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/*
* Copyright (c) 2019-2021 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 "arm_compute/runtime/NEON/functions/NECropResize.h"
#include "arm_compute/runtime/NEON/NEScheduler.h"
#include "arm_compute/runtime/Tensor.h"
#include "src/common/utils/Log.h"
#include "src/core/NEON/kernels/NECropKernel.h"
#include <cstddef>
namespace arm_compute
{
NECropResize::~NECropResize() = default;
NECropResize::NECropResize()
: _output(nullptr),
_num_boxes(0),
_method(),
_extrapolation_value(0),
_crop(),
_scale(),
_crop_results(),
_scaled_results()
{
}
Status NECropResize::validate(const ITensorInfo *input,
const ITensorInfo *boxes,
const ITensorInfo *box_ind,
const ITensorInfo *output,
Coordinates2D crop_size,
InterpolationPolicy method,
float extrapolation_value)
{
ARM_COMPUTE_RETURN_ERROR_ON(crop_size.x <= 0 || crop_size.y <= 0);
ARM_COMPUTE_RETURN_ERROR_ON(method == InterpolationPolicy::AREA);
TensorInfo temp_info;
ARM_COMPUTE_RETURN_ON_ERROR(NECropKernel::validate(input->clone().get(), boxes->clone().get(),
box_ind->clone().get(), &temp_info, boxes->tensor_shape()[1] - 1,
extrapolation_value));
if (output->total_size() > 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(output, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output);
TensorShape out_shape(input->tensor_shape()[0], crop_size.x, crop_size.y, boxes->tensor_shape()[1]);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), out_shape);
}
return Status{};
}
void NECropResize::configure(const ITensor *input,
const ITensor *boxes,
const ITensor *box_ind,
ITensor *output,
Coordinates2D crop_size,
InterpolationPolicy method,
float extrapolation_value)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_ERROR_THROW_ON(NECropResize::validate(input->info(), boxes->info(), box_ind->info(), output->info(),
crop_size, method, extrapolation_value));
ARM_COMPUTE_LOG_PARAMS(input, boxes, box_ind, output, crop_size, method, extrapolation_value);
_num_boxes = boxes->info()->tensor_shape()[1];
TensorShape out_shape(input->info()->tensor_shape()[0], crop_size.x, crop_size.y);
_output = output;
_method = method;
_extrapolation_value = extrapolation_value;
// For each crop box:
// - A crop kernel is used to extract the initial cropped image as specified by boxes[i] from the 3D image input[box_ind[i]].
// - A tensor is required to hold this initial cropped image.
// - A scale function is used to resize the cropped image to the size specified by crop_size.
// - A tensor is required to hold the final scaled image before it is copied into the 4D output
// that will hold all final cropped and scaled 3D images.
_crop.reserve(_num_boxes);
_crop_results.reserve(_num_boxes);
_scaled_results.reserve(_num_boxes);
_scale.reserve(_num_boxes);
for (unsigned int i = 0; i < _num_boxes; ++i)
{
auto crop_tensor = std::make_unique<Tensor>();
TensorInfo crop_result_info(1, DataType::F32);
crop_result_info.set_data_layout(DataLayout::NHWC);
crop_tensor->allocator()->init(crop_result_info);
auto scale_tensor = std::make_unique<Tensor>();
TensorInfo scaled_result_info(out_shape, 1, DataType::F32);
scaled_result_info.set_data_layout(DataLayout::NHWC);
scale_tensor->allocator()->init(scaled_result_info);
auto crop_kernel = std::make_unique<NECropKernel>();
auto scale_kernel = std::make_unique<NEScale>();
crop_kernel->configure(input, boxes, box_ind, crop_tensor.get(), i, _extrapolation_value);
_crop.emplace_back(std::move(crop_kernel));
_scaled_results.emplace_back(std::move(scale_tensor));
_crop_results.emplace_back(std::move(crop_tensor));
_scale.emplace_back(std::move(scale_kernel));
}
}
void NECropResize::run()
{
ARM_COMPUTE_ERROR_ON_MSG(_output == nullptr, "Unconfigured function");
for (unsigned int i = 0; i < _num_boxes; ++i)
{
// Size of the crop box in _boxes and thus the shape of _crop_results[i]
// may not be known until run-time and so the kernels cannot be configured until then.
_crop[i]->configure_output_shape();
_crop_results[i]->allocator()->allocate();
NEScheduler::get().schedule(_crop[i].get(), Window::DimZ);
// Scale the cropped image.
_scale[i]->configure(_crop_results[i].get(), _scaled_results[i].get(),
ScaleKernelInfo{_method, BorderMode::CONSTANT, PixelValue(_extrapolation_value),
SamplingPolicy::TOP_LEFT, false});
_scaled_results[i]->allocator()->allocate();
_scale[i]->run();
// Copy scaled image into output.
std::copy_n(_scaled_results[i]->buffer(), _scaled_results[i]->info()->total_size(),
_output->ptr_to_element(Coordinates(0, 0, 0, i)));
}
}
} // namespace arm_compute
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