| /* |
| * 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_BOUNDINGBOXTRANSFORM_FIXTURE |
| #define ARM_COMPUTE_TEST_BOUNDINGBOXTRANSFORM_FIXTURE |
| |
| #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/framework/Asserts.h" |
| #include "tests/framework/Fixture.h" |
| #include "tests/validation/Helpers.h" |
| #include "tests/validation/reference/BoundingBoxTransform.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class BoundingBoxTransformFixture : public framework::Fixture |
| { |
| public: |
| template <typename...> |
| void setup(TensorShape deltas_shape, const BoundingBoxTransformInfo &info, DataType data_type) |
| { |
| std::mt19937 gen_target(library->seed()); |
| _target = compute_target(deltas_shape, data_type, info, gen_target); |
| |
| std::mt19937 gen_reference(library->seed()); |
| _reference = compute_reference(deltas_shape, data_type, info, gen_reference); |
| } |
| |
| protected: |
| TensorType compute_target(const TensorShape &deltas_shape, DataType data_type, |
| const BoundingBoxTransformInfo &bbox_info, std::mt19937 &gen) |
| { |
| // Create tensors |
| TensorShape boxes_shape(4, deltas_shape[1]); |
| TensorType deltas = create_tensor<TensorType>(deltas_shape, data_type); |
| TensorType boxes = create_tensor<TensorType>(boxes_shape, data_type); |
| TensorType pred_boxes; |
| |
| // Create and configure function |
| FunctionType bbox_transform; |
| bbox_transform.configure(&boxes, &pred_boxes, &deltas, bbox_info); |
| |
| ARM_COMPUTE_EXPECT(deltas.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(boxes.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(pred_boxes.info()->is_resizable(), framework::LogLevel::ERRORS); |
| |
| // Allocate tensors |
| deltas.allocator()->allocate(); |
| boxes.allocator()->allocate(); |
| pred_boxes.allocator()->allocate(); |
| |
| ARM_COMPUTE_EXPECT(!deltas.info()->is_resizable(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(!boxes.info()->is_resizable(), framework::LogLevel::ERRORS); |
| |
| // Fill tensors |
| TensorShape img_shape(bbox_info.scale() * bbox_info.img_width(), bbox_info.scale() * bbox_info.img_height()); |
| generate_boxes(AccessorType(boxes), img_shape, boxes_shape[1], gen); |
| generate_deltas(AccessorType(deltas), AccessorType(boxes), img_shape, deltas_shape[1], deltas_shape[0] / 4, gen); |
| |
| // Compute function |
| bbox_transform.run(); |
| |
| return pred_boxes; |
| } |
| |
| SimpleTensor<T> compute_reference(const TensorShape &deltas_shape, |
| DataType data_type, |
| const BoundingBoxTransformInfo &bbox_info, std::mt19937 &gen) |
| { |
| // Create reference tensor |
| TensorShape boxes_shape(4, deltas_shape[1]); |
| SimpleTensor<T> boxes{ boxes_shape, data_type }; |
| SimpleTensor<T> deltas{ deltas_shape, data_type }; |
| |
| // Fill reference tensor |
| TensorShape img_shape(bbox_info.scale() * bbox_info.img_width(), bbox_info.scale() * bbox_info.img_height()); |
| generate_boxes(boxes, img_shape, boxes_shape[1], gen); |
| generate_deltas(deltas, boxes, img_shape, deltas_shape[1], deltas_shape[0] / 4, gen); |
| |
| return reference::bounding_box_transform(boxes, deltas, bbox_info); |
| } |
| |
| TensorType _target{}; |
| SimpleTensor<T> _reference{}; |
| |
| private: |
| template <typename U> |
| void generate_deltas(U &&deltas, U &&boxes, const TensorShape &image_shape, size_t num_boxes, size_t num_classes, std::mt19937 &gen) |
| { |
| T *deltas_ptr = static_cast<T *>(deltas.data()); |
| T *boxes_ptr = static_cast<T *>(boxes.data()); |
| |
| std::uniform_int_distribution<> dist_x1(0, image_shape[0] - 1); |
| std::uniform_int_distribution<> dist_y1(0, image_shape[1] - 1); |
| std::uniform_int_distribution<> dist_w(1, image_shape[0]); |
| std::uniform_int_distribution<> dist_h(1, image_shape[1]); |
| |
| for(size_t i = 0; i < num_boxes; ++i) |
| { |
| const T ex_width = boxes_ptr[4 * i + 2] - boxes_ptr[4 * i] + T(1); |
| const T ex_height = boxes_ptr[4 * i + 3] - boxes_ptr[4 * i + 1] + T(1); |
| const T ex_ctr_x = boxes_ptr[4 * i] + T(0.5) * ex_width; |
| const T ex_ctr_y = boxes_ptr[4 * i + 1] + T(0.5) * ex_height; |
| |
| for(size_t j = 0; j < num_classes; ++j) |
| { |
| const T x1 = T(dist_x1(gen)); |
| const T y1 = T(dist_y1(gen)); |
| const T width = T(dist_w(gen)); |
| const T height = T(dist_h(gen)); |
| const T ctr_x = x1 + T(0.5) * width; |
| const T ctr_y = y1 + T(0.5) * height; |
| |
| deltas_ptr[4 * num_classes * i + 4 * j] = (ctr_x - ex_ctr_x) / ex_width; |
| deltas_ptr[4 * num_classes * i + 4 * j + 1] = (ctr_y - ex_ctr_y) / ex_height; |
| deltas_ptr[4 * num_classes * i + 4 * j + 2] = log(width / ex_width); |
| deltas_ptr[4 * num_classes * i + 4 * j + 3] = log(height / ex_height); |
| } |
| } |
| } |
| |
| template <typename U> |
| void generate_boxes(U &&boxes, const TensorShape &image_shape, size_t num_boxes, std::mt19937 &gen) |
| { |
| T *boxes_ptr = (T *)boxes.data(); |
| |
| std::uniform_int_distribution<> dist_x1(0, image_shape[0] - 1); |
| std::uniform_int_distribution<> dist_y1(0, image_shape[1] - 1); |
| std::uniform_int_distribution<> dist_w(1, image_shape[0]); |
| std::uniform_int_distribution<> dist_h(1, image_shape[1]); |
| |
| for(size_t i = 0; i < num_boxes; ++i) |
| { |
| boxes_ptr[4 * i] = dist_x1(gen); |
| boxes_ptr[4 * i + 1] = dist_y1(gen); |
| boxes_ptr[4 * i + 2] = boxes_ptr[4 * i] + dist_w(gen) - 1; |
| boxes_ptr[4 * i + 3] = boxes_ptr[4 * i + 1] + dist_h(gen) - 1; |
| } |
| } |
| }; |
| |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |
| #endif /* ARM_COMPUTE_TEST_BOUNDINGBOXTRANSFORM_FIXTURE */ |