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/*
* Copyright (c) 2017 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/CLOpticalFlow.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/CL/kernels/CLLKTrackerKernel.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Window.h"
#include "arm_compute/runtime/CL/CLPyramid.h"
#include "arm_compute/runtime/CL/CLScheduler.h"
#include "arm_compute/runtime/CL/CLTensor.h"
#include "arm_compute/runtime/CL/CLTensorAllocator.h"
#include "arm_compute/runtime/CL/functions/CLScharr3x3.h"
#include "support/ToolchainSupport.h"
using namespace arm_compute;
CLOpticalFlow::CLOpticalFlow(std::shared_ptr<IMemoryManager> memory_manager) // NOLINT
: _memory_group(std::move(memory_manager)),
_tracker_init_kernel(),
_tracker_stage0_kernel(),
_tracker_stage1_kernel(),
_tracker_finalize_kernel(),
_func_scharr(),
_scharr_gx(),
_scharr_gy(),
_old_points(nullptr),
_new_points_estimates(nullptr),
_new_points(nullptr),
_old_points_internal(),
_new_points_internal(),
_coefficient_table(),
_old_values(),
_num_levels(0)
{
}
void CLOpticalFlow::configure(const CLPyramid *old_pyramid, const CLPyramid *new_pyramid,
const ICLKeyPointArray *old_points, const ICLKeyPointArray *new_points_estimates, ICLKeyPointArray *new_points,
Termination termination, float epsilon, size_t num_iterations, size_t window_dimension, bool use_initial_estimate,
BorderMode border_mode, uint8_t constant_border_value)
{
ARM_COMPUTE_ERROR_ON(nullptr == old_pyramid);
ARM_COMPUTE_ERROR_ON(nullptr == new_pyramid);
ARM_COMPUTE_ERROR_ON(nullptr == old_points);
ARM_COMPUTE_ERROR_ON(nullptr == new_points_estimates);
ARM_COMPUTE_ERROR_ON(nullptr == new_points);
ARM_COMPUTE_ERROR_ON(old_pyramid->info()->num_levels() != new_pyramid->info()->num_levels());
ARM_COMPUTE_ERROR_ON(0 == old_pyramid->info()->num_levels());
ARM_COMPUTE_ERROR_ON(old_pyramid->info()->width() != new_pyramid->info()->width());
ARM_COMPUTE_ERROR_ON(old_pyramid->info()->height() != new_pyramid->info()->height());
ARM_COMPUTE_ERROR_ON(use_initial_estimate && old_points->num_values() != new_points_estimates->num_values());
// Set member variables
_old_points = old_points;
_new_points_estimates = new_points_estimates;
_new_points = new_points;
_num_levels = old_pyramid->info()->num_levels();
const float pyr_scale = old_pyramid->info()->scale();
const int list_length = old_points->num_values();
const int old_values_list_length = list_length * window_dimension * window_dimension;
// Create kernels and tensors
_tracker_init_kernel = arm_compute::support::cpp14::make_unique<CLLKTrackerInitKernel[]>(_num_levels);
_tracker_stage0_kernel = arm_compute::support::cpp14::make_unique<CLLKTrackerStage0Kernel[]>(_num_levels);
_tracker_stage1_kernel = arm_compute::support::cpp14::make_unique<CLLKTrackerStage1Kernel[]>(_num_levels);
_func_scharr = arm_compute::support::cpp14::make_unique<CLScharr3x3[]>(_num_levels);
_scharr_gx = arm_compute::support::cpp14::make_unique<CLTensor[]>(_num_levels);
_scharr_gy = arm_compute::support::cpp14::make_unique<CLTensor[]>(_num_levels);
// Create internal keypoint arrays
_old_points_internal = arm_compute::support::cpp14::make_unique<CLLKInternalKeypointArray>(list_length);
_old_points_internal->resize(list_length);
_new_points_internal = arm_compute::support::cpp14::make_unique<CLLKInternalKeypointArray>(list_length);
_new_points_internal->resize(list_length);
_coefficient_table = arm_compute::support::cpp14::make_unique<CLCoefficientTableArray>(list_length);
_coefficient_table->resize(list_length);
_old_values = arm_compute::support::cpp14::make_unique<CLOldValueArray>(old_values_list_length);
_old_values->resize(old_values_list_length);
_new_points->resize(list_length);
for(size_t i = 0; i < _num_levels; ++i)
{
// Get images from the ith level of old and right pyramid
ICLImage *old_ith_input = old_pyramid->get_pyramid_level(i);
ICLImage *new_ith_input = new_pyramid->get_pyramid_level(i);
// Get width and height of images
const unsigned int width_ith = old_ith_input->info()->dimension(0);
const unsigned int height_ith = new_ith_input->info()->dimension(1);
// Initialize Scharr tensors
TensorInfo tensor_info(TensorShape(width_ith, height_ith), 1, DataType::S16);
_scharr_gx[i].allocator()->init(tensor_info);
_scharr_gy[i].allocator()->init(tensor_info);
// Manage intermediate buffers
_memory_group.manage(_scharr_gx.get() + i);
_memory_group.manage(_scharr_gy.get() + i);
// Init Scharr kernel
_func_scharr[i].configure(old_ith_input, &_scharr_gx[i], &_scharr_gy[i], border_mode, constant_border_value);
// Init Lucas-Kanade init kernel
_tracker_init_kernel[i].configure(old_points, new_points_estimates, _old_points_internal.get(), _new_points_internal.get(), use_initial_estimate, i, _num_levels, pyr_scale);
// Init Lucas-Kanade stage0 kernel
_tracker_stage0_kernel[i].configure(old_ith_input, &_scharr_gx[i], &_scharr_gy[i],
_old_points_internal.get(), _new_points_internal.get(), _coefficient_table.get(), _old_values.get(),
window_dimension, i);
// Init Lucas-Kanade stage1 kernel
_tracker_stage1_kernel[i].configure(new_ith_input, _new_points_internal.get(), _coefficient_table.get(), _old_values.get(),
termination, epsilon, num_iterations, window_dimension, i);
// Allocate intermediate buffers
_scharr_gx[i].allocator()->allocate();
_scharr_gy[i].allocator()->allocate();
}
// Finalize Lucas-Kanade
_tracker_finalize_kernel.configure(_new_points_internal.get(), new_points);
}
void CLOpticalFlow::run()
{
ARM_COMPUTE_ERROR_ON_MSG(_num_levels == 0, "Unconfigured function");
_memory_group.acquire();
for(unsigned int level = _num_levels; level > 0; --level)
{
// Run Scharr kernel
_func_scharr[level - 1].run();
// Run Lucas-Kanade init kernel
CLScheduler::get().enqueue(_tracker_init_kernel[level - 1]);
// Run Lucas-Kanade stage0 kernel
CLScheduler::get().enqueue(_tracker_stage0_kernel[level - 1]);
// Run Lucas-Kanade stage1 kernel
CLScheduler::get().enqueue(_tracker_stage1_kernel[level - 1]);
}
CLScheduler::get().enqueue(_tracker_finalize_kernel, true);
_memory_group.release();
}