George Wort | 894066d | 2019-02-15 15:12:52 +0000 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 2019 ARM Limited. |
| 3 | * |
| 4 | * SPDX-License-Identifier: MIT |
| 5 | * |
| 6 | * Permission is hereby granted, free of charge, to any person obtaining a copy |
| 7 | * of this software and associated documentation files (the "Software"), to |
| 8 | * deal in the Software without restriction, including without limitation the |
| 9 | * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| 10 | * sell copies of the Software, and to permit persons to whom the Software is |
| 11 | * furnished to do so, subject to the following conditions: |
| 12 | * |
| 13 | * The above copyright notice and this permission notice shall be included in all |
| 14 | * copies or substantial portions of the Software. |
| 15 | * |
| 16 | * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| 17 | * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| 18 | * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| 19 | * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| 20 | * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| 21 | * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| 22 | * SOFTWARE. |
| 23 | */ |
| 24 | |
| 25 | #include "arm_compute/core/CL/CLHelpers.h" |
| 26 | |
| 27 | #include "arm_compute/runtime/CL/CLScheduler.h" |
| 28 | #include "arm_compute/runtime/CL/functions/CLCropResize.h" |
| 29 | |
| 30 | #include <cstddef> |
| 31 | |
| 32 | namespace arm_compute |
| 33 | { |
| 34 | namespace |
| 35 | { |
| 36 | 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) |
| 37 | { |
| 38 | batch_index = *(reinterpret_cast<int32_t *>(box_ind->ptr_to_element(Coordinates(crop_box_ind)))); |
| 39 | |
| 40 | // _crop_box_ind is used to index crop_boxes and retrieve the appropriate crop box. |
| 41 | // The crop box is specified by normalized coordinates [y0, x0, y1, x1]. |
| 42 | const float x0 = *reinterpret_cast<const float *>(crop_boxes->ptr_to_element(Coordinates(1, crop_box_ind))); |
| 43 | const float y0 = *reinterpret_cast<const float *>(crop_boxes->ptr_to_element(Coordinates(0, crop_box_ind))); |
| 44 | const float x1 = *reinterpret_cast<const float *>(crop_boxes->ptr_to_element(Coordinates(3, crop_box_ind))); |
| 45 | const float y1 = *reinterpret_cast<const float *>(crop_boxes->ptr_to_element(Coordinates(2, crop_box_ind))); |
| 46 | // The normalized coordinates are scaled to retrieve the floating point image coordinates which are rounded to integers. |
| 47 | start = Coordinates(std::floor(x0 * (input->info()->tensor_shape()[1] - 1) + 0.5f), |
| 48 | std::floor(y0 * (input->info()->tensor_shape()[2] - 1) + 0.5f)); |
| 49 | end = Coordinates(std::floor(x1 * (input->info()->tensor_shape()[1] - 1) + 0.5f), |
| 50 | std::floor(y1 * (input->info()->tensor_shape()[2] - 1) + 0.5f)); |
| 51 | const TensorShape out_shape(input->info()->tensor_shape()[0], abs(end[0] - start[0]) + 1, abs(end[1] - start[1]) + 1); |
| 52 | output->info()->set_tensor_shape(out_shape); |
| 53 | } |
| 54 | |
| 55 | inline void run_crop(const ICLTensor *input, ICLTensor *output, uint32_t batch_index, Coordinates start, Coordinates end, float extrapolation_value) |
| 56 | { |
| 57 | bool is_width_flipped = end[0] < start[0]; |
| 58 | bool is_height_flipped = end[1] < start[1]; |
| 59 | /** The number of rows out of bounds at the start and end of output. */ |
Michalis Spyrou | a4f378d | 2019-04-26 14:54:54 +0100 | [diff] [blame] | 60 | std::array<int32_t, 2> rows_out_of_bounds{ 0 }; |
