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Diffstat (limited to 'tests/validation/reference/HarrisCornerDetector.cpp')
| -rw-r--r-- | tests/validation/reference/HarrisCornerDetector.cpp | 205 |
1 files changed, 0 insertions, 205 deletions
diff --git a/tests/validation/reference/HarrisCornerDetector.cpp b/tests/validation/reference/HarrisCornerDetector.cpp deleted file mode 100644 index 6c46b3de5d..0000000000 --- a/tests/validation/reference/HarrisCornerDetector.cpp +++ /dev/null @@ -1,205 +0,0 @@ -/* - * Copyright (c) 2017 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 "HarrisCornerDetector.h" - -#include "Utils.h" -#include "tests/validation/Helpers.h" -#include "tests/validation/reference/NonMaximaSuppression.h" -#include "tests/validation/reference/Sobel.h" - -namespace arm_compute -{ -namespace test -{ -namespace validation -{ -namespace reference -{ -namespace -{ -template <typename T> -std::tuple<SimpleTensor<T>, SimpleTensor<T>, float> compute_sobel(const SimpleTensor<uint8_t> &src, int gradient_size, int block_size, BorderMode border_mode, uint8_t constant_border_value) -{ - SimpleTensor<T> grad_x; - SimpleTensor<T> grad_y; - float norm_factor = 0.f; - - std::tie(grad_x, grad_y) = sobel<T>(src, gradient_size, border_mode, constant_border_value, GradientDimension::GRAD_XY); - - switch(gradient_size) - { - case 3: - norm_factor = 1.f / (4 * 255 * block_size); - break; - case 5: - norm_factor = 1.f / (16 * 255 * block_size); - break; - case 7: - norm_factor = 1.f / (64 * 255 * block_size); - break; - default: - ARM_COMPUTE_ERROR("Gradient size not supported."); - } - - return std::make_tuple(grad_x, grad_y, norm_factor); -} - -template <typename T, typename U> -std::vector<KeyPoint> harris_corner_detector_impl(const SimpleTensor<U> &src, float threshold, float min_dist, float sensitivity, int gradient_size, int block_size, BorderMode border_mode, - U constant_border_value) -{ - ARM_COMPUTE_ERROR_ON(block_size != 3 && block_size != 5 && block_size != 7); - - SimpleTensor<T> grad_x; - SimpleTensor<T> grad_y; - float norm_factor = 0.f; - - // Sobel - std::tie(grad_x, grad_y, norm_factor) = compute_sobel<T>(src, gradient_size, block_size, border_mode, constant_border_value); - - SimpleTensor<float> scores(src.shape(), DataType::F32); - ValidRegion scores_region = shape_to_valid_region(scores.shape(), border_mode == BorderMode::UNDEFINED, BorderSize(gradient_size / 2 + block_size / 2)); - - // Calculate scores - for(int i = 0; i < scores.num_elements(); ++i) - { - Coordinates src_coord = index2coord(src.shape(), i); - Coordinates block_top_left{ src_coord.x() - block_size / 2, src_coord.y() - block_size / 2 }; - Coordinates block_bottom_right{ src_coord.x() + block_size / 2, src_coord.y() + block_size / 2 }; - - if(!is_in_valid_region(scores_region, src_coord)) - { - scores[i] = 0.f; - continue; - } - - float Gx2 = 0.f; - float Gy2 = 0.f; - float Gxy = 0.f; - - // Calculate Gx^2, Gy^2 and Gxy within the given window - for(int y = block_top_left.y(); y <= block_bottom_right.y(); ++y) - { - for(int x = block_top_left.x(); x <= block_bottom_right.x(); ++x) - { - Coordinates block_coord(x, y); - - const float norm_x = tensor_elem_at(grad_x, block_coord, border_mode, static_cast<T>(constant_border_value)) * norm_factor; - const float norm_y = tensor_elem_at(grad_y, block_coord, border_mode, static_cast<T>(constant_border_value)) * norm_factor; - - Gx2 += std::pow(norm_x, 2); - Gy2 += std::pow(norm_y, 2); - Gxy += norm_x * norm_y; - } - } - - const float trace2 = std::pow(Gx2 + Gy2, 2); - const float det = Gx2 * Gy2 - std::pow(Gxy, 2); - const float response = det - sensitivity * trace2; - - if(response > threshold) - { - scores[i] = response; - } - else - { - scores[i] = 0.f; - } - } - - // Suppress non-maxima candidates - SimpleTensor<float> suppressed_scores = non_maxima_suppression(scores, border_mode != BorderMode::UNDEFINED ? BorderMode::CONSTANT : BorderMode::UNDEFINED, 0.f); - ValidRegion suppressed_scores_region = shape_to_valid_region(suppressed_scores.shape(), border_mode == BorderMode::UNDEFINED, BorderSize(gradient_size / 2 + block_size / 2 + 1)); - - // Create vector of candidate corners - std::vector<KeyPoint> corner_candidates; - - for(int i = 0; i < suppressed_scores.num_elements(); ++i) - { - Coordinates coord = index2coord(suppressed_scores.shape(), i); - - if(is_in_valid_region(suppressed_scores_region, coord) && suppressed_scores[i] != 0.f) - { - KeyPoint corner; - corner.x = coord.x(); - corner.y = coord.y(); - corner.tracking_status = 1; - corner.strength = suppressed_scores[i]; - corner.scale = 0.f; - corner.orientation = 0.f; - corner.error = 0.f; - - corner_candidates.emplace_back(corner); - } - } - - // Sort descending by strength - std::sort(corner_candidates.begin(), corner_candidates.end(), [](const KeyPoint & a, const KeyPoint & b) - { - return a.strength > b.strength; - }); - - std::vector<KeyPoint> corners; - corners.reserve(corner_candidates.size()); - - // Only add corner if there is no stronger within min_dist - for(const KeyPoint &point : corner_candidates) - { - const auto strongest = std::find_if(corners.begin(), corners.end(), [&](const KeyPoint & other) - { - return std::sqrt((std::pow(point.x - other.x, 2) + std::pow(point.y - other.y, 2))) < min_dist; - }); - - if(strongest == corners.end()) - { - corners.emplace_back(point); - } - } - - corners.shrink_to_fit(); - - return corners; -} -} // namespace - -template <typename T> -std::vector<KeyPoint> harris_corner_detector(const SimpleTensor<T> &src, float threshold, float min_dist, float sensitivity, int gradient_size, int block_size, BorderMode border_mode, - T constant_border_value) -{ - if(gradient_size < 7) - { - return harris_corner_detector_impl<int16_t>(src, threshold, min_dist, sensitivity, gradient_size, block_size, border_mode, constant_border_value); - } - else - { - return harris_corner_detector_impl<int32_t>(src, threshold, min_dist, sensitivity, gradient_size, block_size, border_mode, constant_border_value); - } -} - -template std::vector<KeyPoint> harris_corner_detector(const SimpleTensor<uint8_t> &src, float threshold, float min_dist, float sensitivity, int gradient_size, int block_size, BorderMode border_mode, - uint8_t constant_border_value); -} // namespace reference -} // namespace validation -} // namespace test -} // namespace arm_compute |