From 894066de8cc26d1a3aca62dcaa6b30a2a1116028 Mon Sep 17 00:00:00 2001 From: George Wort Date: Fri, 15 Feb 2019 15:12:52 +0000 Subject: COMPMID-1844: Implement CLCrop Change-Id: I8822c37adc45960705dc3f32a53214795ba3cf39 Signed-off-by: George Wort Reviewed-on: https://review.mlplatform.org/c/789 Reviewed-by: Manuel Bottini Tested-by: Arm Jenkins Reviewed-by: Pablo Marquez --- src/runtime/CL/functions/CLCropResize.cpp | 272 ++++++++++++++++++++++++++++++ 1 file changed, 272 insertions(+) create mode 100644 src/runtime/CL/functions/CLCropResize.cpp (limited to 'src/runtime/CL') diff --git a/src/runtime/CL/functions/CLCropResize.cpp b/src/runtime/CL/functions/CLCropResize.cpp new file mode 100644 index 0000000000..2cacef1bb1 --- /dev/null +++ b/src/runtime/CL/functions/CLCropResize.cpp @@ -0,0 +1,272 @@ +/* + * Copyright (c) 2019 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/CLHelpers.h" + +#include "arm_compute/runtime/CL/CLScheduler.h" +#include "arm_compute/runtime/CL/functions/CLCropResize.h" + +#include + +namespace arm_compute +{ +namespace +{ +inline void configure_crop(const ICLTensor *input, ICLTensor *crop_boxes, ICLTensor *box_ind, ICLTensor *output, uint32_t crop_box_ind, Coordinates &start, Coordinates &end, uint32_t &batch_index) +{ + batch_index = *(reinterpret_cast(box_ind->ptr_to_element(Coordinates(crop_box_ind)))); + + // _crop_box_ind is used to index crop_boxes and retrieve the appropriate crop box. + // The crop box is specified by normalized coordinates [y0, x0, y1, x1]. + const float x0 = *reinterpret_cast(crop_boxes->ptr_to_element(Coordinates(1, crop_box_ind))); + const float y0 = *reinterpret_cast(crop_boxes->ptr_to_element(Coordinates(0, crop_box_ind))); + const float x1 = *reinterpret_cast(crop_boxes->ptr_to_element(Coordinates(3, crop_box_ind))); + const float y1 = *reinterpret_cast(crop_boxes->ptr_to_element(Coordinates(2, crop_box_ind))); + // The normalized coordinates are scaled to retrieve the floating point image coordinates which are rounded to integers. + start = Coordinates(std::floor(x0 * (input->info()->tensor_shape()[1] - 1) + 0.5f), + std::floor(y0 * (input->info()->tensor_shape()[2] - 1) + 0.5f)); + end = Coordinates(std::floor(x1 * (input->info()->tensor_shape()[1] - 1) + 0.5f), + std::floor(y1 * (input->info()->tensor_shape()[2] - 1) + 0.5f)); + const TensorShape out_shape(input->info()->tensor_shape()[0], abs(end[0] - start[0]) + 1, abs(end[1] - start[1]) + 1); + output->info()->set_tensor_shape(out_shape); +} + +inline void run_crop(const ICLTensor *input, ICLTensor *output, uint32_t batch_index, Coordinates start, Coordinates end, float extrapolation_value) +{ + bool is_width_flipped = end[0] < start[0]; + bool is_height_flipped = end[1] < start[1]; + /** The number of rows out of bounds at the start and end of output. */ + int32_t rows_out_of_bounds[2]; + /** The number of columns out of bounds at the start and end of output. */ + int32_t cols_out_of_bounds[2]; + if(is_height_flipped) + { + rows_out_of_bounds[0] = start[1] >= static_cast(input->info()->dimension(2)) ? std::min(start[1] - input->info()->dimension(2) + 1, output->info()->dimension(2)) : 0; + rows_out_of_bounds[1] = end[1] < 0 ? std::min(-end[1], static_cast(output->info()->dimension(2))) : 0; + } + else + { + rows_out_of_bounds[0] = start[1] < 0 ? std::min(-start[1], static_cast(output->info()->dimension(2))) : 0; + rows_out_of_bounds[1] = end[1] >= static_cast(input->info()->dimension(2)) ? std::min(end[1] - input->info()->dimension(2) + 1, output->info()->dimension(2)) : 0; + } + if(is_width_flipped) + { + cols_out_of_bounds[0] = start[0] >= static_cast(input->info()->dimension(1)) ? std::min(start[0] - input->info()->dimension(1) + 1, output->info()->dimension(1)) : 0; + cols_out_of_bounds[1] = end[0] < 0 ? std::min(-end[0], static_cast(output->info()->dimension(1))) : 