From 34d5eb6d51217d4ef6592f9925e024cd9970f238 Mon Sep 17 00:00:00 2001 From: Pablo Marquez Date: Fri, 15 Feb 2019 09:51:03 +0000 Subject: Revert "COMPMID-1766: Implemented CPP Non Max Suppression" This reverts commit a0a0e29f635de08092c2325f8f049ffb286aabaf. Change-Id: I2a2a37ba7531f93a1562748054a3c29573c9753f Reviewed-on: https://review.mlplatform.org/705 Tested-by: Arm Jenkins Reviewed-by: VidhyaSudhan Loganathan --- .../CPP/functions/CPPDetectionOutputLayer.h | 52 +------- .../CPP/functions/CPPDetectionOutputLayer.cpp | 101 +-------------- tests/AssetsLibrary.h | 37 ------ tests/datasets/ShapeDatasets.h | 31 ----- tests/validation/CPP/NonMaximalSuppression.cpp | 144 --------------------- .../validation/fixtures/NonMaxSuppressionFixture.h | 124 ------------------ tests/validation/reference/NonMaxSuppression.cpp | 126 ------------------ tests/validation/reference/NonMaxSuppression.h | 44 ------- 8 files changed, 7 insertions(+), 652 deletions(-) delete mode 100644 tests/validation/CPP/NonMaximalSuppression.cpp delete mode 100644 tests/validation/fixtures/NonMaxSuppressionFixture.h delete mode 100644 tests/validation/reference/NonMaxSuppression.cpp delete mode 100644 tests/validation/reference/NonMaxSuppression.h diff --git a/arm_compute/runtime/CPP/functions/CPPDetectionOutputLayer.h b/arm_compute/runtime/CPP/functions/CPPDetectionOutputLayer.h index 8c610f3ec2..7f80948c81 100644 --- a/arm_compute/runtime/CPP/functions/CPPDetectionOutputLayer.h +++ b/arm_compute/runtime/CPP/functions/CPPDetectionOutputLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018-2019 ARM Limited. + * Copyright (c) 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -39,56 +39,6 @@ using NormalizedBBox = std::array; // LabelBBox used for map label and bounding box using LabelBBox = std::map>; -/** CPP Function to perform non maximum suppression on the bounding boxes and scores - * - */ -class CPPNonMaximumSuppression : public IFunction -{ -public: - /** Default constructor */ - CPPNonMaximumSuppression(); - /** Configure the function to perform non maximal suppression - * - * @param[in] bboxes The input bounding boxes. Data types supported: F32. - * @param[in] scores The corresponding input confidence. Same as @p scores. - * @param[out] indices The kept indices of bboxes after nms. Data types supported: S32. - * @param[in] max_output_size An integer tensor representing the maximum number of boxes to be selected by non max suppression. - * @param[in] score_threshold The threshold used to filter detection results. - * @param[in] nms_threshold The threshold used in non maximum suppression. - * - */ - void configure(const ITensor *bboxes, const ITensor *scores, ITensor *indices, unsigned int max_output_size, const float score_threshold, const float nms_threshold); - - /** Static function to check if given arguments will lead to a valid configuration of @ref CPPNonMaximumSuppression - * - * @param[in] bboxes The input bounding boxes. Data types supported: F32. - * @param[in] scores The corresponding input confidence. Same as @p scores. - * @param[out] indices The kept indices of bboxes after nms. Data types supported: S32. - * @param[in] max_output_size An integer tensor representing the maximum number of boxes to be selected by non max suppression. - * @param[in] score_threshold The threshold used to filter detection results. - * @param[in] nms_threshold The threshold used in non maximum suppression. - * - */ - static Status validate(const ITensorInfo *bboxes, const ITensorInfo *scores, const ITensorInfo *indices, unsigned int max_output_size, - const float score_threshold, const float