/* * Copyright (c) 2018-2019 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_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 { namespace { std::vector generate_deltas(std::vector &boxes, const TensorShape &image_shape, size_t num_boxes, size_t num_classes, std::mt19937 &gen) { std::vector deltas(num_boxes * 4 * num_classes); 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 float ex_width = boxes[4 * i + 2] - boxes[4 * i] + 1.f; const float ex_height = boxes[4 * i + 3] - boxes[4 * i + 1] + 1.f; const float ex_ctr_x = boxes[4 * i] + 0.5f * ex_width; const float ex_ctr_y = boxes[4 * i + 1] + 0.5f * ex_height; for(size_t j = 0; j < num_classes; ++j) { const float x1 = dist_x1(gen); const float y1 = dist_y1(gen); const float width = dist_w(gen); const float height = dist_h(gen); const float ctr_x = x1 + 0.5f * width; const float ctr_y = y1 + 0.5f * height; deltas[4 * num_classes * i + 4 * j] = (ctr_x - ex_ctr_x) / ex_width; deltas[4 * num_classes * i + 4 * j + 1] = (ctr_y - ex_ctr_y) / ex_height; deltas[4 * num_classes * i + 4 * j + 2] = log(width / ex_width); deltas[4 * num_classes * i + 4 * j + 3] = log(height / ex_height); } } return deltas; } std::vector generate_boxes(const TensorShape &image_shape, size_t num_boxes, std::mt19937 &gen) { std::vector boxes(num_boxes * 4); 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[4 * i] = dist_x1(gen); boxes[4 * i + 1] = dist_y1(gen); boxes[4 * i + 2] = boxes[4 * i] + dist_w(gen) - 1; boxes[4 * i + 3] = boxes[4 * i + 1] + dist_h(gen) - 1; } return boxes; } } // namespace template class BoundingBoxTransformGenericFixture : public framework::Fixture { public: using TDeltas = typename std::conditional::type, uint16_t>::value, uint8_t, T>::type; template void setup(TensorShape deltas_shape, const BoundingBoxTransformInfo &info, DataType data_type, QuantizationInfo deltas_qinfo) { const bool is_qasymm16 = data_type == DataType::QASYMM16; _data_type_deltas = (is_qasymm16) ? DataType::QASYMM8 : data_type; _boxes_qinfo = (is_qasymm16) ? QuantizationInfo(.125f, 0) : QuantizationInfo(); std::mt19937 gen_target(library->seed()); _target = compute_target(deltas_shape, data_type, info, gen_target, deltas_qinfo); std::mt19937 gen_reference(library->seed()); _reference = compute_reference(deltas_shape, data_type, info, gen_reference, deltas_qinfo); } protected: template void fill(U &&tensor, std::vector values) { data_type *data_ptr = reinterpret_cast(tensor.data()); switch(tensor.data_type()) { case DataType::QASYMM8: for(size_t i = 0; i < values.size(); ++i) { data_ptr[i] = quantize_qasymm8(values[i], tensor.quantization_info()); } break; case DataType::QASYMM16: for(size_t i = 0; i < values.size(); ++i) { data_ptr[i] = quantize_qasymm16(values[i], tensor.quantization_info()); } break; default: for(size_t i = 0; i < values.size(); ++i) { data_ptr[i] = static_cast(values[i]); } } } TensorType compute_target(const TensorShape &deltas_shape, DataType data_type, const BoundingBoxTransformInfo &bbox_info, std::mt19937 &gen, QuantizationInfo deltas_qinfo) { // Create tensors TensorShape boxes_shape(4, deltas_shape[1]); TensorType deltas = create_tensor(deltas_shape, _data_type_deltas, 1, deltas_qinfo); TensorType boxes = create_tensor(boxes_shape, data_type, 1, _boxes_qinfo); 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()); std::vector boxes_vec = generate_boxes(img_shape, boxes_shape[1], gen); std::vector deltas_vec = generate_deltas(boxes_vec, img_shape, deltas_shape[1], deltas_shape[0] / 4, gen); fill(AccessorType(boxes), boxes_vec); fill(AccessorType(deltas), deltas_vec); // Compute function bbox_transform.run(); return pred_boxes; } SimpleTensor compute_reference(const TensorShape &deltas_shape, DataType data_type, const BoundingBoxTransformInfo &bbox_info, std::mt19937 &gen, QuantizationInfo deltas_qinfo) { // Create reference tensor TensorShape boxes_shape(4, deltas_shape[1]); SimpleTensor boxes{ boxes_shape, data_type, 1, _boxes_qinfo }; SimpleTensor deltas{ deltas_shape, _data_type_deltas, 1, deltas_qinfo }; // Fill reference tensor TensorShape img_shape(bbox_info.scale() * bbox_info.img_width(), bbox_info.scale() * bbox_info.img_height()); std::vector boxes_vec = generate_boxes(img_shape, boxes_shape[1], gen); std::vector deltas_vec = generate_deltas(boxes_vec, img_shape, deltas_shape[1], deltas_shape[0] / 4, gen); fill(boxes, boxes_vec); fill(deltas, deltas_vec); return reference::bounding_box_transform(boxes, deltas, bbox_info); } TensorType _target{}; SimpleTensor _reference{}; DataType _data_type_deltas{}; QuantizationInfo _boxes_qinfo{}; private: }; template class BoundingBoxTransformFixture : public BoundingBoxTransformGenericFixture { public: template void setup(TensorShape deltas_shape, const BoundingBoxTransformInfo &info, DataType data_type) { BoundingBoxTransformGenericFixture::setup(deltas_shape, info, data_type, QuantizationInfo()); } private: }; template class BoundingBoxTransformQuantizedFixture : public BoundingBoxTransformGenericFixture { public: template void setup(TensorShape deltas_shape, const BoundingBoxTransformInfo &info, DataType data_type, QuantizationInfo deltas_qinfo) { BoundingBoxTransformGenericFixture::setup(deltas_shape, info, data_type, deltas_qinfo); } }; } // namespace validation } // namespace test } // namespace arm_compute #endif /* ARM_COMPUTE_TEST_BOUNDINGBOXTRANSFORM_FIXTURE */