George Wort | 894066d | 2019-02-15 15:12:52 +0000 | [diff] [blame] | 61 | /** The number of columns out of bounds at the start and end of output. */ |
Michalis Spyrou | a4f378d | 2019-04-26 14:54:54 +0100 | [diff] [blame] | 62 | std::array<int32_t, 2> cols_out_of_bounds{ 0 }; |
George Wort | 894066d | 2019-02-15 15:12:52 +0000 | [diff] [blame] | 63 | if(is_height_flipped) |
| 64 | { |
| 65 | rows_out_of_bounds[0] = start[1] >= static_cast<int32_t>(input->info()->dimension(2)) ? std::min(start[1] - input->info()->dimension(2) + 1, output->info()->dimension(2)) : 0; |
| 66 | rows_out_of_bounds[1] = end[1] < 0 ? std::min(-end[1], static_cast<int32_t>(output->info()->dimension(2))) : 0; |
| 67 | } |
| 68 | else |
| 69 | { |
| 70 | rows_out_of_bounds[0] = start[1] < 0 ? std::min(-start[1], static_cast<int32_t>(output->info()->dimension(2))) : 0; |
| 71 | rows_out_of_bounds[1] = end[1] >= static_cast<int32_t>(input->info()->dimension(2)) ? std::min(end[1] - input->info()->dimension(2) + 1, output->info()->dimension(2)) : 0; |
| 72 | } |
| 73 | if(is_width_flipped) |
| 74 | { |
| 75 | cols_out_of_bounds[0] = start[0] >= static_cast<int32_t>(input->info()->dimension(1)) ? std::min(start[0] - input->info()->dimension(1) + 1, output->info()->dimension(1)) : 0; |
| 76 | cols_out_of_bounds[1] = end[0] < 0 ? std::min(-end[0], static_cast<int32_t>(output->info()->dimension(1))) : 0; |
| 77 | } |
| 78 | else |
| 79 | { |
| 80 | cols_out_of_bounds[0] = start[0] < 0 ? std::min(-start[0], static_cast<int32_t>(output->info()->dimension(1))) : 0; |
| 81 | cols_out_of_bounds[1] = end[0] >= static_cast<int32_t>(input->info()->dimension(1)) ? std::min(end[0] - input->info()->dimension(1) + 1, output->info()->dimension(1)) : 0; |
| 82 | } |
| 83 | |
| 84 | Window full_window = calculate_max_window(*output->info()); |
| 85 | |
| 86 | // Full output window: |
| 87 | // -------------------------------- |
| 88 | // | Out of bounds | |
| 89 | // | rows before | |
| 90 | // |------------------------------| |
| 91 | // | Out of | In | Out of | |
| 92 | // | bounds | bounds | bounds | |
| 93 | // | cols | elements | cols | |
| 94 | // | before | copied | after | |
| 95 | // | | from input | | |
| 96 | // |------------------------------| |
| 97 | // | Out of bounds | |
| 98 | // | rows after | |
| 99 | // |------------------------------| |
| 100 | // Use a separate output window for each section of the full output window. |
| 101 | // Fill all output rows that have no elements that are within the input bounds |
| 102 | // with the extrapolation value using memset. |
| 103 | // First for the rows before the in bounds rows. |
| 104 | if(rows_out_of_bounds[0] > 0) |
| 105 | { |
| 106 | Window slice_fill_rows_before(full_window); |
| 107 | slice_fill_rows_before.set(2, Window::Dimension(0, rows_out_of_bounds[0], 1)); |
| 108 | auto kernel = arm_compute::support::cpp14::make_unique<CLMemsetKernel>(); |
| 109 | kernel->configure(output, extrapolation_value, &slice_fill_rows_before); |
| 110 | CLScheduler::get().enqueue(*kernel); |
| 111 | } |
| 112 | |
| 113 | Window slice_in(full_window); |
| 114 | slice_in.set(2, Window::Dimension(rows_out_of_bounds[0], output->info()->dimension(2) - rows_out_of_bounds[1], 1)); |
| 115 | slice_in.set(1, Window::Dimension(cols_out_of_bounds[0], output->info()->dimension(1) - cols_out_of_bounds[1], 1)); |
| 116 | |