nms_threshold); - - // Inherited methods overridden: - void run() override; - /** Prevent instances of this class from being copied (As this class contains pointers) */ - CPPNonMaximumSuppression(const CPPNonMaximumSuppression &) = delete; - /** Prevent instances of this class from being copied (As this class contains pointers) */ - CPPNonMaximumSuppression &operator=(const CPPNonMaximumSuppression &) = delete; - -private: - const ITensor *_bboxes; - const ITensor *_scores; - ITensor *_indices; - unsigned int _max_output_size; - - float _score_threshold; - float _nms_threshold; -}; - /** CPP Function to generate the detection output based on location and confidence * predictions by doing non maximum suppression. * diff --git a/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp b/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp index 34a7294513..61005ab5fd 100644 --- a/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp +++ b/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018-2019 ARM Limited. + * Copyright (c) 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -34,7 +34,7 @@ namespace arm_compute { namespace { -Status detection_layer_validate_arguments(const ITensorInfo *input_loc, const ITensorInfo *input_conf, const ITensorInfo *input_priorbox, const ITensorInfo *output, DetectionOutputLayerInfo info) +Status validate_arguments(const ITensorInfo *input_loc, const ITensorInfo *input_conf, const ITensorInfo *input_priorbox, const ITensorInfo *output, DetectionOutputLayerInfo info) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input_loc, input_conf, input_priorbox, output); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input_loc, 1, DataType::F32); @@ -366,103 +366,14 @@ void ApplyNMSFast(const std::vector &bboxes, indices.push_back(idx); } score_index_vec.erase(score_index_vec.begin()); - if(keep && eta < 1.f && adaptive_threshold > 0.5f) + if(keep && eta < 1 && adaptive_threshold > 0.5) { adaptive_threshold *= eta; } } } - -Status non_max_suppression_validate_arguments(const ITensorInfo *bboxes, const ITensorInfo *scores, const ITensorInfo *indices, unsigned int max_output_size, - const float score_threshold, const float nms_threshold) -{ - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(bboxes, scores, indices); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(bboxes, 1, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(scores, 1, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(indices, 1, DataType::S32); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(bboxes->num_dimensions() > 2, "The bboxes tensor must be a 2-D float tensor of shape [4, num_boxes]."); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(scores->num_dimensions() > 1, "The scores tensor must be a 1-D float tensor of shape [num_boxes]."); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(indices->num_dimensions() > 1, "The indices must be 1-D integer tensor of shape [M], where max_output_size <= M"); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(bboxes, scores); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(scores->num_dimensions() > 1, "Scores must be a 1D float tensor"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(indices->dimension(0) == 0, "Indices tensor must be bigger than 0"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(max_output_size == 0, "Max size cannot be 0"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(nms_threshold < 0.f || nms_threshold > 1.f, "Threshould must be in [0,1]"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(score_threshold < 0.f || score_threshold > 1.f, "Threshould must be in [0,1]"); - - return Status{}; -} } // namespace -CPPNonMaximumSuppression::CPPNonMaximumSuppression() - : _bboxes(nullptr), _scores(nullptr), _indices(nullptr), _max_output_size(0), _score_threshold(0.f), _nms_threshold(0.f) -{ -} - -void CPPNonMaximumSuppression::configure( - const ITensor *bboxes, const ITensor *scores, ITensor *indices, unsigned int max_output_size, - const float score_threshold, const float nms_threshold) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(bboxes, scores, indices); - ARM_COMPUTE_ERROR_THROW_ON(non_max_suppression_validate_arguments(bboxes->info(), scores->info(), indices->info(), max_output_size, score_threshold, nms_threshold)); - - // copy scores also to a vector - _bboxes = bboxes; - _scores = scores; - _indices = indices; - - _nms_threshold = nms_threshold; - _max_output_size = max_output_size; - _score_threshold = score_threshold; -} - -Status CPPNonMaximumSuppression::validate( - const ITensorInfo *bboxes, const ITensorInfo *scores, const ITensorInfo *indices, unsigned int max_output_size, - const float score_threshold, const float nms_threshold) -{ - ARM_COMPUTE_RETURN_ON_ERROR(non_max_suppression_validate_arguments(bboxes, scores, indices, max_output_size, score_threshold, nms_threshold)); - return Status{}; -} - -void extract_bounding_boxes_from_tensor(const ITensor *bboxes, std::vector &bboxes_vector) -{ - Window input_win; - input_win.use_tensor_dimensions(bboxes->info()->tensor_shape()); - input_win.set_dimension_step(0U, 4U); - input_win.set_dimension_step(1U, 1U); - Iterator input(bboxes, input_win); - auto f = [&bboxes_vector, &input](const Coordinates &) - { - const auto input_ptr = reinterpret_cast(input.ptr()); - bboxes_vector.push_back(NormalizedBBox({ *input_ptr, *(input_ptr + 1), *(2 + input_ptr), *(3 + input_ptr) })); - }; - execute_window_loop(input_win, f, input); -} - -void extract_scores_from_tensor(const ITensor *scores, std::vector &scores_vector) -{ - Window window; - window.use_tensor_dimensions(scores->info()->tensor_shape()); - Iterator it(scores, window); - auto f = [&it, &scores_vector](const Coordinates &) - { - const auto input_ptr = reinterpret_cast(it.ptr()); - scores_vector.push_back(*input_ptr); - }; - execute_window_loop(window, f, it); -} - -void CPPNonMaximumSuppression::run() -{ - std::vector bboxes_vector; - std::vector scores_vector; - std::vector indices_vector; - extract_bounding_boxes_from_tensor(_bboxes, bboxes_vector); - extract_scores_from_tensor(_scores, scores_vector); - ApplyNMSFast(bboxes_vector, scores_vector, _score_threshold, _nms_threshold, 1, -1 /* disable top_k */, indices_vector); - std::copy_n(indices_vector.begin(), std::min(indices_vector.size(), _indices->info()->dimension(0)), reinterpret_cast(_indices->ptr_to_element(Coordinates(0)))); -} - CPPDetectionOutputLayer::CPPDetectionOutputLayer() : _input_loc(nullptr), _input_conf(nullptr), _input_priorbox(nullptr), _output(nullptr), _info(), _num_priors(), _num(), _all_location_predictions(), _all_confidence_scores(), _all_prior_bboxes(), _all_prior_variances(), _all_decode_bboxes(), _all_indices() @@ -480,7 +391,7 @@ void CPPDetectionOutputLayer::configure(const ITensor *input_loc, const ITensor auto_init_if_empty(*output->info(), input_loc->info()->clone()->set_tensor_shape(TensorShape(7U, max_size))); // Perform validation step - ARM_COMPUTE_ERROR_THROW_ON(detection_layer_validate_arguments(input_loc->info(), input_conf->info(), input_priorbox->info(), output->info(), info)); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input_loc->info(), input_conf->info(), input_priorbox->info(), output->info(), info)); _input_loc = input_loc; _input_conf = input_conf; @@ -518,7 +429,7 @@ void CPPDetectionOutputLayer::configure(const ITensor *input_loc, const ITensor Status CPPDetectionOutputLayer::validate(const ITensorInfo *input_loc, const ITensorInfo *input_conf, const ITensorInfo *input_priorbox, const ITensorInfo *output, DetectionOutputLayerInfo info) { - ARM_COMPUTE_RETURN_ON_ERROR(detection_layer_validate_arguments(input_loc, input_conf, input_priorbox, output, info)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input_loc, input_conf, input_priorbox, output, info)); return Status{}; } @@ -671,4 +582,4 @@ void CPPDetectionOutputLayer::run() } } } -} // namespace arm_compute +} // namespace arm_compute \ No newline at end of file diff --git a/tests/AssetsLibrary.h b/tests/AssetsLibrary.h index 366c1450ba..d09e22762d 100644 --- a/tests/AssetsLibrary.h +++ b/tests/AssetsLibrary.h @@ -207,9 +207,6 @@ public: template void fill(T &&tensor, D &&distribution, std::random_device::result_type seed_offset) const; - template - void fill_boxes(T &&tensor, D &&distribution, std::random_device::result_type seed_offset) const; - /** Fills the specified @p raw tensor with random values drawn from @p * distribution. * @@ -484,40 +481,6 @@ void AssetsLibrary::fill_borders_with_garbage(T &&tensor, D &&distribution, std: }); } -template -void AssetsLibrary::fill_boxes(T &&tensor, D &&distribution, std::random_device::result_type seed_offset) const -{ - using ResultType = typename std::remove_reference::type::result_type; - std::mt19937 gen(_seed + seed_offset); - TensorShape shape(tensor.shape()); - const int num_boxes = tensor.num_elements() / 4; - // Iterate over all elements - std::uniform_real_distribution<> size_dist(0.f, 1.f); - for(int element_idx = 0; element_idx < num_boxes * 4; element_idx += 4) - { - const ResultType delta = size_dist(gen); - const ResultType epsilon = size_dist(gen); - const ResultType left = distribution(gen); - const ResultType top = distribution(gen); - const ResultType right = left + delta; - const ResultType bottom = top + epsilon; - const std::tuple box(left, top, right, bottom); - Coordinates x1 = index2coord(shape, element_idx); - Coordinates y1 = index2coord(shape, element_idx + 1); - Coordinates x2 = index2coord(shape, element_idx + 2); - Coordinates y2 = index2coord(shape, element_idx + 3); - ResultType &target_value_x1 = reinterpret_cast(tensor(x1))[0]; - ResultType &target_value_y1 = reinterpret_cast(tensor(y1))[0]; - ResultType &target_value_x2 = reinterpret_cast(tensor(x2))[0]; - ResultType &target_value_y2 = reinterpret_cast(tensor(y2))[0]; - store_value_with_data_type(&target_value_x1, std::get<0>(box), tensor.data_type()); - store_value_with_data_type(&target_value_y1, std::get<1>(box), tensor.data_type()); - store_value_with_data_type(&target_value_x2, std::get<2>(box), tensor.data_type()); - store_value_with_data_type(&target_value_y2, std::get<3>(box), tensor.data_type()); - } - fill_borders_with_garbage(tensor, distribution, seed_offset); -} - template void AssetsLibrary::fill(T &&tensor, D &&distribution, std::random_device::result_type seed_offset) const { diff --git a/tests/datasets/ShapeDatasets.h b/tests/datasets/ShapeDatasets.h index f461d7f9d2..480df3c7eb 100644 --- a/tests/datasets/ShapeDatasets.h +++ b/tests/datasets/ShapeDatasets.h @@ -946,37 +946,6 @@ public: { } }; - -/** Data set containing small 2D tensor shapes. */ -class Small2DNonMaxSuppressionShapes final : public ShapeDataset -{ -public: - Small2DNonMaxSuppressionShapes() - : ShapeDataset("Shape", - { - TensorShape{ 4U, 7U }, - TensorShape{ 4U, 13U }, - TensorShape{ 4U, 64U } - }) - { - } -}; - -/** Data set containing large 2D tensor shapes. */ -class Large2DNonMaxSuppressionShapes final : public ShapeDataset -{ -public: - Large2DNonMaxSuppressionShapes() - : ShapeDataset("Shape", - { - TensorShape{ 4U, 207U }, - TensorShape{ 4U, 113U }, - TensorShape{ 4U, 264U } - }) - { - } -}; - } // namespace datasets } // namespace test } // namespace arm_compute diff --git a/tests/validation/CPP/NonMaximalSuppression.cpp b/tests/validation/CPP/NonMaximalSuppression.cpp deleted file mode 100644 index 6cd7b52066..0000000000 --- a/tests/validation/CPP/NonMaximalSuppression.cpp +++ /dev/null @@ -1,144 +0,0 @@ -/* - * Copyright (c) 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/Types.h" -#include "arm_compute/runtime/CPP/functions/CPPDetectionOutputLayer.h" -#include "arm_compute/runtime/Tensor.h" -#include "arm_compute/runtime/TensorAllocator.h" -#include "tests/NEON/Accessor.h" -#include "tests/PaddingCalculator.h" -#include "tests/datasets/ShapeDatasets.h" -#include "tests/framework/Asserts.h" -#include "tests/framework/Macros.h" -#include "tests/framework/datasets/Datasets.h" -#include "tests/validation/Validation.h" -#include "tests/validation/fixtures/NonMaxSuppressionFixture.h" - -namespace arm_compute -{ -namespace test -{ -namespace validation -{ -namespace -{ -const auto max_output_boxes_dataset = framework::dataset::make("MaxOutputBoxes", 1, 10); -const auto score_threshold_dataset = framework::dataset::make("ScoreThreshold", { 0.1f, 0.5f, 0.f, 1.f }); -const auto nms_threshold_dataset = framework::dataset::make("NMSThreshold", { 0.1f, 0.5f, 0.f, 1.f }); -const auto NMSParametersSmall = datasets::Small2DNonMaxSuppressionShapes() * max_output_boxes_dataset * score_threshold_dataset * nms_threshold_dataset; -const auto NMSParametersBig = datasets::Large2DNonMaxSuppressionShapes() * max_output_boxes_dataset * score_threshold_dataset * nms_threshold_dataset; - -} // namespace - -TEST_SUITE(CPP) -TEST_SUITE(NMS) - -// *INDENT-OFF* -// clang-format off -DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip( - framework::dataset::make("BoundingBox",{ - TensorInfo(TensorShape(4U, 100U), 1, DataType::F32), - TensorInfo(TensorShape(1U, 4U, 2U), 1, DataType::F32), // invalid shape - TensorInfo(TensorShape(4U, 2U), 1, DataType::S32), // invalid data type - TensorInfo(TensorShape(4U, 3U), 1, DataType::F32), - TensorInfo(TensorShape(4U, 66U), 1, DataType::F32), - TensorInfo(TensorShape(4U, 100U), 1, DataType::F32), - TensorInfo(TensorShape(4U, 100U), 1, DataType::F32), - TensorInfo(TensorShape(4U, 100U), 1, DataType::F32), - TensorInfo(TensorShape(4U, 100U), 1, DataType::F32), - TensorInfo(TensorShape(4U, 100U), 1, DataType::F32), - }), - framework::dataset::make("Scores", { - TensorInfo(TensorShape(100U), 1, DataType::F32), - TensorInfo(TensorShape(37U, 2U, 13U, 27U), 1, DataType::F32), // invalid shape - TensorInfo(TensorShape(4U), 1, DataType::F32), - TensorInfo(TensorShape(3U), 1, DataType::U8), // invalid data type - TensorInfo(TensorShape(66U), 1, DataType::F32), // invalid data type - TensorInfo(TensorShape(100U), 1, DataType::F32), - TensorInfo(TensorShape(100U), 1, DataType::F32), - TensorInfo(TensorShape(100U), 1, DataType::F32), - TensorInfo(TensorShape(100U), 1, DataType::F32), - TensorInfo(TensorShape(100U), 1, DataType::F32), - })), - framework::dataset::make("Indices", { - TensorInfo(TensorShape(100U), 1, DataType::S32), - TensorInfo(TensorShape(100U), 1, DataType::S32), - TensorInfo(TensorShape(4U), 1, DataType::S32), - TensorInfo(TensorShape(3U), 1, DataType::S32), - TensorInfo(TensorShape(200U), 1, DataType::S32), // indices bigger