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/*
* Copyright (c) 2017, 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_HOG_DESCRIPTOR_FIXTURE
#define ARM_COMPUTE_TEST_HOG_DESCRIPTOR_FIXTURE
#include "arm_compute/core/HOGInfo.h"
#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/reference/HOGDescriptor.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
template <typename TensorType, typename HOGType, typename AccessorType, typename FunctionType, typename T, typename U>
class HOGDescriptorValidationFixture : public framework::Fixture
{
public:
template <typename...>
void setup(std::string image, HOGInfo hog_info, Format format, BorderMode border_mode)
{
// Only defined borders supported
ARM_COMPUTE_ERROR_ON(border_mode == BorderMode::UNDEFINED);
// Generate a random constant value
std::mt19937 gen(library->seed());
std::uniform_int_distribution<T> int_dist(0, 255);
const T constant_border_value = int_dist(gen);
_target = compute_target(image, format, border_mode, constant_border_value, hog_info);
_reference = compute_reference(image, format, border_mode, constant_border_value, hog_info);
}
protected:
template <typename V>
void fill(V &&tensor, const std::string image, Format format)
{
library->fill(tensor, image, format);
}
template <typename V, typename D>
void fill(V &&tensor, int i, D max)
{
library->fill_tensor_uniform(tensor, i, static_cast<D>(0), max);
}
TensorType compute_target(const std::string image, Format &format, BorderMode &border_mode, T constant_border_value, const HOGInfo &hog_info)
{
// Get image shape for src tensor
TensorShape shape = library->get_image_shape(image);
// Create tensor info for HOG descriptor
TensorInfo tensor_info_hog_descriptor(hog_info, shape.x(), shape.y());
// Create HOG
HOGType hog = create_HOG<HOGType>(hog_info.cell_size(),
hog_info.block_size(),
hog_info.detection_window_size(),
hog_info.block_stride(),
hog_info.num_bins(),
hog_info.normalization_type(),
hog_info.l2_hyst_threshold(),
hog_info.phase_type());
// Create tensors
TensorType src = create_tensor<TensorType>(shape, data_type_from_format(format));
TensorType dst = create_tensor<TensorType>(tensor_info_hog_descriptor.tensor_shape(), DataType::F32, tensor_info_hog_descriptor.num_channels());
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
// Create and configure function
FunctionType hog_descriptor;
hog_descriptor.configure(&src, &dst, &hog, border_mode, constant_border_value);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
// Allocate tensors
src.allocator()->allocate();
dst.allocator()->allocate();
ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
const T max = std::numeric_limits<T>::max();
// Fill tensors
fill(AccessorType(src), image, format);
fill(AccessorType(dst), 1, static_cast<U>(max));
// Compute function
hog_descriptor.run();
return dst;
}
SimpleTensor<U> compute_reference(const std::string image, Format format, BorderMode border_mode, T constant_border_value, const HOGInfo &hog_info)
{
// Create reference
SimpleTensor<T> src{ library->get_image_shape(image), data_type_from_format(format) };
// Fill reference
fill(src, image, format);
return reference::hog_descriptor<U>(src, border_mode, constant_border_value, hog_info);
}
TensorType _target{};
SimpleTensor<U> _reference{};
};
} // namespace validation
} // namespace test
} // namespace arm_compute
#endif /* ARM_COMPUTE_TEST_HOG_DESCRIPTOR_FIXTURE */
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