u8(input_ptrs[0] + input.offset()); |
| |
| for(unsigned int r = 1; r < mask_h; ++r) |
| { |
| const uint8x16_t data = vld1q_u8(input_ptrs[r] + input.offset()); |
| rows_min = vminq_u8(rows_min, data); |
| } |
| |
| const uint8x8_t out = min_row<mask_w>(rows_min); |
| |
| // Store result as U8 |
| vst1_u8(output.ptr(), out); |
| }, |
| input, output); |
| } |
| |
| template <int mask_w, int mask_h> |
| void NENonLinearFilterKernel::max_filter_box(const Window &win) |
| { |
| static_assert(mask_w > 0, "Mask size must not be 0"); |
| static_assert(mask_h > 0, "Mask size must not be 0"); |
| ARM_COMPUTE_ERROR_ON(_input->buffer() == nullptr); |
| |
| Iterator input(_input, win); |
| Iterator output(_output, win); |
| |
| const int k_row_half = mask_h / 2; |
| const int k_col_half = mask_w / 2; |
| |
| // Set row pointers |
| std::array<const unsigned char *, mask_h> input_ptrs{ {} }; |
| for(int i = -k_row_half; i <= k_row_half; ++i) |
| { |
| input_ptrs[k_row_half + i] = _input->buffer() + _input->info()->offset_element_in_bytes(Coordinates(-k_col_half, i)); |
| } |
| |
| execute_window_loop(win, [&](const Coordinates &) |
| { |
| uint8x16_t rows_max = vld1q_u8(input_ptrs[0] + input.offset()); |
| |
| // Get max of rows |
| for(unsigned int r = 1; r < mask_h; ++r) |
| { |
| const uint8x16_t data = vld1q_u8(input_ptrs[r] + input.offset()); |
| rows_max = vmaxq_u8(rows_max, data); |
| } |
| |
| // Get max of columns |
| const uint8x8_t out = max_row<mask_w>(rows_max); |
| |
| // Store result as U8 |
| vst1_u8(output.ptr(), out); |
| }, |
| input, output); |
| } |
| |
| template <> |
| void NENonLinearFilterKernel::median_filter_cross<3, 3>(const Window &win) |
| { |
| Iterator input(_input, win); |
| Iterator output(_output, win); |
| |
| const auto input_top_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(0, -1))); |
| const auto input_mid_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-1, 0))); |
| const auto input_bot_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(0, 1))); |
| |
| execute_window_loop(win, [&](const Coordinates &) |
| { |
| const uint8x8_t top_data = vld1_u8(input_top_ptr + input.offset()); |
| const uint8x16_t mid_data = vld1q_u8(input_mid_ptr + input.offset()); |
| const uint8x8_t bot_data = vld1_u8(input_bot_ptr + input.offset()); |
| |
| uint8x8_t p0 = top_data; |
| uint8x8_t p1 = vget_low_u8(mid_data); |
| uint8x8_t p2 = vext_u8(vget_low_u8(mid_data), vget_high_u8(mid_data), 1); |
| uint8x8_t p3 = vext_u8(vget_low_u8(mid_data), vget_high_u8(mid_data), 2); |
| uint8x8_t p4 = bot_data; |
| |
| sort5(p0, p1, p2, p3, p4); |
| |
| vst1_u8(output.ptr(), p2); |
| }, |
| input, output); |
| } |
| |
| template <> |
| void NENonLinearFilterKernel::median_filter_cross<5, 5>(const Window &win) |
| { |
| Iterator input(_input, win); |
| Iterator output(_output, win); |
| |
| const auto input_top2_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(0, -2))); |
| const auto input_top_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(0, -1))); |
| const auto input_mid_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, 0))); |
| const auto input_bot_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(0, 1))); |
| const auto input_bot2_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(0, 2))); |
| |
| execute_window_loop(win, [&](const Coordinates &) |
