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/*
* Copyright (c) 2016-2018 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 "arm_compute/core/NEON/kernels/NECumulativeDistributionKernel.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/IDistribution1D.h"
#include "arm_compute/core/ILut.h"
#include "arm_compute/core/ITensor.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Validate.h"
#include <algorithm>
#include <cmath>
#include <numeric>
using namespace arm_compute;
NECumulativeDistributionKernel::NECumulativeDistributionKernel()
: _input(nullptr), _distribution(nullptr), _cumulative_sum(nullptr), _output(nullptr)
{
}
bool NECumulativeDistributionKernel::is_parallelisable() const
{
return false;
}
void NECumulativeDistributionKernel::configure(const IImage *input, const IDistribution1D *distribution, IDistribution1D *cumulative_sum, ILut *output)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, distribution, cumulative_sum, output);
ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(input);
set_format_if_unknown(*input->info(), Format::U8);
ARM_COMPUTE_ERROR_ON(distribution->num_bins() != cumulative_sum->num_bins());
ARM_COMPUTE_ERROR_ON(distribution->num_bins() != output->num_elements());
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
ARM_COMPUTE_ERROR_ON(input->info()->data_type() != output->type());
_input = input;
_distribution = distribution;
_cumulative_sum = cumulative_sum;
_output = output;
INEKernel::configure(calculate_max_window(*input->info()));
}
void NECumulativeDistributionKernel::run(const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_UNUSED(window);
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
ARM_COMPUTE_ERROR_ON(_distribution->buffer() == nullptr);
ARM_COMPUTE_ERROR_ON(_cumulative_sum->buffer() == nullptr);
ARM_COMPUTE_ERROR_ON(_output->buffer() == nullptr);
ARM_COMPUTE_ERROR_ON_MSG(_distribution->num_bins() < 256, "Distribution must have 256 bins");
// Calculate the cumulative distribution (summed histogram).
const uint32_t *hist = _distribution->buffer();
uint32_t *cumulative_sum = _cumulative_sum->buffer();
uint8_t *output = _output->buffer();
// Calculate cumulative distribution
std::partial_sum(hist, hist + _histogram_size, cumulative_sum);
// Get the number of pixels that have the lowest value in the input image
const uint32_t cd_min = *std::find_if(hist, hist + _histogram_size, [](const uint32_t &v)
{
return v > 0;
});
const uint32_t image_size = cumulative_sum[_histogram_size - 1];
ARM_COMPUTE_ERROR_ON(cd_min > image_size);
// Create mapping lookup table
if(image_size == cd_min)
{
std::iota(output, output + _histogram_size, 0);
}
else
{
const float diff = image_size - cd_min;
for(unsigned int x = 0; x < _histogram_size; ++x)
{
output[x] = lround((cumulative_sum[x] - cd_min) / diff * 255.0f);
}
}
}
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