giuros01 | c04a0e8 | 2018-10-03 12:44:35 +0100 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 2018 ARM Limited. |
| 3 | * |
| 4 | * SPDX-License-Identifier: MIT |
| 5 | * |
| 6 | * Permission is hereby granted, free of charge, to any person obtaining a copy |
| 7 | * of this software and associated documentation files (the "Software"), to |
| 8 | * deal in the Software without restriction, including without limitation the |
| 9 | * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| 10 | * sell copies of the Software, and to permit persons to whom the Software is |
| 11 | * furnished to do so, subject to the following conditions: |
| 12 | * |
| 13 | * The above copyright notice and this permission notice shall be included in all |
| 14 | * copies or substantial portions of the Software. |
| 15 | * |
| 16 | * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| 17 | * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| 18 | * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| 19 | * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| 20 | * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| 21 | * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| 22 | * SOFTWARE. |
| 23 | */ |
| 24 | #ifndef ARM_COMPUTE_TEST_BOUNDINGBOXTRANSFORM_FIXTURE |
| 25 | #define ARM_COMPUTE_TEST_BOUNDINGBOXTRANSFORM_FIXTURE |
| 26 | |
| 27 | #include "arm_compute/core/TensorShape.h" |
| 28 | #include "arm_compute/core/Types.h" |
| 29 | #include "tests/AssetsLibrary.h" |
| 30 | #include "tests/Globals.h" |
| 31 | #include "tests/IAccessor.h" |
| 32 | #include "tests/framework/Asserts.h" |
| 33 | #include "tests/framework/Fixture.h" |
| 34 | #include "tests/validation/Helpers.h" |
| 35 | #include "tests/validation/reference/BoundingBoxTransform.h" |
| 36 | |
| 37 | namespace arm_compute |
| 38 | { |
| 39 | namespace test |
| 40 | { |
| 41 | namespace validation |
| 42 | { |
| 43 | template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| 44 | class BoundingBoxTransformFixture : public framework::Fixture |
| 45 | { |
| 46 | public: |
| 47 | template <typename...> |
| 48 | void setup(TensorShape deltas_shape, const BoundingBoxTransformInfo &info, DataType data_type) |
| 49 | { |
| 50 | std::mt19937 gen_target(library->seed()); |
| 51 | _target = compute_target(deltas_shape, data_type, info, gen_target); |
| 52 | |
| 53 | std::mt19937 gen_reference(library->seed()); |
| 54 | _reference = compute_reference(deltas_shape, data_type, info, gen_reference); |
| 55 | } |
| 56 | |
| 57 | protected: |
| 58 | TensorType compute_target(const TensorShape &deltas_shape, DataType data_type, |
| 59 | const BoundingBoxTransformInfo &bbox_info, std::mt19937 &gen) |
| 60 | { |
| 61 | // Create tensors |
| 62 | TensorShape boxes_shape(4, deltas_shape[1]); |
| 63 | TensorType deltas = create_tensor<TensorType>(deltas_shape, data_type); |
| 64 | TensorType boxes = create_tensor<TensorType>(boxes_shape, data_type); |
| 65 | TensorType pred_boxes; |
| 66 | |
| 67 | // Create and configure function |
| 68 | FunctionType bbox_transform; |
| 69 | bbox_transform.configure(&boxes, &pred_boxes, &deltas, bbox_info); |
| 70 | |
| 71 | ARM_COMPUTE_EXPECT(deltas.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 72 | ARM_COMPUTE_EXPECT(boxes.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 73 | ARM_COMPUTE_EXPECT(pred_boxes.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 74 | |
| 75 | // Allocate tensors |
| 76 | deltas.allocator()->allocate(); |
| 77 | boxes.allocator()->allocate(); |
| 78 | pred_boxes.allocator()->allocate(); |
| 79 | |
| 80 | ARM_COMPUTE_EXPECT(!deltas.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 81 | ARM_COMPUTE_EXPECT(!boxes.info()->is_resizable(), framework::LogLevel::ERRORS); |
| 82 | |
| 83 | // Fill tensors |
| 84 | TensorShape img_shape(bbox_info.scale() * bbox_info.img_width(), bbox_info.scale() * bbox_info.img_height()); |
