| /* |
| * 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/Helpers.h" |
| |
| using namespace arm_compute; |
| |
| Window arm_compute::calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size) |
| { |
| if(!skip_border) |
| { |
| border_size = BorderSize(0); |
| } |
| |
| const Coordinates &anchor = valid_region.anchor; |
| const TensorShape &shape = valid_region.shape; |
| |
| Window window; |
| |
| window.set(0, Window::Dimension( |
| // Skip the border left of the image |
| anchor[0] + border_size.left, |
| // Skip the border right of the image |
| // Make sure the window width is a multiple of the step size |
| anchor[0] + border_size.left + ceil_to_multiple(std::max(0, static_cast<int>(shape[0]) - static_cast<int>(border_size.left) - static_cast<int>(border_size.right)), steps[0]), |
| steps[0])); |
| |
| size_t n = 1; |
| |
| if(anchor.num_dimensions() > 1) |
| { |
| window.set(1, Window::Dimension( |
| // Skip the border above the image |
| anchor[1] + border_size.top, |
| // Skip the border below the image |
| anchor[1] + border_size.top + ceil_to_multiple(std::max(0, static_cast<int>(shape[1]) - static_cast<int>(border_size.top) - static_cast<int>(border_size.bottom)), steps[1]), |
| steps[1])); |
| |
| ++n; |
| } |
| |
| for(; n < anchor.num_dimensions(); ++n) |
| { |
| window.set(n, Window::Dimension(anchor[n], std::max<size_t>(1, shape[n]))); |
| } |
| |
| for(; n < Coordinates::num_max_dimensions; ++n) |
| { |
| window.set(n, Window::Dimension(0, 1)); |
| } |
| |
| return window; |
| } |
| |
| Window arm_compute::calculate_max_enlarged_window(const ValidRegion &valid_region, const Steps &steps, BorderSize border_size) |
| { |
| const Coordinates &anchor = valid_region.anchor; |
| const TensorShape &shape = valid_region.shape; |
| |
| Window window; |
| |
| window.set(0, Window::Dimension( |
| // move the anchor to the start from the border |
| anchor[0] - border_size.left, |
| // move the anchor to include the right end border |
| // Make sure the window width is a multiple of the step size |
| anchor[0] - border_size.left + ceil_to_multiple(shape[0] + border_size.left + border_size.right, steps[0]), |
| steps[0])); |
| |
| size_t n = 1; |
| |
| if(anchor.num_dimensions() > 1) |
| { |
| window.set(1, Window::Dimension( |
| // Include the border above the image |
| anchor[1] - border_size.top, |
| // Include the border below the image |
| anchor[1] - border_size.top + ceil_to_multiple(shape[1] + border_size.top + border_size.bottom, steps[1]), |
| steps[1])); |
| |
| ++n; |
| } |
| |
| if(anchor.num_dimensions() > 2) |
| { |
| window.set(2, Window::Dimension(0, std::max<size_t>(1, shape[n]), steps[2])); |
| |
| ++n; |
| } |
| |
| for(; n < anchor.num_dimensions(); ++n) |
| { |
| window.set(n, Window::Dimension(anchor[n], std::max<size_t>(1, shape[n]))); |
| } |
| |
| for(; n < Coordinates::num_max_dimensions; ++n) |
| { |
| window.set(n, Window::Dimension(0, 1)); |
| } |
| |
| return window; |
| } |
| |
| Window arm_compute::calculate_max_window_horizontal(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size) |
| { |
| if(skip_border) |
| { |
| border_size.top = 0; |
| border_size.bottom = 0; |
| } |
| else |
| { |
| border_size.left = 0; |
| border_size.right = 0; |
| } |
| |
| const Coordinates &anchor = valid_region.anchor; |
| const TensorShape &shape = valid_region.shape; |
| |
| Window window; |
| |
| window.set(0, Window::Dimension( |
| // Skip the border left of the image |
| anchor[0] + border_size.left, |
| // Skip the border right of the image |
| // Make sure the window width is a multiple of the step size |
| anchor[0] + border_size.left + ceil_to_multiple(std::max(0, static_cast<int>(shape[0]) - static_cast<int>(border_size.left) - static_cast<int>(border_size.right)), steps[0]), |
| steps[0])); |
| |
| size_t n = 1; |
| |
| if(anchor.num_dimensions() > 1) |
| { |
| window.set(1, Window::Dimension( |
| // Skip the border above the image |
