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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.
*/
#include "Scale.h"
#include "Utils.h"
#include "arm_compute/core/utils/misc/Utility.h"
#include "support/ToolchainSupport.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
namespace reference
{
template <typename T>
SimpleTensor<T> scale(const SimpleTensor<T> &in, float scale_x, float scale_y, InterpolationPolicy policy, BorderMode border_mode, T constant_border_value,
SamplingPolicy sampling_policy, bool ceil_policy_scale)
{
// Add 1 if ceil_policy_scale is true
const size_t round_value = ceil_policy_scale ? 1U : 0U;
TensorShape shape_scaled(in.shape());
shape_scaled.set(0, (in.shape()[0] + round_value) * scale_x);
shape_scaled.set(1, (in.shape()[1] + round_value) * scale_y);
SimpleTensor<T> out(shape_scaled, in.data_type());
// Compute the ratio between source width/height and destination width/height
const auto wr = static_cast<float>(in.shape()[0]) / static_cast<float>(out.shape()[0]);
const auto hr = static_cast<float>(in.shape()[1]) / static_cast<float>(out.shape()[1]);
const auto width = static_cast<int>(in.shape().x());
const auto height = static_cast<int>(in.shape().y());
// Determine border size
const int border_size = (border_mode == BorderMode::UNDEFINED) ? 0 : 1;
// Area interpolation behaves as Nearest Neighbour in case of up-sampling
if(policy == InterpolationPolicy::AREA && wr <= 1.f && hr <= 1.f)
{
policy = InterpolationPolicy::NEAREST_NEIGHBOR;
}
for(int element_idx = 0, count = 0; element_idx < out.num_elements(); ++element_idx, ++count)
{
Coordinates id = index2coord(out.shape(), element_idx);
int idx = id.x();
int idy = id.y();
float x_src = 0;
float y_src = 0;
switch(sampling_policy)
{
case SamplingPolicy::TOP_LEFT:
x_src = idx * wr;
y_src = idy * hr;
break;
case SamplingPolicy::CENTER:
x_src = (idx + 0.5f) * wr - 0.5f;
y_src = (idy + 0.5f) * hr - 0.5f;
break;
default:
ARM_COMPUTE_ERROR("Unsupported sampling policy.");
break;
}
switch(policy)
{
case InterpolationPolicy::NEAREST_NEIGHBOR:
{
//Calculate the source coords without -0.5f is equivalent to round the x_scr/y_src coords
x_src = (idx + 0.5f) * wr;
y_src = (idy + 0.5f) * hr;
id.set(0, x_src);
id.set(1, y_src);
// If coordinates in range of tensor's width or height
if(is_valid_pixel_index(x_src, y_src, width, height, border_size))
{
out[element_idx] = tensor_elem_at(in, id, border_mode, constant_border_value);
}
break;
}
case InterpolationPolicy::BILINEAR:
{
id.set(0, std::floor(x_src));
id.set(1, std::floor(y_src));
if(is_valid_pixel_index(x_src, y_src, width, height, border_size))
{
out[element_idx] = bilinear_policy(in, id, x_src, y_src, border_mode, constant_border_value);
}
else
{
if(border_mode == BorderMode::CONSTANT)
{
out[element_idx] = constant_border_value;
}
else if(border_mode == BorderMode::REPLICATE)
{
id.set(0, utility::clamp<int>(x_src, 0, width - 1));
id.set(1, utility::clamp<int>(y_src, 0, height - 1));
out[element_idx] = in[coord2index(in.shape(), id)];
}
}
break;
}
case InterpolationPolicy::AREA:
{
int x_from = std::floor(idx * wr - 0.5f - x_src);
int y_from = std::floor(idy * hr - 0.5f - y_src);
int x_to = std::ceil((idx + 1) * wr - 0.5f - x_src);
int y_to = std::ceil((idy + 1) * hr - 0.5f - y_src);
const int xi = std::floor(x_src);
const int yi = std::floor(y_src);
// Clamp position to borders
x_src = std::max(-static_cast<float>(border_size), std::min(x_src, static_cast<float>(width - 1 + border_size)));
y_src = std::max(-static_cast<float>(border_size), std::min(y_src, static_cast<float>(height - 1 + border_size)));
// Clamp bounding box offsets to borders
x_from = ((x_src + x_from) < -border_size) ? -border_size : x_from;
y_from = ((y_src + y_from) < -border_size) ? -border_size : y_from;
x_to = ((x_src + x_to) >= (width + border_size)) ? (width - 1 + border_size) : x_to;
y_to = ((y_src + y_to) >= (height + border_size)) ? (height - 1 + border_size) : y_to;
ARM_COMPUTE_ERROR_ON((x_to - x_from + 1) == 0 || (y_to - y_from + 1) == 0);
float sum = 0;
for(int j = yi + y_from, je = yi + y_to; j <= je; ++j)
{
for(int i = xi + x_from, ie = xi + x_to; i <= ie; ++i)
{
id.set(0, static_cast<int>(i));
id.set(1, static_cast<int>(j));
sum += tensor_elem_at(in, id, border_mode, constant_border_value);
}
}
out[element_idx] = sum / ((x_to - x_from + 1) * (y_to - y_from + 1));
break;
}
default:
ARM_COMPUTE_ERROR("Unsupported interpolation mode");
}
}
return out;
}
template SimpleTensor<uint8_t> scale(const SimpleTensor<uint8_t> &src, float scale_x, float scale_y, InterpolationPolicy policy, BorderMode border_mode, uint8_t constant_border_value,
SamplingPolicy sampling_policy, bool ceil_policy_scale);
template SimpleTensor<int16_t> scale(const SimpleTensor<int16_t> &src, float scale_x, float scale_y, InterpolationPolicy policy, BorderMode border_mode, int16_t constant_border_value,
SamplingPolicy sampling_policy, bool ceil_policy_scale);
template SimpleTensor<half> scale(const SimpleTensor<half> &src, float scale_x, float scale_y, InterpolationPolicy policy, BorderMode border_mode, half constant_border_value,
SamplingPolicy sampling_policy, bool ceil_policy_scale);
template SimpleTensor<float> scale(const SimpleTensor<float> &src, float scale_x, float scale_y, InterpolationPolicy policy, BorderMode border_mode, float constant_border_value,
SamplingPolicy sampling_policy, bool ceil_policy_scale);
} // namespace reference
} // namespace validation
} // namespace test
} // namespace arm_compute