0; + } + else + { + cols_out_of_bounds[0] = start[0] < 0 ? std::min(-start[0], static_cast(output->info()->dimension(1))) : 0; + cols_out_of_bounds[1] = end[0] >= static_cast(input->info()->dimension(1)) ? std::min(end[0] - input->info()->dimension(1) + 1, output->info()->dimension(1)) : 0; + } + + Window full_window = calculate_max_window(*output->info()); + + // Full output window: + // -------------------------------- + // | Out of bounds | + // | rows before | + // |------------------------------| + // | Out of | In | Out of | + // | bounds | bounds | bounds | + // | cols | elements | cols | + // | before | copied | after | + // | | from input | | + // |------------------------------| + // | Out of bounds | + // | rows after | + // |------------------------------| + // Use a separate output window for each section of the full output window. + // Fill all output rows that have no elements that are within the input bounds + // with the extrapolation value using memset. + // First for the rows before the in bounds rows. + if(rows_out_of_bounds[0] > 0) + { + Window slice_fill_rows_before(full_window); + slice_fill_rows_before.set(2, Window::Dimension(0, rows_out_of_bounds[0], 1)); + auto kernel = arm_compute::support::cpp14::make_unique(); + kernel->configure(output, extrapolation_value, &slice_fill_rows_before); + CLScheduler::get().enqueue(*kernel); + } + + Window slice_in(full_window); + slice_in.set(2, Window::Dimension(rows_out_of_bounds[0], output->info()->dimension(2) - rows_out_of_bounds[1], 1)); + slice_in.set(1, Window::Dimension(cols_out_of_bounds[0], output->info()->dimension(1) - cols_out_of_bounds[1], 1)); + + int rows_in_bounds = static_cast(output->info()->dimension(2)) - rows_out_of_bounds[0] - rows_out_of_bounds[1]; + if(rows_in_bounds > 0) + { + // Fill all elements that share a row with an in bounds element with the extrapolation value. + if(cols_out_of_bounds[0] > 0) + { + Window slice_fill_cols_before(slice_in); + slice_fill_cols_before.set(1, Window::Dimension(0, cols_out_of_bounds[0], 1)); + auto kernel = arm_compute::support::cpp14::make_unique(); + kernel->configure(output, extrapolation_value, &slice_fill_cols_before); + CLScheduler::get().enqueue(*kernel); + } + + if(cols_out_of_bounds[1] > 0) + { + Window slice_fill_cols_after(slice_in); + slice_fill_cols_after.set(1, Window::Dimension(output->info()->dimension(1) - cols_out_of_bounds[1], output->info()->dimension(1), 1)); + auto kernel = arm_compute::support::cpp14::make_unique(); + kernel->configure(output, extrapolation_value, &slice_fill_cols_after); + CLScheduler::get().enqueue(*kernel); + } + + // Copy all elements within the input bounds from the input tensor. + int cols_in_bounds = static_cast(output->info()->dimension(1)) - cols_out_of_bounds[0] - cols_out_of_bounds[1]; + if(cols_in_bounds > 0) + { + Coordinates2D start_in{ is_width_flipped ? start[0] - cols_out_of_bounds[0] : start[0] + cols_out_of_bounds[0], + is_height_flipped ? start[1] - rows_out_of_bounds[0] : start[1] + rows_out_of_bounds[0] }; + Coordinates2D end_in{ is_width_flipped ? start_in.x - cols_in_bounds + 1 : start_in.x + cols_in_bounds - 1, + is_height_flipped ? start_in.y - rows_in_bounds + 1 : start_in.y + rows_in_bounds - 1 }; + auto kernel = arm_compute::support::cpp14::make_unique(); + + kernel->configure(input, output, start_in, end_in, batch_index, extrapolation_value, &slice_in); + CLScheduler::get().enqueue(*kernel); + } + } + + // Fill all rows after the in bounds elements with the extrapolation value. + if(rows_out_of_bounds[1] > 0) + { + Window slice_fill_rows_after(full_window); + slice_fill_rows_after.set(2, Window::Dimension(output->info()->dimension(2) - rows_out_of_bounds[1], output->info()->dimension(2), 1)); + auto kernel = arm_compute::support::cpp14::make_unique(); + kernel->configure(output, extrapolation_value, &slice_fill_rows_after); + CLScheduler::get().enqueue(*kernel); + } +} +} // namespace + +CLCropResize::CLCropResize() + : _input(nullptr), _boxes(nullptr), _box_ind(nullptr), _output(nullptr), _num_boxes(0), _method(), _extrapolation_value(0), _scale(), _copy() +{ +} + +Status CLCropResize::validate(const ITensorInfo *input, ITensorInfo *boxes, 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); + ARM_COMPUTE_RETURN_ERROR_ON(boxes->tensor_shape()[0] != 4); + ARM_COMPUTE_RETURN_ERROR_ON(boxes->tensor_shape()[1] != box_ind->tensor_shape()[0]); + TensorInfo temp_info; + ARM_COMPUTE_RETURN_ON_ERROR(CLCropKernel::validate(input->clone().get(), &temp_info, { 0, 0 }, { 1, 1 }, input->dimension(3) - 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 CLCropResize::configure(const ICLTensor *input, ICLTensor *boxes, ICLTensor *box_ind, ICLTensor *output, Coordinates2D crop_size, + InterpolationPolicy method, float extrapolation_value) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + ARM_COMPUTE_ERROR_THROW_ON(CLCropResize::validate(input->info(), boxes->info(), box_ind->info(), output->info(), 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); + + _input = input; + _boxes = boxes; + _box_ind = box_ind; + _output = output; + _method = method; + _extrapolation_value = extrapolation_value; + + // For each crop box: + // - The initial cropped image is produced as specified by boxes[i] from the 3D image input[box_ind[i]]. + // Possibly using a CLCropKernel and up to four CLMemsetKernels. + // - 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 using CLCopyKernel. + _crop_results = arm_compute::support::cpp14::make_unique(_num_boxes); + _scale = arm_compute::support::cpp14::make_unique(_num_boxes); + _scaled_results = arm_compute::support::cpp14::make_unique(_num_boxes); + _copy = arm_compute::support::cpp14::make_unique(_num_boxes); + + for(unsigned int i = 0; i < _num_boxes; ++i) + { + TensorInfo crop_result_info(1, DataType::F32); + crop_result_info.set_data_layout(DataLayout::NHWC); + _crop_results[i].allocator()->init(crop_result_info); + + TensorInfo scaled_result_info(out_shape, 1, DataType::F32); + scaled_result_info.set_data_layout(DataLayout::NHWC); + _scaled_results[i].allocator()->init(scaled_result_info); + } +} + +void CLCropResize::run() +{ + ARM_COMPUTE_ERROR_ON_MSG(_output == nullptr, "Unconfigured function"); + // The contents of _boxes and _box_ind are required to calculate the shape + // of the initial cropped image and thus are required to configure the + // kernels used for cropping and scaling. + _boxes->map(CLScheduler::get().queue()); + _box_ind->map(CLScheduler::get().queue()); + 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. + uint32_t batch_index; + Coordinates start, end; + configure_crop(_input, _boxes, _box_ind, &_crop_results[i], i, start, end, batch_index); + _scale[i].configure(&_crop_results[i], &_scaled_results[i], _method, BorderMode::CONSTANT, PixelValue(_extrapolation_value), SamplingPolicy::TOP_LEFT); + + Window win = calculate_max_window(*_output->info()); + win.set(3, Window::Dimension(i, i + 1, 1)); + _copy[i].configure(&_scaled_results[i], _output, PaddingList(), &win); + + _crop_results[i].allocator()->allocate(); + _scaled_results[i].allocator()->allocate(); + + run_crop(_input, &_crop_results[i], batch_index, start, end, _extrapolation_value); + } + _boxes->unmap(CLScheduler::get().queue()); + _box_ind->unmap(CLScheduler::get().queue()); + CLScheduler::get().sync(); + for(unsigned int i = 0; i < _num_boxes; ++i) + { + // Scale the cropped image + _scale[i].run(); + } + CLScheduler::get().sync(); + for(unsigned int i = 0; i < _num_boxes; ++i) + { + // Copy scaled image into output. + CLScheduler::get().enqueue(_copy[i]); + } + CLScheduler::get().sync(); +} +} // namespace arm_compute \ No newline at end of file -- cgit v1.2.1