/* * Copyright (c) 2016-2019 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 "arm_compute/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 #include #include #include #include namespace arm_compute { namespace { const uint8x16_t zero_u8 = vdupq_n_u8(0); template 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 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 &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 &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(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(_input->ptr_to_element(Coordinates(-1, -1))); const auto input_mid_ptr = static_cast(_input->ptr_to_element(Coordinates(-1, 0))); const auto input_bot_ptr = static_cast(_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(_input->ptr_to_element(Coordinates(-2, -2))); const auto input_top_ptr = static_cast(_input->ptr_to_element(Coordinates(-2, -1))); const auto input_mid_ptr = static_cast(_input->ptr_to_element(Coordinates(-2, 0))); const auto input_bot_ptr = static_cast(_input->ptr_to_element(Coordinates(-2, 1))); const auto input_bot2_ptr = static_cast(_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 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 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 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 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(rows_min); // Store result as U8 vst1_u8(output.ptr(), out); }, input, output); } template 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 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(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(_input->ptr_to_element(Coordinates(0, -1))); const auto input_mid_ptr = static_cast(_input->ptr_to_element(Coordinates(-1, 0))); const auto input_bot_ptr = static_cast(_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(_input->ptr_to_element(Coordinates(0, -2))); const auto input_top_ptr = static_cast(_input->ptr_to_element(Coordinates(0, -1))); const auto input_mid_ptr = static_cast(_input->ptr_to_element(Coordinates(-2, 0))); const auto input_bot_ptr = static_cast(_input->ptr_to_element(Coordinates(0, 1))); const auto input_bot2_ptr = static_cast(_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 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 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(data); // Get final min out = vmin_u8(out, rows_min); // Store result as U8 vst1_u8(output.ptr(), out); }, input, output); } template 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 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(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(_input->ptr_to_element(Coordinates(-2, -2))); const auto input_top_ptr = static_cast(_input->ptr_to_element(Coordinates(-2, -1))); const auto input_mid_ptr = static_cast(_input->ptr_to_element(Coordinates(-2, 0))); const auto input_bot_ptr = static_cast(_input->ptr_to_element(Coordinates(-2, 1))); const auto input_bot2_ptr = static_cast(_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 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 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(_input->ptr_to_element(Coordinates(-2, -2))); const auto input_top_ptr = static_cast(_input->ptr_to_element(Coordinates(-2, -1))); const auto input_mid_ptr = static_cast(_input->ptr_to_element(Coordinates(-2, 0))); const auto input_bot_ptr = static_cast(_input->ptr_to_element(Coordinates(-2, 1))); const auto input_bot2_ptr = static_cast(_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(_input->ptr_to_element(Coordinates(-2, -2))); const auto input_top_ptr = static_cast(_input->ptr_to_element(Coordinates(-2, -1))); const auto input_mid_ptr = static_cast(_input->ptr_to_element(Coordinates(-2, 0))); const auto input_bot_ptr = static_cast(_input->ptr_to_element(Coordinates(-2, 1))); const auto input_bot2_ptr = static_cast(_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 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 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 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(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 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 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 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 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