diff options
Diffstat (limited to 'src/core/NEON/kernels/NEHOGDescriptorKernel.cpp')
| -rw-r--r-- | src/core/NEON/kernels/NEHOGDescriptorKernel.cpp | 804 |
1 files changed, 0 insertions, 804 deletions
diff --git a/src/core/NEON/kernels/NEHOGDescriptorKernel.cpp b/src/core/NEON/kernels/NEHOGDescriptorKernel.cpp deleted file mode 100644 index c58b1c024a..0000000000 --- a/src/core/NEON/kernels/NEHOGDescriptorKernel.cpp +++ /dev/null @@ -1,804 +0,0 @@ -/* - * 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/NEHOGDescriptorKernel.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 <algorithm> -#include <arm_neon.h> -#include <cstring> - -using namespace arm_compute; - -namespace -{ -void cell_width_lt8(const int16_t *__restrict mag_row_ptr, const uint8_t *__restrict phase_row_ptr, float *__restrict output_ptr, - size_t mag_stride, size_t phase_stride, size_t cell_width, size_t cell_height, size_t num_bins, float phase_scale) -{ - const float32x4_t scale_f32 = vdupq_n_f32(phase_scale); - static const float32x4_t one_f32 = vdupq_n_f32(1.0f); - static const float32x4_t zerofive_f32 = vdupq_n_f32(0.5f); - static const int32x4_t zero_s32 = vdupq_n_s32(0); - static const int32x4_t one_s32 = vdupq_n_s32(1); - const int32x4_t num_bins_s32 = vdupq_n_s32(num_bins); - - memset(output_ptr, 0, sizeof(float) * num_bins); - - for(size_t yc = 0; yc < cell_height; ++yc) - { - int32_t xc = 0; - - for(; xc <= static_cast<int32_t>(cell_width) - 4; xc += 4) - { - // Load magnitude and phase values - const uint8x8_t phase_u8 = vld1_u8(phase_row_ptr + xc + yc * phase_stride); - const int16x4_t mag_s16 = vld1_s16(mag_row_ptr + xc + yc * mag_stride); - - // Convert magnitude and phase to float - const float32x4_t mag_f32 = vcvtq_f32_s32(vmovl_s16(mag_s16)); - float32x4_t phase_f32 = vcvtq_f32_u32(vmovl_u16(vget_low_u16(vmovl_u8(phase_u8)))); - - // Scale phase: phase * scale + 0.5f - phase_f32 = vmlaq_f32(zerofive_f32, phase_f32, scale_f32); - - // Compute histogram index. - int32x4_t hidx_s32 = vcvtq_s32_f32(phase_f32); - - // Compute magnitude weights (w0 and w1) - const float32x4_t hidx_f32 = vcvtq_f32_s32(hidx_s32); - - // w1 = phase_f32 - hidx_f32 - const float32x4_t w1_f32 = vsubq_f32(phase_f32, hidx_f32); - - // w0 = 1.0 - w1 - const float32x4_t w0_f32 = vsubq_f32(one_f32, w1_f32); - - // Compute contribute for splitting vote - const float32x4_t mag_w0_f32 = vmulq_f32(mag_f32, w0_f32); - const float32x4_t mag_w1_f32 = vmulq_f32(mag_f32, w1_f32); - - // Weighted vote between 2 bins - - // Check if the histogram index is equal to num_bins. If so, replace the index with 0 - uint32x4_t mask = vceqq_s32(hidx_s32, num_bins_s32); - hidx_s32 = vbslq_s32(mask, zero_s32, hidx_s32); - - // Bin 0 - *(output_ptr + vgetq_lane_s32(hidx_s32, 0)) += vgetq_lane_f32(mag_w0_f32, 0); - *(output_ptr + vgetq_lane_s32(hidx_s32, 1)) += vgetq_lane_f32(mag_w0_f32, 1); - *(output_ptr + vgetq_lane_s32(hidx_s32, 2)) += vgetq_lane_f32(mag_w0_f32, 2); - *(output_ptr + vgetq_lane_s32(hidx_s32, 3)) += vgetq_lane_f32(mag_w0_f32, 3); - - hidx_s32 = vaddq_s32(hidx_s32, one_s32); - - // Check if the histogram index is equal to num_bins - mask = vceqq_s32(hidx_s32, num_bins_s32); - hidx_s32 = vbslq_s32(mask, zero_s32, hidx_s32); - - // Bin1 - *(output_ptr + vgetq_lane_s32(hidx_s32, 0)) += vgetq_lane_f32(mag_w1_f32, 0); - *(output_ptr + vgetq_lane_s32(hidx_s32, 1)) += vgetq_lane_f32(mag_w1_f32, 1); - *(output_ptr + vgetq_lane_s32(hidx_s32, 2)) += vgetq_lane_f32(mag_w1_f32, 2); - *(output_ptr + vgetq_lane_s32(hidx_s32, 3)) += vgetq_lane_f32(mag_w1_f32, 3); - } - - for(; xc < static_cast<int32_t>(cell_width); ++xc) - { - const float phase_value = *(phase_row_ptr + xc + yc * phase_stride) * phase_scale + 0.5f; - const float mag_value = *(mag_row_ptr + xc + yc * mag_stride); - - const float w1 = phase_value - std::floor(phase_value); - - // The quantised phase is the histogram index [0, num_bins - 1] - Round - // Check limit of histogram index. If hidx == num_bins, hidx = 0 - const auto hidx = static_cast<size_t>(phase_value) % num_bins; - - // Weighted vote between 2 bins - *(output_ptr + hidx) += mag_value * (1.0f - w1); - *(output_ptr + ((hidx + 1) % (num_bins))) += mag_value * w1; - } - } -} - -void cell_width_ge8(const int16_t *__restrict mag_row_ptr, const uint8_t *__restrict phase_row_ptr, float *__restrict output_ptr, size_t mag_stride, size_t phase_stride, size_t cell_width, - size_t cell_height, size_t num_bins, float phase_scale) -{ - const float32x4_t scale_f32 = vdupq_n_f32(phase_scale); - static const float32x4_t one_f32 = vdupq_n_f32(1.0f); - static const float32x4_t zerofive_f32 = vdupq_n_f32(0.5f); - static const int32x4_t zero_s32 = vdupq_n_s32(0); - static const int32x4_t one_s32 = vdupq_n_s32(1); - const int32x4_t num_bins_s32 = vdupq_n_s32(num_bins); - - memset(output_ptr, 0, sizeof(float) * num_bins); - - for(size_t yc = 0; yc < cell_height; ++yc) - { - int32_t xc = 0; - - for(; xc <= static_cast<int32_t>(cell_width) - 8; xc += 8) - { - // Load magnitude and phase values - const uint8x8_t phase_u8 = vld1_u8(phase_row_ptr + xc + yc * phase_stride); - const int16x8_t mag_s16 = vld1q_s16(mag_row_ptr + xc + yc * mag_stride); - - // Convert phase to U16 - const uint16x8_t phase_u16 = vmovl_u8(phase_u8); - - // Convert magnitude to float32 - const float32x4x2_t mag_f32 = - { - { - vcvtq_f32_s32(vmovl_s16(vget_low_s16(mag_s16))), - vcvtq_f32_s32(vmovl_s16(vget_high_s16(mag_s16))) - } - }; - - // Convert phase to float32 - float32x4x2_t phase_f32 = - { - { - vcvtq_f32_u32(vmovl_u16(vget_low_u16(phase_u16))), - vcvtq_f32_u32(vmovl_u16(vget_high_u16(phase_u16))) - } - }; - - // Scale phase: phase * scale + 0.5f - phase_f32.val[0] = vmlaq_f32(zerofive_f32, phase_f32.val[0], scale_f32); - phase_f32.val[1] = vmlaq_f32(zerofive_f32, phase_f32.val[1], scale_f32); - - // Compute histogram index. - int32x4x2_t hidx_s32 = - { - { - vcvtq_s32_f32(phase_f32.val[0]), - vcvtq_s32_f32(phase_f32.val[1]) - } - }; - - // Compute magnitude weights (w0 and w1) - const float32x4x2_t hidx_f32 = - { - { - vcvtq_f32_s32(hidx_s32.val[0]), - vcvtq_f32_s32(hidx_s32.val[1]) - } - }; - - float32x4x2_t w1_f32 = - { - { - vsubq_f32(phase_f32.val[0], hidx_f32.val[0]), - vsubq_f32(phase_f32.val[1], hidx_f32.val[1]) - } - }; - - float32x4x2_t w0_f32 = - { - { - vsubq_f32(one_f32, w1_f32.val[0]), - vsubq_f32(one_f32, w1_f32.val[1]) - } - }; - - // Compute contribute for splitting vote - const float32x4x2_t mag_w0_f32 = - { - { - vmulq_f32(mag_f32.val[0], w0_f32.val[0]), - vmulq_f32(mag_f32.val[1], w0_f32.val[1]) - } - }; - - const float32x4x2_t mag_w1_f32 = - { - { - vmulq_f32(mag_f32.val[0], w1_f32.val[0]), - vmulq_f32(mag_f32.val[1], w1_f32.val[1]) - } - }; - - // Weighted vote between 2 bins - - // Check if the histogram index is equal to num_bins - uint32x4x2_t mask = - { - { - vceqq_s32(hidx_s32.val[0], num_bins_s32), - vceqq_s32(hidx_s32.val[1], num_bins_s32) - } - }; - - hidx_s32.val[0] = vbslq_s32(mask.val[0], zero_s32, hidx_s32.val[0]); - hidx_s32.val[1] = vbslq_s32(mask.val[1], zero_s32, hidx_s32.val[1]); - - // First bin - Low - *(output_ptr + vgetq_lane_s32(hidx_s32.val[0], 0)) += vgetq_lane_f32(mag_w0_f32.val[0], 0); - *(output_ptr + vgetq_lane_s32(hidx_s32.val[0], 1)) += vgetq_lane_f32(mag_w0_f32.val[0], 1); - *(output_ptr + vgetq_lane_s32(hidx_s32.val[0], 2)) += vgetq_lane_f32(mag_w0_f32.val[0], 2); - *(output_ptr + vgetq_lane_s32(hidx_s32.val[0], 3)) += vgetq_lane_f32(mag_w0_f32.val[0], 3); - - // First bin - high - *(output_ptr + vgetq_lane_s32(hidx_s32.val[1], 0)) += vgetq_lane_f32(mag_w0_f32.val[1], 0); - *(output_ptr + vgetq_lane_s32(hidx_s32.val[1], 1)) += vgetq_lane_f32(mag_w0_f32.val[1], 1); - *(output_ptr + vgetq_lane_s32(hidx_s32.val[1], 2)) += vgetq_lane_f32(mag_w0_f32.val[1], 2); - *(output_ptr + vgetq_lane_s32(hidx_s32.val[1], 3)) += vgetq_lane_f32(mag_w0_f32.val[1], 3); - - hidx_s32.val[0] = vaddq_s32(hidx_s32.val[0], one_s32); - hidx_s32.val[1] = vaddq_s32(hidx_s32.val[1], one_s32); - - // Check if the histogram index is equal to num_bins - mask.val[0] = vceqq_s32(hidx_s32.val[0], num_bins_s32); - mask.val[1] = vceqq_s32(hidx_s32.val[1], num_bins_s32); - - hidx_s32.val[0] = vbslq_s32(mask.val[0], zero_s32, hidx_s32.val[0]); - hidx_s32.val[1] = vbslq_s32(mask.val[1], zero_s32, hidx_s32.val[1]); - - // Second bin - Low - *(output_ptr + vgetq_lane_s32(hidx_s32.val[0], 0)) += vgetq_lane_f32(mag_w1_f32.val[0], 0); - *(output_ptr + vgetq_lane_s32(hidx_s32.val[0], 1)) += vgetq_lane_f32(mag_w1_f32.val[0], 1); - *(output_ptr + vgetq_lane_s32(hidx_s32.val[0], 2)) += vgetq_lane_f32(mag_w1_f32.val[0], 2); - *(output_ptr + vgetq_lane_s32(hidx_s32.val[0], 3)) += vgetq_lane_f32(mag_w1_f32.val[0], 3); - - // Second bin - high - *(output_ptr + vgetq_lane_s32(hidx_s32.val[1], 0)) += vgetq_lane_f32(mag_w1_f32.val[1], 0); - *(output_ptr + vgetq_lane_s32(hidx_s32.val[1], 1)) += vgetq_lane_f32(mag_w1_f32.val[1], 1); - *(output_ptr + vgetq_lane_s32(hidx_s32.val[1], 2)) += vgetq_lane_f32(mag_w1_f32.val[1], 2); - *(output_ptr + vgetq_lane_s32(hidx_s32.val[1], 3)) += vgetq_lane_f32(mag_w1_f32.val[1], 3); - } - - for(; xc < static_cast<int32_t>(cell_width); xc++) - { - const float phase_value = *(phase_row_ptr + xc + yc * phase_stride) * phase_scale + 0.5f; - const float mag_value = *(mag_row_ptr + xc + yc * mag_stride); - - const float w1 = phase_value - std::floor(phase_value); - - // The quantised phase is the histogram index [0, num_bins - 1] - Round - // Check limit of histogram index. If hidx == num_bins, hidx = 0 - const size_t hidx = static_cast<size_t>(phase_value) % num_bins; - - // Weighted vote between 2 bins - *(output_ptr + hidx) += mag_value * (1.0f - w1); - *(output_ptr + ((hidx + 1) % (num_bins))) += mag_value * w1; - } - } -} - -void l2_norm(const float *__restrict input_row_ptr, float *__restrict output_ptr, size_t input_stride, - size_t num_cells_per_block_height, size_t num_bins_block_x, size_t num_bins_block, float l2_hyst_threshold) -{ - ARM_COMPUTE_UNUSED(l2_hyst_threshold); - - float sum = 0.0f; - float32x4_t sum_f32 = vdupq_n_f32(0.0f); - - // Compute L2-Norm - for(size_t yc = 0; yc < num_cells_per_block_height; ++yc) - { - const float *const hist_ptr = input_row_ptr + yc * input_stride; - - int32_t xc = 0; - - for(; xc <= static_cast<int32_t>(num_bins_block_x) - 