tests/validation_old/CL/HarrisCorners.cpp - ml/ComputeLibrary - Gitiles

 /*
  * 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 "CL/CLAccessor.h"
 #include "TypePrinter.h"
 #include "Utils.h"
 #include "tests/AssetsLibrary.h"
 #include "tests/Globals.h"
 #include "tests/validation_old/Datasets.h"
 #include "tests/validation_old/Reference.h"
 #include "tests/validation_old/Validation.h"
 #include "tests/validation_old/ValidationUserConfiguration.h"

 #include "arm_compute/core/Helpers.h"
 #include "arm_compute/core/Types.h"
 #include "arm_compute/runtime/CL/CLArray.h"
 #include "arm_compute/runtime/CL/functions/CLHarrisCorners.h"
 #include "arm_compute/runtime/Tensor.h"
 #include "arm_compute/runtime/TensorAllocator.h"

 #include "PaddingCalculator.h"
 #include "tests/validation_old/boost_wrapper.h"

 #include <random>
 #include <string>

 using namespace arm_compute;
 using namespace arm_compute::test;
 using namespace arm_compute::test::validation;

 namespace
 {
 /** Compute CL 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.
  *
  * @return Computed corners' keypoints.
  */
 void compute_harris_corners(const TensorShape &shape, CLKeyPointArray &corners, float threshold, float min_dist, float sensitivity,
                             int32_t gradient_size, int32_t block_size, BorderMode border_mode, uint8_t constant_border_value)
 {
     // Create tensors
     CLTensor src = create_tensor<CLTensor>(shape, DataType::U8);
     src.info()->set_format(Format::U8);

     // Create harris corners configure function
     CLHarrisCorners harris_corners;
     harris_corners.configure(&src, threshold, min_dist, sensitivity, gradient_size, block_size, &corners, border_mode, constant_border_value);

     // Allocate tensors
     src.allocator()->allocate();

     BOOST_TEST(!src.info()->is_resizable());

     // Fill tensors
     library->fill_tensor_uniform(CLAccessor(src), 0);

     // Compute function
     harris_corners.run();
 }
 } // namespace

 #ifndef DOXYGEN_SKIP_THIS
 BOOST_AUTO_TEST_SUITE(CL)
 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
     CLTensor src = create_tensor<CLTensor>(shape, DataType::U8);
     src.info()->set_format(Format::U8);

     CLKeyPointArray corners(shape.total_size());

     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);

     // 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
     CLHarrisCorners harris_corners;
     harris_corners.configure(&src, threshold, min_dist, sensitivity, gradient, block, &corners, border_mode, constant_border_value);

     // 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);

     // 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);
     }

     // Create array of keypoints
     CLKeyPointArray dst(shape.total_size());

     // Compute function
     compute_harris_corners(shape, dst, threshold, min_dist, sensitivity, gradient, block, border_mode, constant_border_value);

     // Compute reference
     KeyPointArray ref_dst = Reference::compute_reference_harris_corners(shape, threshold, min_dist, sensitivity, gradient, block, border_mode, constant_border_value);

     // Validate output
     dst.map();
     validate(dst, ref_dst, 1);
     dst.unmap();
 }

 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);
     const float min_dist = real_dist(gen);

     // 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);
     }

     // Create array of keypoints
     CLKeyPointArray dst(shape.total_size());

     // Compute function
     compute_harris_corners(shape, dst, threshold, min_dist, sensitivity, gradient, block, border_mode, constant_border_value);

     // Compute reference
     KeyPointArray ref_dst = Reference::compute_reference_harris_corners(shape, threshold, min_dist, sensitivity, gradient, block, border_mode, constant_border_value);

     // Validate output
     dst.map();
     validate(dst, ref_dst);
     dst.unmap();
 }

