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Diffstat (limited to 'tests/validation/fixtures/HOGMultiDetectionFixture.h')
| -rw-r--r-- | tests/validation/fixtures/HOGMultiDetectionFixture.h | 193 |
1 files changed, 0 insertions, 193 deletions
diff --git a/tests/validation/fixtures/HOGMultiDetectionFixture.h b/tests/validation/fixtures/HOGMultiDetectionFixture.h deleted file mode 100644 index c37bdb6df6..0000000000 --- a/tests/validation/fixtures/HOGMultiDetectionFixture.h +++ /dev/null @@ -1,193 +0,0 @@ -/* - * 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. - */ -#ifndef ARM_COMPUTE_TEST_HOG_MULTI_DETECTION_FIXTURE -#define ARM_COMPUTE_TEST_HOG_MULTI_DETECTION_FIXTURE - -#include "arm_compute/core/HOGInfo.h" -#include "arm_compute/core/TensorShape.h" -#include "arm_compute/core/Types.h" -#include "tests/AssetsLibrary.h" -#include "tests/Globals.h" -#include "tests/IAccessor.h" -#include "tests/IHOGAccessor.h" -#include "tests/framework/Asserts.h" -#include "tests/framework/Fixture.h" -#include "tests/validation/reference/HOGMultiDetection.h" - -namespace arm_compute -{ -namespace test -{ -namespace validation -{ -template <typename TensorType, - typename HOGType, - typename MultiHOGType, - typename DetectionWindowArrayType, - typename DetectionWindowStrideType, - typename AccessorType, - typename Size2DArrayAccessorType, - typename DetectionWindowArrayAccessorType, - typename HOGAccessorType, - typename FunctionType, - typename T, - typename U> -class HOGMultiDetectionValidationFixture : public framework::Fixture -{ -public: - template <typename...> - void setup(std::string image, std::vector<HOGInfo> models, Format format, BorderMode border_mode, bool non_maxima_suppression) - { - // Only defined borders supported - ARM_COMPUTE_ERROR_ON(border_mode == BorderMode::UNDEFINED); - - // Generate a random constant value - std::mt19937 gen(library->seed()); - std::uniform_int_distribution<T> int_dist(0, 255); - const T constant_border_value = int_dist(gen); - - // Initialize descriptors vector - std::vector<std::vector<U>> descriptors(models.size()); - - // Use default values for threshold and min_distance - const float threshold = 0.f; - const float min_distance = 1.f; - - // Maximum number of detection windows per batch - const unsigned int max_num_detection_windows = 100000; - - _target = compute_target(image, format, border_mode, constant_border_value, models, descriptors, max_num_detection_windows, threshold, non_maxima_suppression, min_distance); - _reference = compute_reference(image, format, border_mode, constant_border_value, models, descriptors, max_num_detection_windows, threshold, non_maxima_suppression, min_distance); - } - -protected: - template <typename V> - void fill(V &&tensor, const std::string image, Format format) - { - library->fill(tensor, image, format); - } - - void initialize_batch(const std::vector<HOGInfo> &models, MultiHOGType &multi_hog, - std::vector<std::vector<U>> &descriptors, DetectionWindowStrideType &detection_window_strides) - { - for(unsigned i = 0; i < models.size(); ++i) - { - auto hog_model = reinterpret_cast<HOGType *>(multi_hog.model(i)); - hog_model->init(models[i]); - - // Initialise descriptor (linear SVM coefficients). - std::random_device::result_type seed = 0; - descriptors.at(i) = generate_random_real(models[i].descriptor_size(), -0.505f, 0.495f, seed); - - // Copy HOG descriptor values to HOG memory - { - HOGAccessorType hog_accessor(*hog_model); - std::memcpy(hog_accessor.descriptor(), descriptors.at(i).data(), descriptors.at(i).size() * sizeof(U)); - } - - // Initialize detection window stride - Size2DArrayAccessorType accessor(detection_window_strides); - accessor.at(i) = models[i].block_stride(); - } - } - - std::vector<DetectionWindow> compute_target(const std::string image, Format &format, BorderMode &border_mode, T constant_border_value, - const std::vector<HOGInfo> &models, std::vector<std::vector<U>> &descriptors, unsigned int max_num_detection_windows, - float threshold, bool non_max_suppression, float min_distance) - { - MultiHOGType multi_hog(models.size()); - DetectionWindowArrayType detection_windows(max_num_detection_windows); - DetectionWindowStrideType detection_window_strides(models.size()); - - // Resize detection window_strides for index access - detection_window_strides.resize(models.size()); - - // Initialiize MultiHOG and detection windows - initialize_batch(models, multi_hog, descriptors, detection_window_strides); - - // Get image shape for src tensor - TensorShape shape = library->get_image_shape(image); - - // Create tensors - TensorType src = create_tensor<TensorType>(shape, data_type_from_format(format)); - ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); - - // Create and configure function - FunctionType hog_multi_detection; - hog_multi_detection.configure(&src, &multi_hog, &detection_windows, &detection_window_strides, border_mode, constant_border_value, threshold, non_max_suppression, min_distance); - - // Reset detection windows - detection_windows.clear(); - - // Allocate tensors - src.allocator()->allocate(); - ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS); - - // Fill tensors - fill(AccessorType(src), image, format); - - // Compute function - hog_multi_detection.run(); - - // Copy detection windows - std::vector<DetectionWindow> windows; - DetectionWindowArrayAccessorType accessor(detection_windows); - - for(size_t i = 0; i < accessor.num_values(); i++) - { - DetectionWindow win; - win.x = accessor.at(i).x; - win.y = accessor.at(i).y; - win.width = accessor.at(i).width; - win.height = accessor.at(i).height; - win.idx_class = accessor.at(i).idx_class; - win.score = accessor.at(i).score; - - windows.push_back(win); - } - - return windows; - } - - std::vector<DetectionWindow> compute_reference(const std::string image, Format format, BorderMode border_mode, T constant_border_value, - const std::vector<HOGInfo> &models, const std::vector<std::vector<U>> &descriptors, unsigned int max_num_detection_windows, - float threshold, bool non_max_suppression, float min_distance) - { - // Create reference - SimpleTensor<T> src{ library->get_image_shape(image), data_type_from_format(format) }; - - // Fill reference - fill(src, image, format); - - // NOTE: Detection window stride fixed to block stride - return reference::hog_multi_detection(src, border_mode, constant_border_value, models, descriptors, max_num_detection_windows, threshold, non_max_suppression, min_distance); - } - - std::vector<DetectionWindow> _target{}; - std::vector<DetectionWindow> _reference{}; -}; -} // namespace validation -} // namespace test -} // namespace arm_compute -#endif /* ARM_COMPUTE_TEST_HOG_MULTI_DETECTION_FIXTURE */ |