/* * 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/CPPNonMaximumSuppression.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 iou_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 * iou_nms_threshold_dataset; const auto NMSParametersBig = datasets::Large2DNonMaxSuppressionShapes() * max_output_boxes_dataset * score_threshold_dataset * iou_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() // NMS TEST_SUITE_END() // CPP } // namespace validation } // namespace test } // namespace arm_compute