| 117 | int rows_in_bounds = static_cast<int32_t>(output->info()->dimension(2)) - rows_out_of_bounds[0] - rows_out_of_bounds[1]; |
| 118 | if(rows_in_bounds > 0) |
| 119 | { |
| 120 | // Fill all elements that share a row with an in bounds element with the extrapolation value. |
| 121 | if(cols_out_of_bounds[0] > 0) |
| 122 | { |
| 123 | Window slice_fill_cols_before(slice_in); |
| 124 | slice_fill_cols_before.set(1, Window::Dimension(0, cols_out_of_bounds[0], 1)); |
| 125 | auto kernel = arm_compute::support::cpp14::make_unique<CLMemsetKernel>(); |
| 126 | kernel->configure(output, extrapolation_value, &slice_fill_cols_before); |
| 127 | CLScheduler::get().enqueue(*kernel); |
| 128 | } |
| 129 | |
| 130 | if(cols_out_of_bounds[1] > 0) |
| 131 | { |
| 132 | Window slice_fill_cols_after(slice_in); |
| 133 | slice_fill_cols_after.set(1, Window::Dimension(output->info()->dimension(1) - cols_out_of_bounds[1], output->info()->dimension(1), 1)); |
| 134 | auto kernel = arm_compute::support::cpp14::make_unique<CLMemsetKernel>(); |
| 135 | kernel->configure(output, extrapolation_value, &slice_fill_cols_after); |
| 136 | CLScheduler::get().enqueue(*kernel); |
| 137 | } |
| 138 | |
| 139 | // Copy all elements within the input bounds from the input tensor. |
| 140 | int cols_in_bounds = static_cast<int32_t>(output->info()->dimension(1)) - cols_out_of_bounds[0] - cols_out_of_bounds[1]; |
| 141 | if(cols_in_bounds > 0) |
| 142 | { |
| 143 | Coordinates2D start_in{ is_width_flipped ? start[0] - cols_out_of_bounds[0] : start[0] + cols_out_of_bounds[0], |
| 144 | is_height_flipped ? start[1] - rows_out_of_bounds[0] : start[1] + rows_out_of_bounds[0] }; |
| 145 | Coordinates2D end_in{ is_width_flipped ? start_in.x - cols_in_bounds + 1 : start_in.x + cols_in_bounds - 1, |
| 146 | is_height_flipped ? start_in.y - rows_in_bounds + 1 : start_in.y + rows_in_bounds - 1 }; |
| 147 | auto kernel = arm_compute::support::cpp14::make_unique<CLCropKernel>(); |
| 148 | |
| 149 | kernel->configure(input, output, start_in, end_in, batch_index, extrapolation_value, &slice_in); |
| 150 | CLScheduler::get().enqueue(*kernel); |
| 151 | } |
| 152 | } |
| 153 | |
| 154 | // Fill all rows after the in bounds elements with the extrapolation value. |
| 155 | if(rows_out_of_bounds[1] > 0) |
| 156 | { |
| 157 | Window slice_fill_rows_after(full_window); |
| 158 | slice_fill_rows_after.set(2, Window::Dimension(output->info()->dimension(2) - rows_out_of_bounds[1], output->info()->dimension(2), 1)); |
| 159 | auto kernel = arm_compute::support::cpp14::make_unique<CLMemsetKernel>(); |
| 160 | kernel->configure(output, extrapolation_value, &slice_fill_rows_after); |
| 161 | CLScheduler::get().enqueue(*kernel); |
| 162 | } |
| 163 | } |
| 164 | } // namespace |
| 165 | |
| 166 | CLCropResize::CLCropResize() |
Michalis Spyrou | a4f378d | 2019-04-26 14:54:54 +0100 | [diff] [blame] | 167 | : _input(nullptr), _boxes(nullptr), _box_ind(nullptr), _output(nullptr), _num_boxes(0), _method(), _extrapolation_value(0), _scale(), _copy(), _crop_results(), _scaled_results() |
George Wort | 894066d | 2019-02-15 15:12:52 +0000 | [diff] [blame] | 168 | { |
| 169 | } |
| 170 | |
| 171 | Status CLCropResize::validate(const ITensorInfo *input, ITensorInfo *boxes, ITensorInfo *box_ind, const ITensorInfo *output, |
| 172 | Coordinates2D crop_size, InterpolationPolicy method, float extrapolation_value) |
| 173 | { |
| 174 | ARM_COMPUTE_RETURN_ERROR_ON(crop_size.x <= 0 || crop_size.y <= 0); |
| 175 | ARM_COMPUTE_RETURN_ERROR_ON(method == InterpolationPolicy::AREA); |