than max bbs, OK because max_output is 66 - TensorInfo(TensorShape(100U), 1, DataType::F32), // invalid data type - TensorInfo(TensorShape(100U), 1, DataType::S32), - TensorInfo(TensorShape(100U), 1, DataType::S32), - TensorInfo(TensorShape(100U), 1, DataType::S32), - TensorInfo(TensorShape(100U), 1, DataType::S32), - - })), - framework::dataset::make("max_output", { - 10U, 2U,4U, 3U,66U, 1U, - 0U, /* invalid, must be greater than 0 */ - 10000U, /* OK, clamped to indices' size */ - 100U, - 10U, - })), - framework::dataset::make("score_threshold", { - 0.1f, 0.4f, 0.2f,0.8f,0.3f, 0.01f, 0.5f, 0.45f, - -1.f, /* invalid value, must be in [0,1] */ - 0.5f, - })), - framework::dataset::make("nms_threshold", { - 0.3f, 0.7f, 0.1f,0.13f,0.2f, 0.97f, 0.76f, 0.87f, 0.1f, - 10.f, /* invalid value, must be in [0,1]*/ - })), - framework::dataset::make("Expected", { - true, false, false, false, true, false, false,true, false, false - })), - - bbox_info, scores_info, indices_info, max_out, score_threshold, nms_threshold, expected) -{ - ARM_COMPUTE_EXPECT(bool(CPPNonMaximumSuppression::validate(&bbox_info.clone()->set_is_resizable(false), - &scores_info.clone()->set_is_resizable(false), - &indices_info.clone()->set_is_resizable(false), - max_out,score_threshold,nms_threshold)) == expected, framework::LogLevel::ERRORS); -} -// clang-format on -// *INDENT-ON* - -using CPPNonMaxSuppressionFixture = NMSValidationFixture; - -FIXTURE_DATA_TEST_CASE(RunSmall, CPPNonMaxSuppressionFixture, framework::DatasetMode::PRECOMMIT, NMSParametersSmall) -{ - // Validate output - validate(Accessor(_target), _reference); -} - -FIXTURE_DATA_TEST_CASE(RunLarge, CPPNonMaxSuppressionFixture, framework::DatasetMode::NIGHTLY, NMSParametersBig) -{ - // Validate output - validate(Accessor(_target), _reference); -} - -TEST_SUITE_END() // CPP -TEST_SUITE_END() // NMS -} // namespace validation -} // namespace test -} // namespace arm_compute diff --git a/tests/validation/fixtures/NonMaxSuppressionFixture.h b/tests/validation/fixtures/NonMaxSuppressionFixture.h deleted file mode 100644 index 9299ed62a4..0000000000 --- a/tests/validation/fixtures/NonMaxSuppressionFixture.h +++ /dev/null @@ -1,124 +0,0 @@ -/* - * Copyright (c) 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. - */ -#ifndef ARM_COMPUTE_TEST_NON_MAX_SUPPRESSION_FIXTURE -#define ARM_COMPUTE_TEST_NON_MAX_SUPPRESSION_FIXTURE - -#include "arm_compute/core/Helpers.h" -#include "arm_compute/core/TensorShape.h" -#include "arm_compute/core/Types.h" -#include "arm_compute/runtime/Tensor.h" -#include "tests/AssetsLibrary.h" -#include "tests/Globals.h" -#include "tests/IAccessor.h" -#include "tests/framework/Asserts.h" -#include "tests/framework/Fixture.h" -#include "tests/validation/reference/NonMaxSuppression.h" - -namespace arm_compute -{ -namespace test -{ -namespace validation -{ -template - -class NMSValidationFixture : public framework::Fixture -{ -public: - template - void setup(TensorShape input_shape, unsigned int max_output_size, float score_threshold, float nms_threshold) - { - ARM_COMPUTE_ERROR_ON(max_output_size == 0); - ARM_COMPUTE_ERROR_ON(input_shape.num_dimensions() != 2); - const TensorShape output_shape(max_output_size); - const TensorShape scores_shape(input_shape[1]); - _target = compute_target(input_shape, scores_shape, output_shape, max_output_size, score_threshold, nms_threshold); - _reference = compute_reference(input_shape, scores_shape, output_shape, max_output_size, score_threshold, nms_threshold); - } - -protected: - template - void fill(U &&tensor, int i, int lo, int hi) - { - std::uniform_real_distribution<> distribution(lo, hi); - library->fill_boxes(tensor, distribution, i); - } - - TensorType