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/*
* Copyright (c) 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_FAST_CORNERS_FIXTURE
#define ARM_COMPUTE_TEST_FAST_CORNERS_FIXTURE
#include "arm_compute/core/TensorShape.h"
#include "arm_compute/core/Types.h"
#include "tests/Globals.h"
#include "tests/Utils.h"
#include "tests/framework/Fixture.h"
namespace arm_compute
{
class CLFastCorners;
class NEFastCorners;
namespace test
{
namespace benchmark
{
template <typename TensorType, typename Function, typename Accessor, typename ArrayType>
class FastCornersFixture : public framework::Fixture
{
public:
template <typename...>
void setup(std::string image, Format format, float threshold, bool suppress_nonmax, BorderMode border_mode)
{
// Load the image (cached by the library if loaded before)
const RawTensor &raw = library->get(image, format);
// Create tensor
src = create_tensor<TensorType>(raw.shape(), format);
// Create and configure function
configure_target<Function>(fast_corners_func, src, corners, &num_corners, threshold, suppress_nonmax, border_mode, 0);
// Allocate tensor
src.allocator()->allocate();
// Copy image data to tensor
library->fill(Accessor(src), raw);
}
void run()
{
fast_corners_func.run();
}
void sync()
{
sync_if_necessary<TensorType>();
}
void teardown()
{
src.allocator()->free();
}
protected:
template <typename F, typename std::enable_if<std::is_same<F, CLFastCorners>::value, int>::type = 0>
void configure_target(F &func, TensorType &src, ArrayType &corners, unsigned int *num_corners, float threshold, bool suppress_nonmax, BorderMode border_mode, uint8_t constant_border_value)
{
func.configure(&src, threshold, suppress_nonmax, &corners, num_corners, border_mode, constant_border_value);
}
template <typename F, typename std::enable_if<std::is_same<F, NEFastCorners>::value, int>::type = 0>
void configure_target(F &func, TensorType &src, ArrayType &corners, unsigned int *num_corners, float threshold, bool suppress_nonmax, BorderMode border_mode, uint8_t constant_border_value)
{
ARM_COMPUTE_UNUSED(num_corners);
func.configure(&src, threshold, suppress_nonmax, &corners, border_mode, constant_border_value);
}
private:
const static size_t max_corners = 20000;
TensorType src{};
ArrayType corners{ max_corners };
unsigned int num_corners{ max_corners };
Function fast_corners_func{};
};
} // namespace benchmark
} // namespace test
} // namespace arm_compute
#endif /* ARM_COMPUTE_TEST_FAST_CORNERS_FIXTURE */