| 176 | ARM_COMPUTE_RETURN_ERROR_ON(boxes->tensor_shape()[0] != 4); |
| 177 | ARM_COMPUTE_RETURN_ERROR_ON(boxes->tensor_shape()[1] != box_ind->tensor_shape()[0]); |
| 178 | TensorInfo temp_info; |
| 179 | ARM_COMPUTE_RETURN_ON_ERROR(CLCropKernel::validate(input->clone().get(), &temp_info, { 0, 0 }, { 1, 1 }, input->dimension(3) - 1, extrapolation_value)); |
| 180 | if(output->total_size() > 0) |
| 181 | { |
| 182 | ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(output, DataType::F32); |
| 183 | ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output); |
| 184 | TensorShape out_shape(input->tensor_shape()[0], crop_size.x, crop_size.y, boxes->tensor_shape()[1]); |
| 185 | ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), out_shape); |
| 186 | } |
| 187 | return Status{}; |
| 188 | } |
| 189 | |
| 190 | void CLCropResize::configure(const ICLTensor *input, ICLTensor *boxes, ICLTensor *box_ind, ICLTensor *output, Coordinates2D crop_size, |
| 191 | InterpolationPolicy method, float extrapolation_value) |
| 192 | { |
| 193 | ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); |
| 194 | ARM_COMPUTE_ERROR_THROW_ON(CLCropResize::validate(input->info(), boxes->info(), box_ind->info(), output->info(), crop_size, method, extrapolation_value)); |
| 195 | |
| 196 | _num_boxes = boxes->info()->tensor_shape()[1]; |
| 197 | TensorShape out_shape(input->info()->tensor_shape()[0], crop_size.x, crop_size.y); |
| 198 | |
| 199 | _input = input; |
| 200 | _boxes = boxes; |
| 201 | _box_ind = box_ind; |
| 202 | _output = output; |
| 203 | _method = method; |
| 204 | _extrapolation_value = extrapolation_value; |
| 205 | |
| 206 | // For each crop box: |
| 207 | // - The initial cropped image is produced as specified by boxes[i] from the 3D image input[box_ind[i]]. |
| 208 | // Possibly using a CLCropKernel and up to four CLMemsetKernels. |
| 209 | // - A tensor is required to hold this initial cropped image. |
| 210 | // - A scale function is used to resize the cropped image to the size specified by crop_size. |
| 211 | // - A tensor is required to hold the final scaled image before it is copied into the 4D output |
| 212 | // that will hold all final cropped and scaled 3D images using CLCopyKernel. |
George Wort | 894066d | 2019-02-15 15:12:52 +0000 | [diff] [blame] | 213 | for(unsigned int i = 0; i < _num_boxes; ++i) |
| 214 | { |
Michalis Spyrou | a4f378d | 2019-04-26 14:54:54 +0100 | [diff] [blame] | 215 | auto crop_tensor = support::cpp14::make_unique<CLTensor>(); |
George Wort | 894066d | 2019-02-15 15:12:52 +0000 | [diff] [blame] | 216 | TensorInfo crop_result_info(1, DataType::F32); |
| 217 | crop_result_info.set_data_layout(DataLayout::NHWC); |
Michalis Spyrou | a4f378d | 2019-04-26 14:54:54 +0100 | [diff] [blame] | 218 | crop_tensor->allocator()->init(crop_result_info); |
| 219 | _crop_results.emplace_back(std::move(crop_tensor)); |
George Wort | 894066d | 2019-02-15 15:12:52 +0000 | [diff] [blame] | 220 | |
Michalis Spyrou | a4f378d | 2019-04-26 14:54:54 +0100 | [diff] [blame] | 221 | auto scale_tensor = support::cpp14::make_unique<CLTensor>(); |
George Wort | 894066d | 2019-02-15 15:12:52 +0000 | [diff] [blame] | 222 | TensorInfo scaled_result_info(out_shape, 1, DataType::F32); |
| 223 | scaled_result_info.set_data_layout(DataLayout::NHWC); |
Michalis Spyrou | a4f378d | 2019-04-26 14:54:54 +0100 | [diff] [blame] | 224 | scale_tensor->allocator()->init(scaled_result_info); |