compute_target(const TensorShape input_shape, const TensorShape scores_shape, const TensorShape output_shape, - unsigned int max_output_size, float score_threshold, float nms_threshold) - { - // Create tensors - TensorType bboxes = create_tensor(input_shape, DataType::F32); - TensorType scores = create_tensor(scores_shape, DataType::F32); - TensorType indices = create_tensor(output_shape, DataType::S32); - - // Create and configure function - FunctionType nms_func; - nms_func.configure(&bboxes, &scores, &indices, max_output_size, score_threshold, nms_threshold); - - ARM_COMPUTE_EXPECT(bboxes.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(indices.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(scores.info()->is_resizable(), framework::LogLevel::ERRORS); - - // Allocate tensors - bboxes.allocator()->allocate(); - indices.allocator()->allocate(); - scores.allocator()->allocate(); - - ARM_COMPUTE_EXPECT(!bboxes.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!indices.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!scores.info()->is_resizable(), framework::LogLevel::ERRORS); - - // Fill tensors - fill(AccessorType(bboxes), 0, 0.f, 1.f); - fill(AccessorType(scores), 1, 0.f, 1.f); - - // Compute function - nms_func.run(); - return indices; - } - - SimpleTensor compute_reference(const TensorShape input_shape, const TensorShape scores_shape, const TensorShape output_shape, - unsigned int max_output_size, float score_threshold, float nms_threshold) - { - // Create reference - SimpleTensor bboxes{ input_shape, DataType::F32 }; - SimpleTensor scores{ scores_shape, DataType::F32 }; - SimpleTensor indices{ output_shape, DataType::S32 }; - - // Fill reference - fill(bboxes, 0, 0.f, 1.f); - fill(scores, 1, 0.f, 1.f); - - return reference::non_max_suppression(bboxes, scores, indices, max_output_size, score_threshold, nms_threshold); - } - - TensorType _target{}; - SimpleTensor _reference{}; -}; - -} // namespace validation -} // namespace test -} // namespace arm_compute -#endif /* ARM_COMPUTE_TEST_NON_MAX_SUPPRESSION_FIXTURE */ diff --git a/tests/validation/reference/NonMaxSuppression.cpp b/tests/validation/reference/NonMaxSuppression.cpp deleted file mode 100644 index 013a26f645..0000000000 --- a/tests/validation/reference/NonMaxSuppression.cpp +++ /dev/null @@ -1,126 +0,0 @@ -/* - * Copyright (c) 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 "Permute.h" - -#include "arm_compute/core/Types.h" -#include "tests/validation/Helpers.h" -#include - -namespace arm_compute -{ -namespace test -{ -namespace validation -{ -namespace reference -{ -namespace -{ -inline float get_elem_by_coordinate(const SimpleTensor &tensor, Coordinates coord) -{ - return *static_cast(tensor(coord)); -} - -// Return intersection-over-union overlap between boxes i and j -inline bool iou_greater_than_threshold(const SimpleTensor &boxes, size_t i, size_t j, float iou_threshold) -{ - const float ymin_i = std::min(get_elem_by_coordinate(boxes, Coordinates(0, i)), get_elem_by_coordinate(boxes, Coordinates(2, i))); - const float xmin_i = std::min(get_elem_by_coordinate(boxes, Coordinates(1, i)), get_elem_by_coordinate(boxes, Coordinates(3, i))); - const float ymax_i = std::max(get_elem_by_coordinate(boxes, Coordinates(0, i)), get_elem_by_coordinate(boxes, Coordinates(2, i))); - const float xmax_i = std::max(get_elem_by_coordinate(boxes, Coordinates(1, i)), get_elem_by_coordinate(boxes, Coordinates(3, i))); - const float ymin_j = std::min(get_elem_by_coordinate(boxes, Coordinates(0, j)), get_elem_by_coordinate(boxes, Coordinates(2, j))); - const