| /* |
| * Copyright (c) 2017 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 "AssetsLibrary.h" |
| #include "Globals.h" |
| #include "NEON/Accessor.h" |
| #include "NEON/Helper.h" |
| #include "TypePrinter.h" |
| #include "Utils.h" |
| #include "validation/Datasets.h" |
| #include "validation/Reference.h" |
| #include "validation/Validation.h" |
| #include "validation/ValidationUserConfiguration.h" |
| |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/runtime/NEON/functions/NEHarrisCorners.h" |
| #include "arm_compute/runtime/Tensor.h" |
| #include "arm_compute/runtime/TensorAllocator.h" |
| |
| #include "PaddingCalculator.h" |
| #include "boost_wrapper.h" |
| |
| #include <random> |
| #include <string> |
| |
| using namespace arm_compute; |
| using namespace arm_compute::test; |
| using namespace arm_compute::test::validation; |
| |
| namespace |
| { |
| /** Compute Neon Harris corners function. |
| * |
| * @param[in] shape Shape of input tensor |
| * @param[in] threshold Minimum threshold with which to eliminate Harris Corner scores (computed using the normalized Sobel kernel). |
| * @param[in] min_dist Radial Euclidean distance for the euclidean distance stage |
| * @param[in] sensitivity Sensitivity threshold k from the Harris-Stephens equation |
| * @param[in] gradient_size The gradient window size to use on the input. The implementation supports 3, 5, and 7 |
| * @param[in] block_size The block window size used to compute the Harris Corner score. The implementation supports 3, 5, and 7. |
| * @param[in] border_mode Border mode to use |
| * @param[in] constant_border_value Constant value to use for borders if border_mode is set to CONSTANT. |
| * @param[in] use_fp16 If true the FP16 kernels will be used. If false F32 kernels are used. |
| * |
| * @return Computed corners' keypoints. |
| */ |
| KeyPointArray compute_harris_corners(const TensorShape &shape, float threshold, float min_dist, float sensitivity, |
| int32_t gradient_size, int32_t block_size, BorderMode border_mode, uint8_t constant_border_value, bool use_fp16) |
| { |
| // Create tensors |
| Tensor src = create_tensor<Tensor>(shape, DataType::U8); |
| src.info()->set_format(Format::U8); |
| |
| // Create array of keypoints |
| KeyPointArray corners(shape.total_size()); |
| |
| // Create harris corners configure function |
| NEHarrisCorners harris_corners; |
| harris_corners.configure(&src, threshold, min_dist, sensitivity, gradient_size, block_size, &corners, border_mode, constant_border_value, use_fp16); |
| |
| // Allocate tensors |
| src.allocator()->allocate(); |
| |
| BOOST_TEST(!src.info()->is_resizable()); |
| |
| // Fill tensors |
| library->fill_tensor_uniform(Accessor(src), 0); |
| |
| // Compute function |
| harris_corners.run(); |
| |
| return corners; |
| } |
| } // namespace |
| |
| #ifndef DOXYGEN_SKIP_THIS |
| BOOST_AUTO_TEST_SUITE(NEON) |
| BOOST_AUTO_TEST_SUITE(HarrisCorners) |
| |
| BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly")) |
| BOOST_DATA_TEST_CASE(Configuration, (Small2DShapes() + Large2DShapes()) * BorderModes() |
| * boost::unit_test::data::make({ 3, 5, 7 }) * boost::unit_test::data::make({ 3, 5, 7 }), |
| shape, border_mode, gradient, block) |
| { |
| // Create tensors |
| Tensor src = create_tensor<Tensor>(shape, DataType::U8); |
| src.info()->set_format(Format::U8); |
| |
| KeyPointArray corners; |
| |
| uint8_t constant_border_value = 0; |
| |
| std::mt19937 gen(user_config.seed.get()); |
| std::uniform_real_distribution<float> real_dist(0.01, std::numeric_limits<float>::min()); |
| |
| const float threshold = real_dist(gen); |
| const float sensitivity = real_dist(gen); |
| const float max_euclidean_distance = 30.f; |
| |
| real_dist = std::uniform_real_distribution<float>(0.f, max_euclidean_distance); |
| const float min_dist = real_dist(gen); |
| |
| // 50% chance to use fp16 |
| bool use_fp16 = real_dist(gen) < max_euclidean_distance / 2 ? true : false; |
| |
| // Generate a random constant value if border_mode is constant |
| if(border_mode == BorderMode::CONSTANT) |