| anchor[1] - border_size.top, |
| // Skip the border below the image |
| anchor[1] + shape[1] + border_size.bottom, |
| 1)); |
| |
| ++n; |
| } |
| |
| for(; n < anchor.num_dimensions(); ++n) |
| { |
| window.set(n, Window::Dimension(anchor[n], std::max<size_t>(1, shape[n]))); |
| } |
| |
| for(; n < Coordinates::num_max_dimensions; ++n) |
| { |
| window.set(n, Window::Dimension(0, 1)); |
| } |
| |
| return window; |
| } |
| |
| ValidRegion arm_compute::calculate_valid_region_scale(const ITensorInfo &src_info, const TensorShape &dst_shape, |
| InterpolationPolicy interpolate_policy, SamplingPolicy sampling_policy, bool border_undefined) |
| { |
| const float scale_x = static_cast<float>(dst_shape[0]) / src_info.tensor_shape()[0]; |
| const float scale_y = static_cast<float>(dst_shape[1]) / src_info.tensor_shape()[1]; |
| const float sampling_point = (sampling_policy == SamplingPolicy::CENTER) ? 0.5f : 0.0f; |
| |
| // Get input's valid region start and end points |
| const int valid_start_in_x = src_info.valid_region().anchor[0]; |
| const int valid_start_in_y = src_info.valid_region().anchor[1]; |
| const int valid_end_in_x = src_info.valid_region().anchor[0] + src_info.valid_region().shape[0]; |
| const int valid_end_in_y = src_info.valid_region().anchor[1] + src_info.valid_region().shape[1]; |
| |
| // Initialize output's valid region start and end points |
| auto valid_start_out_x = static_cast<int>(valid_start_in_x * scale_x); |
| auto valid_start_out_y = static_cast<int>(valid_start_in_y * scale_y); |
| auto valid_end_out_x = std::min<int>(std::ceil(valid_end_in_x * scale_x), dst_shape[0]); |
| auto valid_end_out_y = std::min<int>(std::ceil(valid_end_in_y * scale_y), dst_shape[1]); |
| |
| // Handle valid points in case of the bi-linear interpolation |
| if(border_undefined) |
| { |
| switch(interpolate_policy) |
| { |
| case InterpolationPolicy::NEAREST_NEIGHBOR: |
| { |
| // (start_out + sampling_point) >= (start_in * scale) |
| // start_out = ceil((start_in * scale) - sampling_point) |
| valid_start_out_x = std::ceil(valid_start_in_x * scale_x - sampling_point); |
| valid_start_out_y = std::ceil(valid_start_in_y * scale_y - sampling_point); |
| |
| // (end_out - 1 + sampling_point) < (end_in * scale) |
| // end_out = ceil((end_in * scale) - sampling_point); // <-- ceil(x - 1) strictly less |
| valid_end_out_x = std::ceil(valid_end_in_x * scale_x - sampling_point); |
| valid_end_out_y = std::ceil(valid_end_in_y * scale_y - sampling_point); |
| break; |
| } |
| case InterpolationPolicy::BILINEAR: |
| { |
| // (start_out + sampling_point) >= ((start_in + sampling_point) * scale) |
| // start_out = ceil(((start_in + sampling_point) * scale) - sampling_point) |
| valid_start_out_x = std::ceil((valid_start_in_x + sampling_point) * scale_x - sampling_point); |
| valid_start_out_y = std::ceil((valid_start_in_y + sampling_point) * scale_y - sampling_point); |
| |
| // (end_out - 1 + sampling_point) <= ((end_in - 1 + sampling_point) * scale) |
| // end_out = floor(((end_in - 1 + sampling_point) * scale) - sampling_point + 1) |
| valid_end_out_x = std::floor((valid_end_in_x - 1.f + sampling_point) * scale_x - sampling_point + 1.f); |
| valid_end_out_y = std::floor((valid_end_in_y - 1.f + sampling_point) * scale_y - sampling_point + 1.f); |
| break; |
| } |
| case InterpolationPolicy::AREA: |
| break; |
| default: |
| { |
| ARM_COMPUTE_ERROR("Invalid InterpolationPolicy"); |
| break; |
| } |
| } |
| } |
| |
| // Setup output valid region |
| ValidRegion valid_region{ Coordinates(), dst_shape, src_info.tensor_shape().num_dimensions() }; |
| |
| valid_region.anchor.set(0, std::max(0, valid_start_out_x)); |
| valid_region.anchor.set(1, std::max(0, valid_start_out_y)); |
| |
| valid_region.shape.set(0, std::min<size_t>(valid_end_out_x - valid_start_out_x, dst_shape[0])); |
| valid_region.shape.set(1, std::min<size_t>(valid_end_out_y - valid_start_out_y, dst_shape[1])); |
| |
| return valid_region; |
| } |