| /* |
| * Copyright (c) 2019-2021 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/runtime/CL/functions/CLCropResize.h" |
| |
| #include "arm_compute/core/CL/CLHelpers.h" |
| #include "arm_compute/runtime/CL/CLScheduler.h" |
| |
| #include "src/common/utils/Log.h" |
| #include "src/core/CL/kernels/CLFillBorderKernel.h" |
| #include "src/core/helpers/AutoConfiguration.h" |
| #include "src/core/helpers/WindowHelpers.h" |
| |
| #include <cstddef> |
| |
| 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<int32_t *>(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<const float *>(crop_boxes->ptr_to_element(Coordinates(1, crop_box_ind))); |
| const float y0 = *reinterpret_cast<const float *>(crop_boxes->ptr_to_element(Coordinates(0, crop_box_ind))); |
| const float x1 = *reinterpret_cast<const float *>(crop_boxes->ptr_to_element(Coordinates(3, crop_box_ind))); |
| const float y1 = *reinterpret_cast<const float *>(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], static_cast<uint32_t>(abs(end[0] - start[0])) + 1, |
| static_cast<uint32_t>(abs(end[1] - start[1])) + 1); |
| output->info()->set_tensor_shape(out_shape); |
| } |
| } // namespace |
| |
| CLCropResize::CLCropResize() |
| : _input(nullptr), |
| _boxes(nullptr), |
| _box_ind(nullptr), |
| _output(nullptr), |
| _num_boxes(0), |
| _method(), |
| _extrapolation_value(0), |
| _scale(), |
| _copy(), |
| _crop_results(), |
| _scaled_results(), |
| _internal_functions() |
| { |
| } |
| |
| CLCropResize::~CLCropResize() = default; |
| |
| 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(CLCrop::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) |
| { |
| configure(CLKernelLibrary::get().get_compile_context(), input, boxes, box_ind, output, crop_size, method, |
| extrapolation_value); |
| } |
| |
| void CLCropResize::configure(const CLCompileContext &compile_context, |
| 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, boxes, box_ind); |
| ARM_COMPUTE_ERROR_THROW_ON(CLCropResize::validate(input->info(), boxes->info(), box_ind->info(), output->info(), |
| crop_size, method, extrapolation_value)); |
| ARM_COMPUTE_LOG_PARAMS(input, boxes, box_ind, output, crop_size, method, extrapolation_value); |
| |
| TensorShape output_shape = |
| TensorShape(input->info()->tensor_shape()[0], crop_size.x, crop_size.y, boxes->info()->tensor_shape()[1]); |
| auto_init_if_empty(*output->info(), output_shape, 1, DataType::F32); |
| |
| _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 CLCrop and up to four CLFills. |
| // - 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 CLCopy. |
| |
| // 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 num_box = 0; num_box < _num_boxes; ++num_box) |
| { |
| auto crop_tensor = std::make_unique<CLTensor>(); |
| TensorInfo crop_result_info(1, DataType::F32); |
| crop_result_info.set_data_layout(DataLayout::NHWC); |
| crop_tensor->allocator()->init(crop_result_info); |
| _crop_results.emplace_back(std::move(crop_tensor)); |
| |
| auto scale_tensor = std::make_unique<CLTensor>(); |
| TensorInfo scaled_result_info(out_shape, 1, DataType::F32); |
| scaled_result_info.set_data_layout(DataLayout::NHWC); |
| scale_tensor->allocator()->init(scaled_result_info); |
| _scaled_results.emplace_back(std::move(scale_tensor)); |
| |
| // Size of the crop box in _boxes has to be given before the configure |
| uint32_t batch_index; |
| Coordinates start{}; |
| Coordinates end{}; |
| configure_crop(_input, _boxes, _box_ind, _crop_results[num_box].get(), num_box, start, end, batch_index); |
| |
| auto scale_kernel = std::make_unique<CLScale>(); |
| scale_kernel->configure( |
| compile_context, _crop_results[num_box].get(), _scaled_results[num_box].get(), |
| ScaleKernelInfo{_method, BorderMode::CONSTANT, PixelValue(_extrapolation_value), SamplingPolicy::TOP_LEFT}); |
| _scale.emplace_back(std::move(scale_kernel)); |
| |
| Window win = calculate_max_window(*_output->info()); |
| win.set(3, Window::Dimension(num_box, num_box + 1, 1)); |
| |
| auto copy_kernel = std::make_unique<CLCopy>(); |
| copy_kernel->configure(compile_context, _scaled_results[num_box].get(), _output, &win); |
| _copy.emplace_back(std::move(copy_kernel)); |
| |
| _crop_results[num_box]->allocator()->allocate(); |
| _scaled_results[num_box]->allocator()->allocate(); |
| |
| 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 _crop_results[num_box].get(). */ |
| std::array<int32_t, 2> rows_out_of_bounds{0}; |
| /** The number of columns out of bounds at the start and end of _crop_results[num_box].get(). */ |
| std::array<int32_t, 2> cols_out_of_bounds{0}; |
| if (is_height_flipped) |
| { |
| rows_out_of_bounds[0] = start[1] >= static_cast<int32_t>(_input->info()->dimension(2)) |
| ? std::min(start[1] - _input->info()->dimension(2) + 1, |
| _crop_results[num_box].get()->info()->dimension(2)) |
| : 0; |
| rows_out_of_bounds[1] = |
