| /* |
| * Copyright (c) 2016, 2017 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) |
| { |
| 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); |
| } |
| } |
| } |