16; xc += 16) - { - const float32x4x4_t input_value = - { - { - vld1q_f32(hist_ptr + xc + 0), - vld1q_f32(hist_ptr + xc + 4), - vld1q_f32(hist_ptr + xc + 8), - vld1q_f32(hist_ptr + xc + 12) - } - }; - - // Compute input_value^2 - sum_f32 = vmlaq_f32(sum_f32, input_value.val[0], input_value.val[0]); - sum_f32 = vmlaq_f32(sum_f32, input_value.val[1], input_value.val[1]); - sum_f32 = vmlaq_f32(sum_f32, input_value.val[2], input_value.val[2]); - sum_f32 = vmlaq_f32(sum_f32, input_value.val[3], input_value.val[3]); - - vst1q_f32(&output_ptr[xc + 0 + yc * num_bins_block_x], input_value.val[0]); - vst1q_f32(&output_ptr[xc + 4 + yc * num_bins_block_x], input_value.val[1]); - vst1q_f32(&output_ptr[xc + 8 + yc * num_bins_block_x], input_value.val[2]); - vst1q_f32(&output_ptr[xc + 12 + yc * num_bins_block_x], input_value.val[3]); - } - - // Compute left over - for(; xc < static_cast<int32_t>(num_bins_block_x); xc++) - { - const float input_value = hist_ptr[xc]; - - sum += input_value * input_value; - - output_ptr[xc + yc * num_bins_block_x] = input_value; - } - } - - sum += vgetq_lane_f32(sum_f32, 0); - sum += vgetq_lane_f32(sum_f32, 1); - sum += vgetq_lane_f32(sum_f32, 2); - sum += vgetq_lane_f32(sum_f32, 3); - - const float scale = 1.0f / (std::sqrt(sum) + num_bins_block * 0.1f); - const float32x4_t scale_f32 = vdupq_n_f32(scale); - - int32_t i = 0; - - for(; i <= static_cast<int32_t>(num_bins_block) - 16; i += 16) - { - float32x4x4_t input_value = - { - { - vld1q_f32(&output_ptr[i + 0]), - vld1q_f32(&output_ptr[i + 4]), - vld1q_f32(&output_ptr[i + 8]), - vld1q_f32(&output_ptr[i + 12]) - } - }; - - // Scale input_value - input_value.val[0] = vmulq_f32(input_value.val[0], scale_f32); - input_value.val[1] = vmulq_f32(input_value.val[1], scale_f32); - input_value.val[2] = vmulq_f32(input_value.val[2], scale_f32); - input_value.val[3] = vmulq_f32(input_value.val[3], scale_f32); - - vst1q_f32(&output_ptr[i + 0], input_value.val[0]); - vst1q_f32(&output_ptr[i + 4], input_value.val[1]); - vst1q_f32(&output_ptr[i + 8], input_value.val[2]); - vst1q_f32(&output_ptr[i + 12], input_value.val[3]); - } - - for(; i < static_cast<int32_t>(num_bins_block); ++i) - { - output_ptr[i] *= scale; - } -} - -void l2hys_norm(const float *__restrict input_row_ptr, float *__restrict output_ptr, size_t input_stride, size_t num_cells_per_block_height, size_t num_bins_block_x, size_t num_bins_block, - float l2_hyst_threshold) -{ - float sum = 0.0f; - float32x4_t sum_f32 = vdupq_n_f32(0.0f); - - // Compute L2-Hys - for(size_t yc = 0; yc < num_cells_per_block_height; ++yc) - { - const float *const hist_ptr = input_row_ptr + yc * input_stride; - - int32_t xc = 0; - - for(; xc <= static_cast<int32_t>(num_bins_block_x) - 16; xc += 16) - { - const float32x4x4_t input_value = - { - { - vld1q_f32(hist_ptr + xc + 0), - vld1q_f32(hist_ptr + xc + 4), - vld1q_f32(hist_ptr + xc + 8), - vld1q_f32(hist_ptr + xc + 12) - } - }; - - // Compute input_value^2 - sum_f32 = vmlaq_f32(sum_f32, input_value.val[0], input_value.val[0]); - sum_f32 = vmlaq_f32(sum_f32, input_value.val[1], input_value.val[1]); - sum_f32 = vmlaq_f32(sum_f32, input_value.val[2], input_value.val[2]); - sum_f32 = vmlaq_f32(sum_f32, input_value.val[3], input_value.val[3]); - - vst1q_f32(&output_ptr[xc + 0 + yc * num_bins_block_x], input_value.val[0]); - vst1q_f32(&output_ptr[xc + 4 + yc * num_bins_block_x], input_value.val[1]); - vst1q_f32(&output_ptr[xc + 8 + yc * num_bins_block_x], input_value.val[2]); - vst1q_f32(&output_ptr[xc + 12 + yc * num_bins_block_x], input_value.val[3]); - } - - // Compute left over - for(; xc < static_cast<int32_t>(num_bins_block_x); ++xc) - { - const float input_value = hist_ptr[xc]; - - sum += input_value * input_value; - - output_ptr[xc + yc * num_bins_block_x] = input_value; - } - } - - sum += vgetq_lane_f32(sum_f32, 0); - sum += vgetq_lane_f32(sum_f32, 1); - sum += vgetq_lane_f32(sum_f32, 2); - sum += vgetq_lane_f32(sum_f32, 3); - - float scale = 1.0f / (std::sqrt(sum) + num_bins_block * 0.1f); - float32x4_t scale_f32 = vdupq_n_f32(scale); - const float32x4_t l2_hyst_threshold_f32 = vdupq_n_f32(l2_hyst_threshold); - - // Reset sum - sum_f32 = vdupq_n_f32(0.0f); - sum = 0.0f; - - int32_t i = 0; - - for(; i <= static_cast<int32_t>(num_bins_block) - 16; i += 16) - { - float32x4x4_t input_value = - { - { - vld1q_f32(&output_ptr[i + 0]), - vld1q_f32(&output_ptr[i + 4]), - vld1q_f32(&output_ptr[i + 8]), - vld1q_f32(&output_ptr[i + 12]) - } - }; - - // Scale input_value - input_value.val[0] = vmulq_f32(input_value.val[0], scale_f32); - input_value.val[1] = vmulq_f32(input_value.val[1], scale_f32); - input_value.val[2] = vmulq_f32(input_value.val[2], scale_f32); - input_value.val[3] = vmulq_f32(input_value.val[3], scale_f32); - - // Clip input_value if over _threshold_l2hys - input_value.val[0] = vminq_f32(input_value.val[0], l2_hyst_threshold_f32); - input_value.val[1] = vminq_f32(input_value.val[1], l2_hyst_threshold_f32); - input_value.val[2] = vminq_f32(input_value.val[2], l2_hyst_threshold_f32); - input_value.val[3] = vminq_f32(input_value.val[3], l2_hyst_threshold_f32); - - // Compute input_value^2 - sum_f32 = vmlaq_f32(sum_f32, input_value.val[0], input_value.val[0]); - sum_f32 = vmlaq_f32(sum_f32, input_value.val[1], input_value.val[1]); - sum_f32 = vmlaq_f32(sum_f32, input_value.val[2], input_value.val[2]); - sum_f32 = vmlaq_f32(sum_f32, input_value.val[3], input_value.val[3]); - - vst1q_f32(&output_ptr[i + 0], input_value.val[0]); - vst1q_f32(&output_ptr[i + 4], input_value.val[1]); - vst1q_f32(&output_ptr[i + 8], input_value.val[2]); - vst1q_f32(&output_ptr[i + 12], input_value.val[3]); - } - - sum += vgetq_lane_f32(sum_f32, 0); - sum += vgetq_lane_f32(sum_f32, 1); - sum += vgetq_lane_f32(sum_f32, 2); - sum += vgetq_lane_f32(sum_f32, 3); - - for(; i < static_cast<int32_t>(num_bins_block); ++i) - { - float input_value = output_ptr[i] * scale; - - // Clip scaled input_value if over _threshold_L2hys - input_value = std::min(input_value, l2_hyst_threshold); - - sum += input_value * input_value; - - output_ptr[i] = input_value; - } - - // We use the same constants of OpenCV - scale = 1.0f / (std::sqrt(sum) + 1e-3f); - scale_f32 = vdupq_n_f32(scale); - - // Rescale - i = 0; - - for(; i <= static_cast<int32_t>(num_bins_block) - 16; i += 16) - { - float32x4x4_t input_value = - { - { - vld1q_f32(&output_ptr[i + 0]), - vld1q_f32(&output_ptr[i + 4]), - vld1q_f32(&output_ptr[i + 8]), - vld1q_f32(&output_ptr[i + 12]) - } - }; - - // Scale input_value - input_value.val[0] = vmulq_f32(input_value.val[0], scale_f32); - input_value.val[1] = vmulq_f32(input_value.val[1], scale_f32); - input_value.val[2] = vmulq_f32(input_value.val[2], scale_f32); - input_value.val[3] = vmulq_f32(input_value.val[3], scale_f32); - - vst1q_f32(&output_ptr[i + 0], input_value.val[0]); - vst1q_f32(&output_ptr[i + 4], input_value.val[1]); - vst1q_f32(&output_ptr[i + 8], input_value.val[2]); - vst1q_f32(&output_ptr[i + 12], input_value.val[3]); - } - - for(; i < static_cast<int32_t>(num_bins_block); ++i) - { - // Store result - output_ptr[i] *= scale; - } -} - -void l1_norm(const float *__restrict input_row_ptr, float *__restrict output_ptr, size_t input_stride, size_t num_cells_per_block_height, size_t num_bins_block_x, size_t num_bins_block, - float l2_hyst_threshold) -{ - ARM_COMPUTE_UNUSED(l2_hyst_threshold); - - float sum = 0.0f; - float32x4_t sum_f32 = vdupq_n_f32(0.0f); - - // Compute L1-Norm - for(size_t yc = 0; yc < num_cells_per_block_height; ++yc) - { - const float *const hist_ptr = input_row_ptr + yc * input_stride; - - int32_t xc = 0; - - for(; xc <= static_cast<int32_t>(num_bins_block_x) - 16; xc += 16) - { - const float32x4x4_t input_value = - { - { - vld1q_f32(hist_ptr + xc + 0), - vld1q_f32(hist_ptr + xc + 4), - vld1q_f32(hist_ptr + xc + 8), - vld1q_f32(hist_ptr + xc + 12) - } - }; - - // Compute |input_value| - sum_f32 += vabsq_f32(input_value.val[0]); - sum_f32 += vabsq_f32(input_value.val[1]); - sum_f32 += vabsq_f32(input_value.val[2]); - sum_f32 += vabsq_f32(input_value.val[3]); - - vst1q_f32(&output_ptr[xc + 0 + yc * num_bins_block_x], input_value.val[0]); - vst1q_f32(&output_ptr[xc + 4 + yc * num_bins_block_x], input_value.val[1]); - vst1q_f32(&output_ptr[xc + 8 + yc * num_bins_block_x], input_value.val[2]); - vst1q_f32(&output_ptr[xc + 12 + yc * num_bins_block_x], input_value.val[3]); - } - - for(; xc < static_cast<int32_t>(num_bins_block_x); xc++) - { - const float input_value = hist_ptr[xc]; - - sum += std::abs(input_value); - - output_ptr[xc + yc * num_bins_block_x] = input_value; - } - } - - sum += vgetq_lane_f32(sum_f32, 0); - sum += vgetq_lane_f32(sum_f32, 1); - sum += vgetq_lane_f32(sum_f32, 2); - sum += vgetq_lane_f32(sum_f32, 3); - - const float scale = 1.0f / (std::sqrt(sum) + num_bins_block * 0.1f); - const float32x4_t scale_f32 = vdupq_n_f32(scale); - - int32_t i = 0; - - for(; i <= static_cast<int32_t>(num_bins_block) - 16; i += 16) - { - float32x4x4_t input_value = - { - { - vld1q_f32(&output_ptr[i + 0]), - vld1q_f32(&output_ptr[i + 4]), - vld1q_f32(&output_ptr[i + 8]), - vld1q_f32(&output_ptr[i + 12]) - } - }; - - // Scale input_value - input_value.val[0] = vmulq_f32(input_value.val[0], scale_f32); - input_value.val[1] = vmulq_f32(input_value.val[1], scale_f32); - input_value.val[2] = vmulq_f32(input_value.val[2], scale_f32); - input_value.val[3] = vmulq_f32(input_value.val[3], scale_f32); - - vst1q_f32(&output_ptr[i + 0], input_value.val[0]); - vst1q_f32(&output_ptr[i + 4], input_value.val[1]); - vst1q_f32(&output_ptr[i + 8], input_value.val[2]); - vst1q_f32(&output_ptr[i + 12], input_value.val[3]); - } - - for(; i < static_cast<int32_t>(num_bins_block); ++i) - { - output_ptr[i] *= scale; - } -} -} // namespace - -NEHOGOrientationBinningKernel::NEHOGOrientationBinningKernel() - : _func(nullptr), _input_magnitude(nullptr), _input_phase(nullptr), _output(nullptr), _cell_width(0), _cell_height(0), _num_bins(0), _phase_scale(0) -{ -} - -void NEHOGOrientationBinningKernel::configure(const ITensor *input_magnitude, const ITensor *input_phase, ITensor *output, const HOGInfo *hog_info) -{ - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input_magnitude, 1, DataType::S16); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input_phase, 