| { |
| const uint8x8_t top2_data = vld1_u8(input_top2_ptr + input.offset()); |
| const uint8x8_t top_data = vld1_u8(input_top_ptr + input.offset()); |
| const uint8x16_t mid_data = vld1q_u8(input_mid_ptr + input.offset()); |
| const uint8x8_t bot_data = vld1_u8(input_bot_ptr + input.offset()); |
| const uint8x8_t bot2_data = vld1_u8(input_bot2_ptr + input.offset()); |
| |
| uint8x8_t p0 = top2_data; |
| uint8x8_t p1 = top_data; |
| uint8x8_t p2 = vget_low_u8(mid_data); |
| uint8x8_t p3 = vext_u8(vget_low_u8(mid_data), vget_high_u8(mid_data), 1); |
| uint8x8_t p4 = vext_u8(vget_low_u8(mid_data), vget_high_u8(mid_data), 2); |
| uint8x8_t p5 = vext_u8(vget_low_u8(mid_data), vget_high_u8(mid_data), 3); |
| uint8x8_t p6 = vext_u8(vget_low_u8(mid_data), vget_high_u8(mid_data), 4); |
| uint8x8_t p7 = bot_data; |
| uint8x8_t p8 = bot2_data; |
| |
| sort9(p0, p1, p2, p3, p4, p5, p6, p7, p8); |
| |
| vst1_u8(output.ptr(), p4); |
| }, |
| input, output); |
| } |
| |
| template <int mask_w, int mask_h> |
| void NENonLinearFilterKernel::min_filter_cross(const Window &win) |
| { |
| static_assert(mask_w > 0, "Mask size must not be 0"); |
| static_assert(mask_h > 0, "Mask size must not be 0"); |
| ARM_COMPUTE_ERROR_ON(_input->buffer() == nullptr); |
| |
| Iterator input(_input, win); |
| Iterator output(_output, win); |
| |
| const int k_row_half = mask_h / 2; |
| const int k_col_half = mask_w / 2; |
| |
| const unsigned char *mid_ptr = _input->buffer() + _input->info()->offset_element_in_bytes(Coordinates(-k_col_half, 0)); |
| |
| // Set row pointers |
| std::array<const unsigned char *, mask_h> input_ptrs{ {} }; |
| for(int i = -k_row_half; i <= k_row_half; ++i) |
| { |
| input_ptrs[k_row_half + i] = _input->buffer() + _input->info()->offset_element_in_bytes(Coordinates(0, i)); |
| } |
| |
| execute_window_loop(win, [&](const Coordinates &) |
| { |
| uint8x8_t rows_min = vld1_u8(input_ptrs[0] + input.offset()); |
| |
| // Get min of rows |
| for(unsigned int r = 1; r < mask_h; ++r) |
| { |
| const uint8x8_t data = vld1_u8(input_ptrs[r] + input.offset()); |
| rows_min = vmin_u8(rows_min, data); |
| } |
| |
| // Get min of middle row |
| const uint8x16_t data = vld1q_u8(mid_ptr + input.offset()); |
| uint8x8_t out = min_row<mask_w>(data); |
| |
| // Get final min |
| out = vmin_u8(out, rows_min); |
| |
| // Store result as U8 |
| vst1_u8(output.ptr(), out); |
| }, |
| input, output); |
| } |
| |
| template <int mask_w, int mask_h> |
| void NENonLinearFilterKernel::max_filter_cross(const Window &win) |
| { |
| static_assert(mask_w > 0, "Mask size must not be 0"); |
| static_assert(mask_h > 0, "Mask size must not be 0"); |
| ARM_COMPUTE_ERROR_ON(_input->buffer() == nullptr); |
| |
| Iterator input(_input, win); |
| Iterator output(_output, win); |
| |
| const int k_row_half = mask_h / 2; |
| const int k_col_half = mask_w / 2; |
| |
| const unsigned char *mid_ptr = _input->buffer() + _input->info()->offset_element_in_bytes(Coordinates(-k_col_half, 0)); |
| |
| // Set row pointers |
| std::array<unsigned char *, mask_h> input_ptrs{ {} }; |
| for(int i = -k_row_half; i <= k_row_half; ++i) |
| { |
| input_ptrs[k_row_half + i] = _input->buffer() + _input->info()->offset_element_in_bytes(Coordinates(0, i)); |
| } |
| |
| execute_window_loop(win, [&](const Coordinates &) |
| { |
