/* * 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/NEHOGDetectorKernel.h" #include "arm_compute/core/Error.h" #include "arm_compute/core/HOGInfo.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/IAccessWindow.h" #include "arm_compute/core/Validate.h" #include using namespace arm_compute; NEHOGDetectorKernel::NEHOGDetectorKernel() : _input(nullptr), _detection_windows(), _hog_descriptor(nullptr), _bias(0.0f), _threshold(0.0f), _idx_class(0), _num_bins_per_descriptor_x(0), _num_blocks_per_descriptor_y(0), _block_stride_width(0), _block_stride_height(0), _detection_window_width(0), _detection_window_height(0), _max_num_detection_windows(0), _mutex() { } void NEHOGDetectorKernel::configure(const ITensor *input, const IHOG *hog, IDetectionWindowArray *detection_windows, const Size2D &detection_window_stride, float threshold, uint16_t idx_class) { ARM_COMPUTE_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::F32); ARM_COMPUTE_ERROR_ON(hog == nullptr); ARM_COMPUTE_ERROR_ON(detection_windows == nullptr); ARM_COMPUTE_ERROR_ON((detection_window_stride.width % hog->info()->block_stride().width) != 0); ARM_COMPUTE_ERROR_ON((detection_window_stride.height % hog->info()->block_stride().height) != 0); const Size2D &detection_window_size = hog->info()->detection_window_size(); const Size2D &block_size = hog->info()->block_size(); const Size2D &block_stride = hog->info()->block_stride(); _input = input; _detection_windows = detection_windows; _threshold = threshold; _idx_class = idx_class; _hog_descriptor = hog->descriptor(); _bias = _hog_descriptor[hog->info()->descriptor_size() - 1]; _num_bins_per_descriptor_x = ((detection_window_size.width - block_size.width) / block_stride.width + 1) * input->info()->num_channels(); _num_blocks_per_descriptor_y = (detection_window_size.height - block_size.height) / block_stride.height + 1; _block_stride_width = block_stride.width; _block_stride_height = block_stride.height; _detection_window_width = detection_window_size.width; _detection_window_height = detection_window_size.height; _max_num_detection_windows = detection_windows->max_num_values(); ARM_COMPUTE_ERROR_ON((_num_bins_per_descriptor_x * _num_blocks_per_descriptor_y + 1) != hog->info()->descriptor_size()); // Get the number of blocks along the x and y directions of the input tensor const ValidRegion &valid_region = input->info()->valid_region(); const size_t num_blocks_x = valid_region.shape[0]; const size_t num_blocks_y = valid_region.shape[1]; // Get the number of blocks along the x and y directions of the detection window const size_t num_blocks_per_detection_window_x = detection_window_size.width / block_stride.width; const size_t num_blocks_per_detection_window_y = detection_window_size.height / block_stride.height; const size_t window_step_x = detection_window_stride.width / block_stride.width; const size_t window_step_y = detection_window_stride.height / block_stride.height; // Configure kernel window Window win; win.set(Window::DimX, Window::Dimension(0, floor_to_multiple(num_blocks_x - num_blocks_per_detection_window_x, window_step_x) + window_step_x, window_step_x)); win.set(Window::DimY, Window::Dimension(0, floor_to_multiple(num_blocks_y - num_blocks_per_detection_window_y, window_step_y) + window_step_y, window_step_y)); constexpr unsigned int num_elems_read_per_iteration = 1; const unsigned int num_rows_read_per_iteration = _num_blocks_per_descriptor_y; update_window_and_padding(win, AccessWindowRectangle(input->info(), 0, 0, num_elems_read_per_iteration, num_rows_read_per_iteration)); INEKernel::configure(win); } void NEHOGDetectorKernel::run(const Window &window, const ThreadInfo &info) { ARM_COMPUTE_UNUSED(info); ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); ARM_COMPUTE_ERROR_ON(_hog_descriptor == nullptr); const size_t in_step_y = _input->info()->strides_in_bytes()[Window::DimY] / data_size_from_type(_input->info()->data_type()); Iterator in(_input, window); execute_window_loop(window, [&](const Coordinates & id) { const auto *in_row_ptr = reinterpret_cast(in.ptr()); // Init score_f32 with 0 float32x4_t score_f32 = vdupq_n_f32(0.0f); // Init score with bias float score = _bias; // Compute Linear SVM for(size_t yb = 0; yb < _num_blocks_per_descriptor_y; ++yb, in_row_ptr += in_step_y) { int32_t xb = 0; const int32_t offset_y = yb * _num_bins_per_descriptor_x; for(; xb < static_cast(_num_bins_per_descriptor_x) - 16; xb += 16) { // Load descriptor values const float32x4x4_t a_f32 = { { vld1q_f32(&in_row_ptr[xb + 0]), vld1q_f32(&in_row_ptr[xb + 4]), vld1q_f32(&in_row_ptr[xb + 8]), vld1q_f32(&in_row_ptr[xb + 12]) } }; // Load detector values const float32x4x4_t b_f32 = { { vld1q_f32(&_hog_descriptor[xb + 0 + offset_y]), vld1q_f32(&_hog_descriptor[xb + 4 + offset_y]), vld1q_f32(&_hog_descriptor[xb + 8 + offset_y]), vld1q_f32(&_hog_descriptor[xb + 12 + offset_y]) } }; // Multiply accumulate score_f32 = vmlaq_f32(score_f32, a_f32.val[0], b_f32.val[0]); score_f32 = vmlaq_f32(score_f32, a_f32.val[1], b_f32.val[1]); score_f32 = vmlaq_f32(score_f32, a_f32.val[2], b_f32.val[2]); score_f32 = vmlaq_f32(score_f32, a_f32.val[3], b_f32.val[3]); } for(; xb < static_cast(_num_bins_per_descriptor_x); ++xb) { const float a = in_row_ptr[xb]; const float b = _hog_descriptor[xb + offset_y]; score += a * b; } } score += vgetq_lane_f32(score_f32, 0); score += vgetq_lane_f32(score_f32, 1); score += vgetq_lane_f32(score_f32, 2); score += vgetq_lane_f32(score_f32, 3); if(score > _threshold) { if(_detection_windows->num_values() < _max_num_detection_windows) { DetectionWindow win; win.x = (id.x() * _block_stride_width); win.y = (id.y() * _block_stride_height); win.width = _detection_window_width; win.height = _detection_window_height; win.idx_class = _idx_class; win.score = score; arm_compute::unique_lock lock(_mutex); _detection_windows->push_back(win); lock.unlock(); } } }, in); }