| 225 | _scaled_results.emplace_back(std::move(scale_tensor)); |
George Wort | 894066d | 2019-02-15 15:12:52 +0000 | [diff] [blame] | 226 | } |
| 227 | } |
| 228 | |
| 229 | void CLCropResize::run() |
| 230 | { |
| 231 | ARM_COMPUTE_ERROR_ON_MSG(_output == nullptr, "Unconfigured function"); |
| 232 | // The contents of _boxes and _box_ind are required to calculate the shape |
| 233 | // of the initial cropped image and thus are required to configure the |
| 234 | // kernels used for cropping and scaling. |
| 235 | _boxes->map(CLScheduler::get().queue()); |
| 236 | _box_ind->map(CLScheduler::get().queue()); |
| 237 | for(unsigned int i = 0; i < _num_boxes; ++i) |
| 238 | { |
| 239 | // Size of the crop box in _boxes and thus the shape of _crop_results[i] |
| 240 | // may not be known until run-time and so the kernels cannot be configured until then. |
| 241 | uint32_t batch_index; |
Michalis Spyrou | a4f378d | 2019-04-26 14:54:54 +0100 | [diff] [blame] | 242 | Coordinates start{}; |
| 243 | Coordinates end{}; |
| 244 | configure_crop(_input, _boxes, _box_ind, _crop_results[i].get(), i, start, end, batch_index); |
| 245 | |
| 246 | auto scale_kernel = support::cpp14::make_unique<CLScale>(); |
| 247 | scale_kernel->configure(_crop_results[i].get(), _scaled_results[i].get(), _method, BorderMode::CONSTANT, PixelValue(_extrapolation_value), SamplingPolicy::TOP_LEFT); |
| 248 | _scale.emplace_back(std::move(scale_kernel)); |
George Wort | 894066d | 2019-02-15 15:12:52 +0000 | [diff] [blame] | 249 | |
| 250 | Window win = calculate_max_window(*_output->info()); |
| 251 | win.set(3, Window::Dimension(i, i + 1, 1)); |
George Wort | 894066d | 2019-02-15 15:12:52 +0000 | [diff] [blame] | 252 | |
Michalis Spyrou | a4f378d | 2019-04-26 14:54:54 +0100 | [diff] [blame] | 253 | auto copy_kernel = support::cpp14::make_unique<CLCopyKernel>(); |
| 254 | copy_kernel->configure(_scaled_results[i].get(), _output, PaddingList(), &win); |
| 255 | _copy.emplace_back(std::move(copy_kernel)); |
George Wort | 894066d | 2019-02-15 15:12:52 +0000 | [diff] [blame] | 256 | |
Michalis Spyrou | a4f378d | 2019-04-26 14:54:54 +0100 | [diff] [blame] | 257 | _crop_results[i]->allocator()->allocate(); |
| 258 | _scaled_results[i]->allocator()->allocate(); |
| 259 | |
| 260 | run_crop(_input, _crop_results[i].get(), batch_index, start, end, _extrapolation_value); |
George Wort | 894066d | 2019-02-15 15:12:52 +0000 | [diff] [blame] | 261 | } |
| 262 | _boxes->unmap(CLScheduler::get().queue()); |
| 263 | _box_ind->unmap(CLScheduler::get().queue()); |
| 264 | CLScheduler::get().sync(); |
Michalis Spyrou | a4f378d | 2019-04-26 14:54:54 +0100 | [diff] [blame] | 265 | for(auto &kernel : _scale) |
George Wort | 894066d | 2019-02-15 15:12:52 +0000 | [diff] [blame] | 266 | { |
Michalis Spyrou | a4f378d | 2019-04-26 14:54:54 +0100 | [diff] [blame] | 267 | kernel->run(); |
George Wort | 894066d | 2019-02-15 15:12:52 +0000 | [diff] [blame] | 268 | } |
| 269 | CLScheduler::get().sync(); |
Michalis Spyrou | a4f378d | 2019-04-26 14:54:54 +0100 | [diff] [blame] | 270 | for(auto &kernel : _copy) |
George Wort | 894066d | 2019-02-15 15:12:52 +0000 | [diff] [blame] | 271 | { |
Michalis Spyrou | a4f378d | 2019-04-26 14:54:54 +0100 | [diff] [blame] | 272 | CLScheduler::get().enqueue(*kernel, true); |
George Wort | 894066d | 2019-02-15 15:12:52 +0000 | [diff] [blame] | 273 | } |
| 274 | CLScheduler::get().sync(); |
| 275 | } |
| 276 | } // namespace arm_compute |