 BOOST_AUTO_TEST_SUITE_END()
 BOOST_AUTO_TEST_SUITE_END()
 #endif /* DOXYGEN_SKIP_THIS */
	/*
	* 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 "CL/CLAccessor.h"
	#include "TypePrinter.h"
	#include "Utils.h"
	#include "tests/AssetsLibrary.h"
	#include "tests/Globals.h"
	#include "tests/validation_old/Datasets.h"
	#include "tests/validation_old/Reference.h"
	#include "tests/validation_old/Validation.h"
	#include "tests/validation_old/ValidationUserConfiguration.h"

	#include "arm_compute/core/Helpers.h"
	#include "arm_compute/core/Types.h"
	#include "arm_compute/runtime/CL/CLArray.h"
	#include "arm_compute/runtime/CL/functions/CLHarrisCorners.h"
	#include "arm_compute/runtime/Tensor.h"
	#include "arm_compute/runtime/TensorAllocator.h"

	#include "PaddingCalculator.h"
	#include "tests/validation_old/boost_wrapper.h"

	#include <random>
	#include <string>

	using namespace arm_compute;
	using namespace arm_compute::test;
	using namespace arm_compute::test::validation;

	namespace
	{
	/** Compute CL 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.
	*
	* @return Computed corners' keypoints.
	*/
	void compute_harris_corners(const TensorShape &shape, CLKeyPointArray &corners, float threshold, float min_dist, float sensitivity,
	int32_t gradient_size, int32_t block_size, BorderMode border_mode, uint8_t constant_border_value)
	{
	// Create tensors
	CLTensor src = create_tensor<CLTensor>(shape, DataType::U8);
	src.info()->set_format(Format::U8);

	// Create harris corners configure function
	CLHarrisCorners harris_corners;
	harris_corners.configure(&src, threshold, min_dist, sensitivity, gradient_size, block_size, &corners, border_mode, constant_border_value);

	// Allocate tensors
	src.allocator()->allocate();

	BOOST_TEST(!src.info()->is_resizable());

	// Fill tensors
	library->fill_tensor_uniform(CLAccessor(src), 0);

	// Compute function
	harris_corners.run();
	}
	} // namespace

	#ifndef DOXYGEN_SKIP_THIS
	BOOST_AUTO_TEST_SUITE(CL)
	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
	CLTensor src = create_tensor<CLTensor>(shape, DataType::U8);
	src.info()->set_format(Format::U8);

	CLKeyPointArray corners(shape.total_size());

	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);

	// 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
	CLHarrisCorners harris_corners;
	harris_corners.configure(&src, threshold, min_dist, sensitivity, gradient, block, &corners, border_mode, constant_border_value);

	// 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);

	// 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);
	}

	// Create array of keypoints
	CLKeyPointArray dst(shape.total_size());

	// Compute function
	compute_harris_corners(shape, dst, threshold, min_dist, sensitivity, gradient, block, border_mode, constant_border_value);

	// Compute reference
	KeyPointArray ref_dst = Reference::compute_reference_harris_corners(shape, threshold, min_dist, sensitivity, gradient, block, border_mode, constant_border_value);

	// Validate output
	dst.map();
	validate(dst, ref_dst, 1);
	dst.unmap();
	}

	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);
	const float min_dist = real_dist(gen);

	// 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);
	}

	// Create array of keypoints
	CLKeyPointArray dst(shape.total_size());

	// Compute function
	compute_harris_corners(shape, dst, threshold, min_dist, sensitivity, gradient, block, border_mode, constant_border_value);

	// Compute reference
	KeyPointArray ref_dst = Reference::compute_reference_harris_corners(shape, threshold, min_dist, sensitivity, gradient, block, border_mode, constant_border_value);

	// Validate output
	dst.map();
	validate(dst, ref_dst);
	dst.unmap();
	}

	BOOST_AUTO_TEST_SUITE_END()
	BOOST_AUTO_TEST_SUITE_END()
	#endif /* DOXYGEN_SKIP_THIS */