| end[1] < 0 ? std::min(-end[1], static_cast<int32_t>(_crop_results[num_box].get()->info()->dimension(2))) |
| : 0; |
| } |
| else |
| { |
| rows_out_of_bounds[0] = |
| start[1] < 0 |
| ? std::min(-start[1], static_cast<int32_t>(_crop_results[num_box].get()->info()->dimension(2))) |
| : 0; |
| rows_out_of_bounds[1] = end[1] >= static_cast<int32_t>(_input->info()->dimension(2)) |
| ? std::min(end[1] - _input->info()->dimension(2) + 1, |
| _crop_results[num_box].get()->info()->dimension(2)) |
| : 0; |
| } |
| if (is_width_flipped) |
| { |
| cols_out_of_bounds[0] = start[0] >= static_cast<int32_t>(_input->info()->dimension(1)) |
| ? std::min(start[0] - _input->info()->dimension(1) + 1, |
| _crop_results[num_box].get()->info()->dimension(1)) |
| : 0; |
| cols_out_of_bounds[1] = |
| end[0] < 0 ? std::min(-end[0], static_cast<int32_t>(_crop_results[num_box].get()->info()->dimension(1))) |
| : 0; |
| } |
| else |
| { |
| cols_out_of_bounds[0] = |
| start[0] < 0 |
| ? std::min(-start[0], static_cast<int32_t>(_crop_results[num_box].get()->info()->dimension(1))) |
| : 0; |
| cols_out_of_bounds[1] = end[0] >= static_cast<int32_t>(_input->info()->dimension(1)) |
| ? std::min(end[0] - _input->info()->dimension(1) + 1, |
| _crop_results[num_box].get()->info()->dimension(1)) |
| : 0; |
| } |
| |
| Window full_window = calculate_max_window(*_crop_results[num_box].get()->info()); |
| |
| // Full _crop_results[num_box].get() 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 _crop_results[num_box].get() window for each section of the full _crop_results[num_box].get() window. |
| // Fill all _crop_results[num_box].get() 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 = std::make_unique<CLFill>(); |
| kernel->configure(compile_context, _crop_results[num_box].get(), extrapolation_value, |
| &slice_fill_rows_before); |
| //_internal_functions.emplace_back(std::move(kernel)); |
| _internal_functions.push_back(std::move(kernel)); |
| } |
| |
| Window slice_in(full_window); |
| slice_in.set(2, |
| Window::Dimension(rows_out_of_bounds[0], |
| _crop_results[num_box].get()->info()->dimension(2) - rows_out_of_bounds[1], 1)); |
| slice_in.set(1, |
| Window::Dimension(cols_out_of_bounds[0], |
| _crop_results[num_box].get()->info()->dimension(1) - cols_out_of_bounds[1], 1)); |
| |
| int rows_in_bounds = static_cast<int32_t>(_crop_results[num_box].get()->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 = std::make_unique<CLFill>(); |
| kernel->configure(compile_context, _crop_results[num_box].get(), extrapolation_value, |
| &slice_fill_cols_before); |
| //_internal_functions.emplace_back(std::move(kernel)); |
| _internal_functions.push_back(std::move(kernel)); |
| } |
| |
| if (cols_out_of_bounds[1] > 0) |
| { |
| Window slice_fill_cols_after(slice_in); |
| slice_fill_cols_after.set( |
| 1, Window::Dimension(_crop_results[num_box].get()->info()->dimension(1) - cols_out_of_bounds[1], |
| _crop_results[num_box].get()->info()->dimension(1), 1)); |
| auto kernel = std::make_unique<CLFill>(); |
| kernel->configure(compile_context, _crop_results[num_box].get(), extrapolation_value, |
| &slice_fill_cols_after); |
| //_internal_functions.emplace_back(std::move(kernel)); |
| _internal_functions.push_back(std::move(kernel)); |
| } |
| |
| // Copy all elements within the input bounds from the input tensor. |
| int cols_in_bounds = static_cast<int32_t>(_crop_results[num_box].get()->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 = std::make_unique<CLCrop>(); |
| |
| kernel->configure(compile_context, _input, _crop_results[num_box].get(), start_in, end_in, batch_index, |
| extrapolation_value, &slice_in); |
| //_internal_functions.emplace_back(std::move(kernel)); |
| _internal_functions.push_back(std::move(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(_crop_results[num_box].get()->info()->dimension(2) - rows_out_of_bounds[1], |
| _crop_results[num_box].get()->info()->dimension(2), 1)); |
| auto kernel = std::make_unique<CLFill>(); |
| kernel->configure(compile_context, _crop_results[num_box].get(), extrapolation_value, |
| &slice_fill_rows_after); |
| //_internal_functions.emplace_back(std::move(kernel)); |
| _internal_functions.push_back(std::move(kernel)); |
| } |
| } |
| _boxes->unmap(CLScheduler::get().queue()); |
| _box_ind->unmap(CLScheduler::get().queue()); |
| CLScheduler::get().sync(); |
| } |
| |
| void CLCropResize::run() |
| { |
| ARM_COMPUTE_ERROR_ON_MSG(_output == nullptr, "Unconfigured function"); |
| |
| for (unsigned int i = 0; i < _internal_functions.size(); ++i) |
| { |
| _internal_functions[i]->run(); |
| } |
| |
| CLScheduler::get().sync(); |
| for (auto &kernel : _scale) |
| { |
| kernel->run(); |
| } |
| CLScheduler::get().sync(); |
| for (auto &kernel : _copy) |
| { |
| kernel->run(); |
| } |
| CLScheduler::get().sync(); |
| } |
| } // namespace arm_compute |