From 6c7c38e70c795077ba727aadeefc670888bec089 Mon Sep 17 00:00:00 2001 From: Michalis Spyrou Date: Wed, 29 Aug 2018 16:28:11 +0100 Subject: COMPMID-1462 SSD support: Create CL PriorBox Change-Id: I5bf5d751ec7c02d96c26a769f49d03ea23a248b7 --- tests/validation/reference/PriorBoxLayer.cpp | 158 +++++++++++++++++++++++++++ 1 file changed, 158 insertions(+) create mode 100644 tests/validation/reference/PriorBoxLayer.cpp (limited to 'tests/validation/reference/PriorBoxLayer.cpp') diff --git a/tests/validation/reference/PriorBoxLayer.cpp b/tests/validation/reference/PriorBoxLayer.cpp new file mode 100644 index 0000000000..0fd4a8aa48 --- /dev/null +++ b/tests/validation/reference/PriorBoxLayer.cpp @@ -0,0 +1,158 @@ +/* + * Copyright (c) 2018 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 "PriorBoxLayer.h" + +#include "ActivationLayer.h" + +#include "tests/validation/Helpers.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace reference +{ +template +SimpleTensor prior_box_layer(const SimpleTensor &src1, const SimpleTensor &src2, const PriorBoxLayerInfo &info, const TensorShape &output_shape) +{ + const auto layer_width = static_cast(src1.shape()[0]); + const auto layer_height = static_cast(src1.shape()[1]); + + int img_width = info.img_size().x; + int img_height = info.img_size().y; + if(img_width == 0 || img_height == 0) + { + img_width = static_cast(src2.shape()[0]); + img_height = static_cast(src2.shape()[1]); + } + + float step_x = info.steps()[0]; + float step_y = info.steps()[1]; + if(step_x == 0.f || step_y == 0.f) + { + step_x = static_cast(img_width) / layer_width; + step_x = static_cast(img_height) / layer_height; + } + + // Calculate number of aspect ratios + const int num_priors = info.aspect_ratios().size() * info.min_sizes().size() + info.max_sizes().size(); + const int total_elements = layer_width * layer_height * num_priors * 4; + + SimpleTensor result(output_shape, src1.data_type()); + + int idx = 0; + for(int y = 0; y < layer_height; ++y) + { + for(int x = 0; x < layer_width; ++x) + { + const float center_x = (x + info.offset()) * step_x; + const float center_y = (y + info.offset()) * step_y; + float box_width; + float box_height; + for(unsigned int i = 0; i < info.min_sizes().size(); ++i) + { + const float min_size = info.min_sizes().at(i); + box_width = min_size; + box_height = min_size; + // (xmin, ymin, xmax, ymax) + result[idx++] = (center_x - box_width / 2.f) / img_width; + result[idx++] = (center_y - box_height / 2.f) / img_height; + result[idx++] = (center_x + box_width / 2.f) / img_width; + result[idx++] = (center_y + box_height / 2.f) / img_height; + + if(!info.max_sizes().empty()) + { + const float max_size = info.max_sizes().at(i); + box_width = sqrt(min_size * max_size); + box_height = box_width; + + // (xmin, ymin, xmax, ymax) + result[idx++] = (center_x - box_width / 2.f) / img_width; + result[idx++] = (center_y - box_height / 2.f) / img_height; + result[idx++] = (center_x + box_width / 2.f) / img_width; + result[idx++] = (center_y + box_height / 2.f) / img_height; + } + + // rest of priors + for(auto ar : info.aspect_ratios()) + { + if(fabs(ar - 1.) < 1e-6) + { + continue; + } + + box_width = min_size * sqrt(ar); + box_height = min_size / sqrt(ar); + + // (xmin, ymin, xmax, ymax) + result[idx++] = (center_x - box_width / 2.f) / img_width; + result[idx++] = (center_y - box_height / 2.f) / img_height; + result[idx++] = (center_x + box_width / 2.f) / img_width; + result[idx++] = (center_y + box_height / 2.f) / img_height; + } + } + } + } + + // clip the coordinates + if(info.clip()) + { + for(int i = 0; i < total_elements; ++i) + { + result[i] = std::min(std::max(result[i], 0.f), 1.f); + } + } + + // set the variance. + if(info.variances().size() == 1) + { + std::fill_n(result.data() + idx, total_elements, info.variances().at(0)); + } + else + { + for(int h = 0; h < layer_height; ++h) + { + for(int w = 0; w < layer_width; ++w) + { + for(int i = 0; i < num_priors; ++i) + { + for(int j = 0; j < 4; ++j) + { + result[idx++] = info.variances().at(j); + } + } + } + } + } + + return result; +} +template SimpleTensor prior_box_layer(const SimpleTensor &src1, const SimpleTensor &src2, const PriorBoxLayerInfo &info, const TensorShape &output_shape); + +} // namespace reference +} // namespace validation +} // namespace test +} // namespace arm_compute -- cgit v1.2.1