| { |
| std::uniform_int_distribution<uint8_t> int_dist(0, 255); |
| constant_border_value = int_dist(gen); |
| } |
| |
| BOOST_TEST(src.info()->is_resizable()); |
| |
| // Create harris corners configure function |
| NEHarrisCorners harris_corners; |
| harris_corners.configure(&src, threshold, min_dist, sensitivity, gradient, block, &corners, border_mode, constant_border_value, use_fp16); |
| |
| // Validate valid region |
| const ValidRegion valid_region = shape_to_valid_region(shape); |
| |
| validate(src.info()->valid_region(), valid_region); |
| |
| // Validate padding |
| PaddingCalculator calculator(shape.x(), 8); |
| |
| calculator.set_border_mode(border_mode); |
| calculator.set_border_size(gradient / 2); |
| calculator.set_access_offset(-gradient / 2); |
| calculator.set_accessed_elements(16); |
| |
| const PaddingSize padding = calculator.required_padding(); |
| |
| validate(src.info()->padding(), padding); |
| } |
| |
| BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit")) |
| BOOST_DATA_TEST_CASE(RunSmall, Small2DShapes() * BorderModes() * boost::unit_test::data::make({ 3, 5, 7 }) * boost::unit_test::data::make({ 3, 5, 7 }), shape, border_mode, gradient, block) |
| { |
| uint8_t constant_border_value = 0; |
| |
| std::mt19937 gen(user_config.seed.get()); |
| std::uniform_real_distribution<float> real_dist(0.01, std::numeric_limits<float>::min()); |
| |
| const float threshold = real_dist(gen); |
| const float sensitivity = real_dist(gen); |
| const float max_euclidean_distance = 30.f; |
| |
| real_dist = std::uniform_real_distribution<float>(0.f, max_euclidean_distance); |
| const float min_dist = real_dist(gen); |
| |
| // 50% chance to use fp16 |
| bool use_fp16 = real_dist(gen) < max_euclidean_distance / 2 ? true : false; |
| |
| // Generate a random constant value if border_mode is constant |
| if(border_mode == BorderMode::CONSTANT) |
| { |
| std::uniform_int_distribution<uint8_t> int_dist(0, 255); |
| constant_border_value = int_dist(gen); |
| } |
| |
| // Compute function |
| KeyPointArray dst = compute_harris_corners(shape, threshold, min_dist, sensitivity, gradient, block, border_mode, constant_border_value, use_fp16); |
| |
| // Compute reference |
| KeyPointArray ref_dst = Reference::compute_reference_harris_corners(shape, threshold, min_dist, sensitivity, gradient, block, border_mode, constant_border_value); |
| |
| // Validate output |
| validate(dst, ref_dst); |
| } |
| |
| BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly")) |
| BOOST_DATA_TEST_CASE(RunLarge, Large2DShapes() * BorderModes() * boost::unit_test::data::make({ 3, 5, 7 }) * boost::unit_test::data::make({ 3, 5, 7 }), shape, border_mode, gradient, block) |
| { |
| uint8_t constant_border_value = 0; |
| |
| std::mt19937 gen(user_config.seed.get()); |
| std::uniform_real_distribution<float> real_dist(0.01, std::numeric_limits<float>::min()); |
| |
| const float threshold = real_dist(gen); |
| const float sensitivity = real_dist(gen); |
| const float max_euclidean_distance = 30.f; |
| |
| real_dist = std::uniform_real_distribution<float>(0.f, max_euclidean_distance); |
| float min_dist = real_dist(gen); |
| |
| // 50% chance to use fp16 |
| bool use_fp16 = real_dist(gen) < max_euclidean_distance / 2 ? true : false; |
| |
| // Generate a random constant value if border_mode is constant |
| if(border_mode == BorderMode::CONSTANT) |
| { |
| std::uniform_int_distribution<uint8_t> int_dist(0, 255); |
| constant_border_value = int_dist(gen); |
| } |
| |
| // Compute function |
| KeyPointArray dst = compute_harris_corners(shape, threshold, min_dist, sensitivity, gradient, block, border_mode, constant_border_value, use_fp16); |
| |
| // Compute reference |
| KeyPointArray ref_dst = Reference::compute_reference_harris_corners(shape, threshold, min_dist, sensitivity, gradient, block, border_mode, constant_border_value); |
| |
| // Validate output |
| validate(dst, ref_dst); |
| } |
| |
| BOOST_AUTO_TEST_SUITE_END() |
| BOOST_AUTO_TEST_SUITE_END() |
| #endif /* DOXYGEN_SKIP_THIS */ |