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authorGeorge Wort <george.wort@arm.com>2019-02-15 15:12:52 +0000
committerManuel Bottini <manuel.bottini@arm.com>2019-03-13 13:54:10 +0000
commit894066de8cc26d1a3aca62dcaa6b30a2a1116028 (patch)
tree9dcb227018ea69fcfb83f7b25be2009fdd16e18e /src/runtime/CL
parentadfb2737046028c042f0aecaff87733a442da29f (diff)
downloadComputeLibrary-894066de8cc26d1a3aca62dcaa6b30a2a1116028.tar.gz
COMPMID-1844: Implement CLCrop
Change-Id: I8822c37adc45960705dc3f32a53214795ba3cf39 Signed-off-by: George Wort <george.wort@arm.com> Reviewed-on: https://review.mlplatform.org/c/789 Reviewed-by: Manuel Bottini <manuel.bottini@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Pablo Marquez <pablo.tello@arm.com>
Diffstat (limited to 'src/runtime/CL')
-rw-r--r--src/runtime/CL/functions/CLCropResize.cpp272
1 files changed, 272 insertions, 0 deletions
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 <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], 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<int32_t>(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<int32_t>(output->info()->dimension(2))) : 0;
+ }
+ else
+ {
+ rows_out_of_bounds[0] = start[1] < 0 ? std::min(-start[1], static_cast<int32_t>(output->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, output->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, output->info()->dimension(1)) : 0;
+ cols_out_of_bounds[1] = end[0] < 0 ? std::min(-end[0], static_cast<int32_t>(output->info()->dimension(1))) : 0;
+ }
+ else
+ {
+ cols_out_of_bounds[0] = start[0] < 0 ? std::min(-start[0], static_cast<int32_t>(output->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, 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<CLMemsetKernel>();
+ 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<int32_t>(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<CLMemsetKernel>();
+ 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<CLMemsetKernel>();
+ 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<int32_t>(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<CLCropKernel>();
+
+ 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<CLMemsetKernel>();
+ 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<CLTensor[]>(_num_boxes);
+ _scale = arm_compute::support::cpp14::make_unique<CLScale[]>(_num_boxes);
+ _scaled_results = arm_compute::support::cpp14::make_unique<CLTensor[]>(_num_boxes);
+ _copy = arm_compute::support::cpp14::make_unique<CLCopyKernel[]>(_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