float xmin_j = std::min(get_elem_by_coordinate(boxes, Coordinates(1, j)), get_elem_by_coordinate(boxes, Coordinates(3, j))); - const float ymax_j = std::max(get_elem_by_coordinate(boxes, Coordinates(0, j)), get_elem_by_coordinate(boxes, Coordinates(2, j))); - const float xmax_j = std::max(get_elem_by_coordinate(boxes, Coordinates(1, j)), get_elem_by_coordinate(boxes, Coordinates(3, j))); - const float area_i = (ymax_i - ymin_i) * (xmax_i - xmin_i); - const float area_j = (ymax_j - ymin_j) * (xmax_j - xmin_j); - if(area_i <= 0 || area_j <= 0) - { - return false; - } - const float intersection_ymin = std::max(ymin_i, ymin_j); - const float intersection_xmin = std::max(xmin_i, xmin_j); - const float intersection_ymax = std::min(ymax_i, ymax_j); - const float intersection_xmax = std::min(xmax_i, xmax_j); - const float intersection_area = std::max(intersection_ymax - intersection_ymin, 0.0) * std::max(intersection_xmax - intersection_xmin, 0.0); - const float iou = intersection_area / (area_i + area_j - intersection_area); - return iou > iou_threshold; -} - -} // namespace - -SimpleTensor non_max_suppression(const SimpleTensor &bboxes, const SimpleTensor &scores, SimpleTensor &indices, - unsigned int max_output_size, float score_threshold, float nms_threshold) -{ - const size_t num_boxes = bboxes.shape().y(); - const size_t output_size = std::min(static_cast(max_output_size), num_boxes); - std::vector scores_data(num_boxes); - std::copy_n(scores.data(), num_boxes, scores_data.begin()); - - using CandidateBox = std::pair; - auto cmp = [](const CandidateBox bb0, const CandidateBox bb1) - { - return bb0.second < bb1.second; - }; - - std::priority_queue, decltype(cmp)> candidate_priority_queue(cmp); - for(size_t i = 0; i < scores_data.size(); ++i) - { - if(scores_data[i] > score_threshold) - { - candidate_priority_queue.emplace(CandidateBox({ i, scores_data[i] })); - } - } - - std::vector selected; - std::vector selected_scores; - CandidateBox next_candidate; - - while(selected.size() < output_size && !candidate_priority_queue.empty()) - { - next_candidate = candidate_priority_queue.top(); - candidate_priority_queue.pop(); - bool should_select = true; - for(int j = selected.size() - 1; j >= 0; --j) - { - if(iou_greater_than_threshold(bboxes, next_candidate.first, selected[j], nms_threshold)) - { - should_select = false; - break; - } - } - if(should_select) - { - selected.push_back(next_candidate.first); - selected_scores.push_back(next_candidate.second); - } - } - std::copy_n(selected.begin(), selected.size(), indices.data()); - return indices; -} - -} // namespace reference -} // namespace validation -} // namespace test -} // namespace arm_compute diff --git a/tests/validation/reference/NonMaxSuppression.h b/tests/validation/reference/NonMaxSuppression.h deleted file mode 100644 index 0418412939..0000000000 --- a/tests/validation/reference/NonMaxSuppression.h +++ /dev/null @@ -1,44 +0,0 @@ -/* - * Copyright (c) 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. - */ -#ifndef __ARM_COMPUTE_TEST_NON_MAX_SUPPRESION_H__ -#define __ARM_COMPUTE_TEST_NON_MAX_SUPPRESION_H__ - -#include "tests/SimpleTensor.h" - -namespace arm_compute -{ -namespace test -{ -namespace validation -{ -namespace reference -{ -SimpleTensor non_max_suppression(const SimpleTensor &bboxes, const SimpleTensor &scores, SimpleTensor &indices, - unsigned int max_output_size, float score_threshold, float nms_threshold); - -} // namespace reference -} // namespace validation -} // namespace test -} // namespace arm_compute -#endif /* __ARM_COMPUTE_TEST_NON_MAX_SUPPRESION_H__ */ -- cgit v1.2.1