| uint8x8_t rows_max = vld1_u8(input_ptrs[0] + input.offset()); |
| |
| // Get max of rows |
| for(unsigned int r = 1; r < mask_h; ++r) |
| { |
| const uint8x8_t data = vld1_u8(input_ptrs[r] + input.offset()); |
| rows_max = vmax_u8(rows_max, data); |
| } |
| |
| // Get max of middle row |
| const uint8x16_t data = vld1q_u8(mid_ptr + input.offset()); |
| uint8x8_t out = max_row<mask_w>(data); |
| |
| // Get final max |
| out = vmax_u8(out, rows_max); |
| |
| // Store result as U8 |
| vst1_u8(output.ptr(), out); |
| }, |
| input, output); |
| } |
| |
| template <> |
| void NENonLinearFilterKernel::median_filter_disk<5, 5>(const Window &win) |
| { |
| Iterator input(_input, win); |
| Iterator output(_output, win); |
| |
| static const uint8x16_t zero = vdupq_n_u8(0); |
| const auto input_top2_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, -2))); |
| const auto input_top_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, -1))); |
| const auto input_mid_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, 0))); |
| const auto input_bot_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, 1))); |
| const auto input_bot2_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, 2))); |
| |
| execute_window_loop(win, [&](const Coordinates &) |
| { |
| const uint8x16_t top2_data = vextq_u8(vld1q_u8(input_top2_ptr + input.offset()), zero, 1); |
| const uint8x16_t top_data = vld1q_u8(input_top_ptr + input.offset()); |
| const uint8x16_t mid_data = vld1q_u8(input_mid_ptr + input.offset()); |
| const uint8x16_t bot_data = vld1q_u8(input_bot_ptr + input.offset()); |
| const uint8x16_t bot2_data = vextq_u8(vld1q_u8(input_bot2_ptr + input.offset()), zero, 1); |
| |
| std::array<uint8x8_t, 10> d = |
| { |
| vget_low_u8(top2_data), |
| vget_high_u8(top2_data), |
| vget_low_u8(top_data), |
| vget_high_u8(top_data), |
| vget_low_u8(mid_data), |
| vget_high_u8(mid_data), |
| vget_low_u8(bot_data), |
| vget_high_u8(bot_data), |
| vget_low_u8(bot2_data), |
| vget_high_u8(bot2_data) |
| }; |
| |
| std::array<uint8x8_t, 21> p{ 0 }; |
| p[0] = d[0]; |
| p[1] = vext_u8(d[0], d[1], 1); |
| p[2] = vext_u8(d[0], d[1], 2); |
| p[18] = d[8]; |
| p[19] = vext_u8(d[8], d[9], 1); |
| p[20] = vext_u8(d[8], d[9], 2); |
| |
| for(unsigned int i = 0; i < 3; ++i) |
| { |
| const unsigned int idx_d = 2 + i * 2; |
| const unsigned int idx_p = 3 + i * 5; |
| |
| p[idx_p] = d[idx_d]; |
| p[idx_p + 1] = vext_u8(d[idx_d], d[idx_d + 1], 1); |
| p[idx_p + 2] = vext_u8(d[idx_d], d[idx_d + 1], 2); |
| p[idx_p + 3] = vext_u8(d[idx_d], d[idx_d + 1], 3); |
| p[idx_p + 4] = vext_u8(d[idx_d], d[idx_d + 1], 4); |
| } |
| |
| sort21(p); |
| |
| vst1_u8(output.ptr(), p[10]); |
| }, |
| input, output); |
| } |
| |
| template <> |
| void NENonLinearFilterKernel::min_filter_disk<5, 5>(const Window &win) |
| { |
| Iterator input(_input, win); |
| Iterator output(_output, win); |
| |
| static const uint8x16_t zero = vdupq_n_u8(0); |
| const auto input_top2_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, -2))); |
| const auto input_top_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, -1))); |
| const auto input_mid_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, 0))); |
| const auto input_bot_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, 1))); |
| const auto input_bot2_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, 2))); |