1, DataType::U8); - ARM_COMPUTE_ERROR_ON(hog_info == nullptr); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, hog_info->num_bins(), DataType::F32); - ARM_COMPUTE_ERROR_ON(input_magnitude->info()->dimension(Window::DimX) != input_phase->info()->dimension(Window::DimX)); - ARM_COMPUTE_ERROR_ON(input_magnitude->info()->dimension(Window::DimY) != input_phase->info()->dimension(Window::DimY)); - - _input_magnitude = input_magnitude; - _input_phase = input_phase; - _output = output; - _cell_width = hog_info->cell_size().width; - _cell_height = hog_info->cell_size().height; - _num_bins = hog_info->num_bins(); - _phase_scale = (PhaseType::SIGNED == hog_info->phase_type() ? _num_bins / 360.0f : _num_bins / 180.0f); - _phase_scale *= (PhaseType::SIGNED == hog_info->phase_type() ? 360.0f / 255.0f : 1.0f); - - if(_cell_width < 8) - { - _func = &cell_width_lt8; - } - else - { - _func = &cell_width_ge8; - } - - constexpr unsigned int num_elems_processed_per_iteration = 1; - const unsigned int num_elems_read_per_iteration = 1; - const unsigned int num_rows_read_per_iteration = _cell_height; - const unsigned int num_elems_written_per_iteration = 1; - - // Configure kernel window - Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration)); - AccessWindowHorizontal output_access(output->info(), 0, num_elems_written_per_iteration); - - update_window_and_padding(win, - AccessWindowRectangle(input_magnitude->info(), 0, 0, num_elems_read_per_iteration, num_rows_read_per_iteration), - AccessWindowRectangle(input_phase->info(), 0, 0, num_elems_read_per_iteration, num_rows_read_per_iteration), - output_access); - - output->info()->set_valid_region(ValidRegion(Coordinates(), output->info()->tensor_shape())); - - INEKernel::configure(win); -} - -void NEHOGOrientationBinningKernel::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(_func == nullptr); - - const size_t mag_stride = _input_magnitude->info()->strides_in_bytes()[Window::DimY] / pixel_size_from_format(_input_magnitude->info()->format()); - const size_t phase_stride = _input_phase->info()->strides_in_bytes()[Window::DimY] / pixel_size_from_format(_input_phase->info()->format()); - - Window win_mag(window); - win_mag.set(Window::DimX, Window::Dimension(window.x().start() * _cell_width, window.x().start() * _cell_width, _cell_width)); - win_mag.set(Window::DimY, Window::Dimension(window.y().start() * _cell_height, window.y().start() * _cell_height, _cell_height)); - - Window win_phase(win_mag); - - Iterator mag(_input_magnitude, win_mag); - Iterator phase(_input_phase, win_phase); - Iterator out(_output, window); - - execute_window_loop(window, [&](const Coordinates &) - { - const auto mag_row_ptr = reinterpret_cast<const int16_t *>(mag.ptr()); - const auto phase_row_ptr = reinterpret_cast<const uint8_t *>(phase.ptr()); - const auto out_row_ptr = reinterpret_cast<float *>(out.ptr()); - - (*_func)(mag_row_ptr, phase_row_ptr, out_row_ptr, mag_stride, phase_stride, _cell_width, _cell_height, _num_bins, _phase_scale); - }, - mag, phase, out); -} - -NEHOGBlockNormalizationKernel::NEHOGBlockNormalizationKernel() - : _func(nullptr), _input(nullptr), _output(nullptr), _num_cells_per_block(), _num_cells_per_block_stride(), _num_bins(0), _l2_hyst_threshold(0.0f) -{ -} - -void NEHOGBlockNormalizationKernel::configure(const ITensor *input, ITensor *output, const HOGInfo *hog_info) -{ - ARM_COMPUTE_ERROR_ON(hog_info == nullptr); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, hog_info->num_bins(), DataType::F32); - ARM_COMPUTE_ERROR_ON_DATA_TYPE_NOT_IN(output, DataType::F32); - - // Number of cells per block - const Size2D num_cells_per_block(hog_info->block_size().width / hog_info->cell_size().width, - hog_info->block_size().height / hog_info->cell_size().height); - - // Number of cells per block stride - const Size2D num_cells_per_block_stride(hog_info->block_stride().width / hog_info->cell_size().width, - hog_info->block_stride().height / hog_info->cell_size().height); - - _input = input; - _output = output; - _l2_hyst_threshold = hog_info->l2_hyst_threshold(); - _num_cells_per_block = num_cells_per_block; - _num_cells_per_block_stride = num_cells_per_block_stride; - _num_bins = hog_info->num_bins(); - - ARM_COMPUTE_ERROR_ON((output->info()->num_channels() != (_num_bins * num_cells_per_block.width * num_cells_per_block.height))); - - switch(hog_info->normalization_type()) - { - case HOGNormType::L2_NORM: - _func = &l2_norm; - break; - case HOGNormType::L2HYS_NORM: - _func = &l2hys_norm; - break; - case HOGNormType::L1_NORM: - _func = &l1_norm; - break; - default: - ARM_COMPUTE_ERROR_ON("Normalisation type not supported"); - break; - } - - constexpr unsigned int num_elems_processed_per_iteration = 1; - const unsigned int num_elems_read_per_iteration = 1; - const unsigned int num_rows_read_per_iteration = _num_cells_per_block.height; - const unsigned int num_elems_written_per_iteration = 1; - const unsigned int num_rows_written_per_iteration = _num_cells_per_block.height; - - // Configure kernel window - Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration)); - AccessWindowRectangle output_access(output->info(), 0, 0, num_elems_written_per_iteration, num_rows_written_per_iteration); - - update_window_and_padding(win, - AccessWindowRectangle(input->info(), 0, 0, num_elems_read_per_iteration, num_rows_read_per_iteration), - output_access); - - output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape())); - - INEKernel::configure(win); -} - -void NEHOGBlockNormalizationKernel::run(const Window &window, const ThreadInfo &info) -{ - ARM_COMPUTE_UNUSED(info); - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON(_func == nullptr); - ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); - - // Get number of bins per block - const size_t num_bins_per_block = _output->info()->num_channels(); - - // Number of bins on the same row of the block - const int32_t num_bins_per_block_x = _num_cells_per_block.width * _num_bins; - - const size_t input_stride = _input->info()->strides_in_bytes()[Window::DimY] / data_size_from_type(_input->info()->data_type()); - - Window win_in(window); - win_in.set_dimension_step(Window::DimX, _num_cells_per_block_stride.width); - win_in.set(Window::DimY, Window::Dimension(0, 0, 0)); - - Iterator in(_input, win_in); - Iterator out(_output, window); - - // Normalises blocks - execute_window_loop(window, [&](const Coordinates & id) - { - const auto input_row_ptr = reinterpret_cast<const float *>(in.ptr() + id.y() * _num_cells_per_block_stride.height * _input->info()->strides_in_bytes()[Window::DimY]); - const auto out_row_ptr = reinterpret_cast<float *>(out.ptr()); - - // Execute normalization function - (*_func)(input_row_ptr, out_row_ptr, input_stride, _num_cells_per_block.height, num_bins_per_block_x, num_bins_per_block, _l2_hyst_threshold); - }, - in, out); -} |