| /* |
| * 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/CL/kernels/CLIntegralImageKernel.h" |
| |
| #include "arm_compute/core/CL/CLKernelLibrary.h" |
| #include "arm_compute/core/CL/ICLTensor.h" |
| #include "arm_compute/core/CL/OpenCL.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/core/Window.h" |
| |
| #include <cstddef> |
| |
| using namespace arm_compute; |
| |
| void CLIntegralImageHorKernel::configure(const ICLTensor *input, ICLTensor *output) |
| { |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8); |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U32); |
| |
| _input = input; |
| _output = output; |
| |
| // Create kernel |
| _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("integral_horizontal")); |
| |
| // Configure kernel window |
| const unsigned int num_elems_processed_per_iteration = input->info()->dimension(0); |
| const unsigned int num_elems_accessed_per_iteration = ceil_to_multiple(num_elems_processed_per_iteration, 16); |
| |
| Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); |
| AccessWindowHorizontal output_access(output->info(), 0, num_elems_accessed_per_iteration); |
| |
| update_window_and_padding(win, |
| AccessWindowHorizontal(input->info(), 0, num_elems_accessed_per_iteration), |
| output_access); |
| |
| output_access.set_valid_region(win, input->info()->valid_region()); |
| |
| ICLKernel::configure(win); |
| } |
| |
| CLIntegralImageVertKernel::CLIntegralImageVertKernel() |
| : _in_out(nullptr) |
| { |
| } |
| |
| void CLIntegralImageVertKernel::configure(ICLTensor *in_out) |
| { |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(in_out, 1, DataType::U32); |
| |
| _in_out = in_out; |
| |
| // Create kernel |
| _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("integral_vertical")); |
| |
| // Configure kernel window |
| constexpr unsigned int num_elems_processed_per_iteration_x = 8; |
| const unsigned int num_elems_processed_per_iteration_y = in_out->info()->dimension(Window::DimY); |
| |
| Window win = calculate_max_window(*in_out->info(), Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); |
| |
| AccessWindowRectangle in_out_access(in_out->info(), 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y); |
| |
| update_window_and_padding(win, in_out_access); |
| |
| in_out_access.set_valid_region(win, in_out->info()->valid_region()); |
| |
| ICLKernel::configure(win); |
| } |
| |
| void CLIntegralImageVertKernel::run(const Window &window, cl::CommandQueue &queue) |
| { |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); |
| |
| const size_t height = _in_out->info()->dimension(1); |
| |
| Window slice = window.first_slice_window_2D(); |
| |
| do |
| { |
| unsigned int idx = 0; |
| add_2D_tensor_argument(idx, _in_out, slice); |
| _kernel.setArg<cl_uint>(idx++, height); |
| enqueue(queue, *this, slice); |
| } |
| while(window.slide_window_slice_2D(slice)); |
| } |