| |
| execute_window_loop(win, [&](const Coordinates &) |
| { |
| const uint8x16_t top2_data = vextq_u8(vld1q_u8(input_top2_ptr + input.offset()), zero, 1); |
| const uint8x16_t top_data = vld1q_u8(input_top_ptr + input.offset()); |
| const uint8x16_t mid_data = vld1q_u8(input_mid_ptr + input.offset()); |
| const uint8x16_t bot_data = vld1q_u8(input_bot_ptr + input.offset()); |
| const uint8x16_t bot2_data = vextq_u8(vld1q_u8(input_bot2_ptr + input.offset()), zero, 1); |
| |
| const uint8x16_t rows_min_3 = vminq_u8(top2_data, bot2_data); |
| uint8x16_t rows_min_5 = vminq_u8(top_data, bot_data); |
| rows_min_5 = vminq_u8(rows_min_5, mid_data); |
| |
| const uint8x8_t out_3 = min_row<3>(rows_min_3); |
| const uint8x8_t out_5 = min_row<5>(rows_min_5); |
| |
| vst1_u8(output.ptr(), vmin_u8(out_3, out_5)); |
| }, |
| input, output); |
| } |
| |
| template <> |
| void NENonLinearFilterKernel::max_filter_disk<5, 5>(const Window &win) |
| { |
| Iterator input(_input, win); |
| Iterator output(_output, win); |
| |
| static const uint8x16_t zero = vdupq_n_u8(0); |
| const auto input_top2_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, -2))); |
| const auto input_top_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, -1))); |
| const auto input_mid_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, 0))); |
| const auto input_bot_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, 1))); |
| const auto input_bot2_ptr = static_cast<const unsigned char *>(_input->ptr_to_element(Coordinates(-2, 2))); |
| |
| execute_window_loop(win, [&](const Coordinates &) |
| { |
| const uint8x16_t top2_data = vextq_u8(vld1q_u8(input_top2_ptr + input.offset()), zero, 1); |
| const uint8x16_t top_data = vld1q_u8(input_top_ptr + input.offset()); |
| const uint8x16_t mid_data = vld1q_u8(input_mid_ptr + input.offset()); |
| const uint8x16_t bot_data = vld1q_u8(input_bot_ptr + input.offset()); |
| const uint8x16_t bot2_data = vextq_u8(vld1q_u8(input_bot2_ptr + input.offset()), zero, 1); |
| |
| const uint8x16_t rows_max_3 = vmaxq_u8(top2_data, bot2_data); |
| uint8x16_t rows_max_5 = vmaxq_u8(top_data, bot_data); |
| rows_max_5 = vmaxq_u8(rows_max_5, mid_data); |
| |
| const uint8x8_t out_3 = max_row<3>(rows_max_3); |
| const uint8x8_t out_5 = max_row<5>(rows_max_5); |
| |
| vst1_u8(output.ptr(), vmax_u8(out_3, out_5)); |
| }, |
| input, output); |
| } |
| |
| template <int mask_w, int mask_h> |
| void NENonLinearFilterKernel::non_linear_filter_generic(const Window &win) |
| { |
| Iterator input(_input, win); |
| Iterator output(_output, win); |
| ARM_COMPUTE_ERROR_ON(_input->buffer() == nullptr); |
| |
| const int k_row_half = mask_h / 2; |
| const int k_col_half = mask_w / 2; |
| constexpr int mask_size = mask_w * mask_h; |
| |
| // Set row pointers |
| std::array<unsigned char *, mask_h> input_ptrs{ {} }; |
| for(int i = -k_row_half; i <= k_row_half; ++i) |
| { |
| input_ptrs[k_row_half + i] = _input->buffer() + _input->info()->offset_element_in_bytes(Coordinates(-k_col_half, i)); |
| } |
| |
| std::array<uint8_t, mask_size> vals{ {} }; |
| |
| execute_window_loop(win, [&](const Coordinates &) |
| { |
| // Clear array |
| std::fill(std::begin(vals), std::end(vals), 0); |
| |
| size_t v = 0; |
| size_t m = 0; |
| |
| for(unsigned int r = 0; r < mask_h; ++r) |
| { |
