| /* |
| * Copyright (c) 2019-2021 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 <typename TensorType, typename AccessorType, typename FunctionType> |
| |
| class NMSValidationFixture : public framework::Fixture |
| { |
| public: |
| template <typename...> |
| 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 <typename U> |
| void fill(U &&tensor, int i, float lo, float hi) |
| { |
| std::uniform_real_distribution<float> 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<TensorType>(input_shape, DataType::F32); |
| TensorType scores = create_tensor<TensorType>(scores_shape, DataType::F32); |
| TensorType indices = create_tensor<TensorType>(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_ASSERT(bboxes.info()->is_resizable()); |
| ARM_COMPUTE_ASSERT(indices.info()->is_resizable()); |
| ARM_COMPUTE_ASSERT(scores.info()->is_resizable()); |
| |
| // Allocate tensors |
| bboxes.allocator()->allocate(); |
| indices.allocator()->allocate(); |
| scores.allocator()->allocate(); |
| |
| ARM_COMPUTE_ASSERT(!bboxes.info()->is_resizable()); |
| ARM_COMPUTE_ASSERT(!indices.info()->is_resizable()); |
| ARM_COMPUTE_ASSERT(!scores.info()->is_resizable()); |
| |
| // 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<int> 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<float> bboxes{ input_shape, DataType::F32 }; |
| SimpleTensor<float> scores{ scores_shape, DataType::F32 }; |
| SimpleTensor<int> 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<int> _reference{}; |
| }; |
| |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |
| #endif /* ARM_COMPUTE_TEST_NON_MAX_SUPPRESSION_FIXTURE */ |