| 85 | generate_boxes(AccessorType(boxes), img_shape, boxes_shape[1], gen); |
| 86 | generate_deltas(AccessorType(deltas), AccessorType(boxes), img_shape, deltas_shape[1], deltas_shape[0] / 4, gen); |
| 87 | |
| 88 | // Compute function |
| 89 | bbox_transform.run(); |
| 90 | |
| 91 | return pred_boxes; |
| 92 | } |
| 93 | |
| 94 | SimpleTensor<T> compute_reference(const TensorShape &deltas_shape, |
| 95 | DataType data_type, |
| 96 | const BoundingBoxTransformInfo &bbox_info, std::mt19937 &gen) |
| 97 | { |
| 98 | // Create reference tensor |
| 99 | TensorShape boxes_shape(4, deltas_shape[1]); |
| 100 | SimpleTensor<T> boxes{ boxes_shape, data_type }; |
| 101 | SimpleTensor<T> deltas{ deltas_shape, data_type }; |
| 102 | |
| 103 | // Fill reference tensor |
| 104 | TensorShape img_shape(bbox_info.scale() * bbox_info.img_width(), bbox_info.scale() * bbox_info.img_height()); |
| 105 | generate_boxes(boxes, img_shape, boxes_shape[1], gen); |
| 106 | generate_deltas(deltas, boxes, img_shape, deltas_shape[1], deltas_shape[0] / 4, gen); |
| 107 | |
| 108 | return reference::bounding_box_transform(boxes, deltas, bbox_info); |
| 109 | } |
| 110 | |
| 111 | TensorType _target{}; |
| 112 | SimpleTensor<T> _reference{}; |
| 113 | |
| 114 | private: |
| 115 | template <typename U> |
| 116 | void generate_deltas(U &&deltas, U &&boxes, const TensorShape &image_shape, size_t num_boxes, size_t num_classes, std::mt19937 &gen) |
| 117 | { |
| 118 | T *deltas_ptr = static_cast<T *>(deltas.data()); |
| 119 | T *boxes_ptr = static_cast<T *>(boxes.data()); |
| 120 | |
| 121 | std::uniform_int_distribution<> dist_x1(0, image_shape[0] - 1); |
| 122 | std::uniform_int_distribution<> dist_y1(0, image_shape[1] - 1); |
| 123 | std::uniform_int_distribution<> dist_w(1, image_shape[0]); |
| 124 | std::uniform_int_distribution<> dist_h(1, image_shape[1]); |
| 125 | |
| 126 | for(size_t i = 0; i < num_boxes; ++i) |
| 127 | { |
| 128 | const T ex_width = boxes_ptr[4 * i + 2] - boxes_ptr[4 * i] + T(1); |
| 129 | const T ex_height = boxes_ptr[4 * i + 3] - boxes_ptr[4 * i + 1] + T(1); |
| 130 | const T ex_ctr_x = boxes_ptr[4 * i] + T(0.5) * ex_width; |
| 131 | const T ex_ctr_y = boxes_ptr[4 * i + 1] + T(0.5) * ex_height; |
| 132 | |
| 133 | for(size_t j = 0; j < num_classes; ++j) |
| 134 | { |
| 135 | const T x1 = T(dist_x1(gen)); |
| 136 | const T y1 = T(dist_y1(gen)); |
| 137 | const T width = T(dist_w(gen)); |
| 138 | const T height = T(dist_h(gen)); |
| 139 | const T ctr_x = x1 + T(0.5) * width; |
| 140 | const T ctr_y = y1 + T(0.5) * height; |
| 141 | |
| 142 | deltas_ptr[4 * num_classes * i + 4 * j] = (ctr_x - ex_ctr_x) / ex_width; |
| 143 | deltas_ptr[4 * num_classes * i + 4 * j + 1] = (ctr_y - ex_ctr_y) / ex_height; |
| 144 | deltas_ptr[4 * num_classes * i + 4 * j + 2] = log(width / ex_width); |
| 145 | deltas_ptr[4 * num_classes * i + 4 * j + 3] = log(height / ex_height); |
| 146 | } |
| 147 | } |
| 148 | } |
| 149 | |
| 150 | template <typename U> |
| 151 | void generate_boxes(U &&boxes, const TensorShape &image_shape, size_t num_boxes, std::mt19937 &gen) |
| 152 | { |
| 153 | T *boxes_ptr = (T *)boxes.data(); |
| 154 | |
| 155 | std::uniform_int_distribution<> dist_x1(0, image_shape[0] - 1); |
| 156 | std::uniform_int_distribution<> dist_y1(0, image_shape[1] - 1); |
| 157 | std::uniform_int_distribution<> dist_w(1, image_shape[0]); |
| 158 | std::uniform_int_distribution<> dist_h(1, image_shape[1]); |
| 159 | |
| 160 | for(size_t i = 0; i < num_boxes; ++i) |
| 161 | { |
| 162 | boxes_ptr[4 * i] = dist_x1(gen); |
| 163 | boxes_ptr[4 * i + 1] = dist_y1(gen); |
| 164 | boxes_ptr[4 * i + 2] = boxes_ptr[4 * i] + dist_w(gen) - 1; |
| 165 | boxes_ptr[4 * i + 3] = boxes_ptr[4 * i + 1] + dist_h(gen) - 1; |
| 166 | } |
| 167 | } |
| 168 | }; |
| 169 | |
| 170 | } // namespace validation |
| 171 | } // namespace test |
| 172 | } // namespace arm_compute |
| 173 | #endif /* ARM_COMPUTE_TEST_BOUNDINGBOXTRANSFORM_FIXTURE */ |