| const auto in_ptr = static_cast<const uint8_t *>(input_ptrs[r] + input.offset()); |
| |
| for(unsigned int c = 0; c < mask_w; ++c, ++m) |
| { |
| if(_mask[m] == 255) |
| { |
| vals[v] = in_ptr[c]; |
| ++v; |
| } |
| } |
| } |
| |
| // Only do something if there is at least one non-zero element in the |
| // mask |
| if(v > 0) |
| { |
| std::sort(vals.begin(), vals.begin() + v); |
| |
| switch(_function) |
| { |
| case NonLinearFilterFunction::MIN: |
| *output.ptr() = vals[0]; |
| break; |
| case NonLinearFilterFunction::MAX: |
| *output.ptr() = vals[v - 1]; |
| break; |
| case NonLinearFilterFunction::MEDIAN: |
| *output.ptr() = vals[v / 2]; |
| break; |
| default: |
| break; |
| } |
| } |
| }, |
| input, output); |
| } |
| |
| void NENonLinearFilterKernel::run(const Window &window, const ThreadInfo &info) |
| { |
| ARM_COMPUTE_UNUSED(info); |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); |
| |
| using NonLinearFilterFunction = void (NENonLinearFilterKernel::*)(const Window & window); |
| |
| // Function table for BOX pattern |
| static const std::array<NonLinearFilterFunction, 6> func_table_box = |
| { |
| { |
| &NENonLinearFilterKernel::median_filter_box<3, 3>, |
| &NENonLinearFilterKernel::min_filter_box<3, 3>, |
| &NENonLinearFilterKernel::max_filter_box<3, 3>, |
| &NENonLinearFilterKernel::median_filter_box<5, 5>, |
| &NENonLinearFilterKernel::min_filter_box<5, 5>, |
| &NENonLinearFilterKernel::max_filter_box<5, 5>, |
| } |
| }; |
| |
| // Function table for CROSS pattern |
| static const std::array<NonLinearFilterFunction, 6> func_table_cross = |
| { |
| { |
| &NENonLinearFilterKernel::median_filter_cross<3, 3>, |
| &NENonLinearFilterKernel::min_filter_cross<3, 3>, |
| &NENonLinearFilterKernel::max_filter_cross<3, 3>, |
| &NENonLinearFilterKernel::median_filter_cross<5, 5>, |
| &NENonLinearFilterKernel::min_filter_cross<5, 5>, |
| &NENonLinearFilterKernel::max_filter_cross<5, 5>, |
| } |
| }; |
| |
| // Function table for DISK pattern |
| static const std::array<NonLinearFilterFunction, 6> func_table_disk = |
| { |
| { |
| &NENonLinearFilterKernel::median_filter_box<3, 3>, |
| &NENonLinearFilterKernel::min_filter_box<3, 3>, |
| &NENonLinearFilterKernel::max_filter_box<3, 3>, |
| &NENonLinearFilterKernel::median_filter_disk<5, 5>, |
| &NENonLinearFilterKernel::min_filter_disk<5, 5>, |
| &NENonLinearFilterKernel::max_filter_disk<5, 5>, |
| } |
| }; |
| |
| // Function table for OTHER pattern |
| static const std::array<NonLinearFilterFunction, 2> func_table_generic = |
| { |
| { |
| &NENonLinearFilterKernel::non_linear_filter_generic<3, 3>, |
| &NENonLinearFilterKernel::non_linear_filter_generic<5, 5>, |
| } |
| }; |
| |
| switch(_pattern) |
| { |
| case MatrixPattern::BOX: |
| ARM_COMPUTE_ERROR_ON(_func_idx >= func_table_box.size()); |
| (this->*func_table_box[_func_idx])(window); |
| break; |
| case MatrixPattern::CROSS: |
| ARM_COMPUTE_ERROR_ON(_func_idx >= func_table_cross.size()); |
| (this->*func_table_cross[_func_idx])(window); |
| break; |
| case MatrixPattern::DISK: |
| ARM_COMPUTE_ERROR_ON(_func_idx >= func_table_disk.size()); |
| (this->*func_table_disk[_func_idx])(window); |
| break; |
| case MatrixPattern::OTHER: |
| default: |
| ARM_COMPUTE_ERROR_ON(_func_idx >= func_table_generic.size()); |
| (this->*func_table_generic[_func_idx])(window); |
| break; |
| } |
| } |
| } // namespace arm_compute |