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-rw-r--r--src/core/CL/kernels/CLFastCornersKernel.cpp172
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diff --git a/src/core/CL/kernels/CLFastCornersKernel.cpp b/src/core/CL/kernels/CLFastCornersKernel.cpp
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+++ b/src/core/CL/kernels/CLFastCornersKernel.cpp
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+/*
+ * Copyright (c) 2016, 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/core/CL/kernels/CLFastCornersKernel.h"
+
+#include "arm_compute/core/CL/CLKernelLibrary.h"
+#include "arm_compute/core/CL/ICLTensor.h"
+#include "arm_compute/core/CL/OpenCL.h"
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/IAccessWindow.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/Window.h"
+
+#include <set>
+#include <string>
+
+using namespace arm_compute;
+
+CLFastCornersKernel::CLFastCornersKernel()
+ : ICLKernel(), _input(nullptr), _output(nullptr)
+{
+}
+
+BorderSize CLFastCornersKernel::border_size() const
+{
+ return BorderSize(3);
+}
+
+void CLFastCornersKernel::configure(const ICLImage *input, ICLImage *output, float threshold, bool non_max_suppression, BorderMode border_mode)
+{
+ ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(input);
+ ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(output);
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
+ ARM_COMPUTE_ERROR_ON_MSG(border_mode != BorderMode::UNDEFINED, "Not implemented");
+
+ _input = input;
+ _output = output;
+
+ // Create build options
+ std::set<std::string> build_opts;
+
+ if(non_max_suppression)
+ {
+ build_opts.emplace("-DUSE_MAXSUPPRESSION");
+ }
+
+ // Create kernel
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("fast_corners", build_opts));
+
+ // Set static kernel arguments
+ unsigned int idx = 2 * num_arguments_per_2D_tensor(); // Skip the input and output parameters
+ _kernel.setArg<cl_float>(idx, static_cast<float>(threshold));
+
+ // Configure kernel window
+ constexpr unsigned int num_elems_processed_per_iteration = 1;
+ constexpr unsigned int num_elems_read_per_iteration = 7;
+ constexpr unsigned int num_rows_read_per_iteration = 3;
+
+ Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration), border_mode == BorderMode::UNDEFINED, BorderSize(3));
+
+ AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration);
+ AccessWindowRectangle input_access(input->info(), -border_size().left, -border_size().top, num_elems_read_per_iteration, num_rows_read_per_iteration);
+
+ update_window_and_padding(win, input_access, output_access);
+
+ output_access.set_valid_region(win, input->info()->valid_region(), border_mode == BorderMode::UNDEFINED, border_size());
+
+ ICLKernel::configure(win);
+}
+
+void CLFastCornersKernel::run(const Window &window, cl::CommandQueue &queue)
+{
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
+
+ Window slice = window.first_slice_window_2D();
+
+ do
+ {
+ unsigned int idx = 0;
+ add_2D_tensor_argument(idx, _input, slice);
+ add_2D_tensor_argument(idx, _output, slice);
+ enqueue(queue, *this, slice);
+ }
+ while(window.slide_window_slice_2D(slice));
+}
+
+CLCopyToArrayKernel::CLCopyToArrayKernel()
+ : ICLKernel(), _input(nullptr), _corners(nullptr), _num_buffer(nullptr)
+{
+}
+
+void CLCopyToArrayKernel::configure(const ICLImage *input, bool update_number, ICLKeyPointArray *corners, cl::Buffer *num_buffers)
+{
+ ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(input);
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
+ ARM_COMPUTE_ERROR_ON(corners == nullptr);
+ ARM_COMPUTE_ERROR_ON(num_buffers == nullptr);
+
+ _input = input;
+ _corners = corners;
+ _num_buffer = num_buffers;
+
+ std::set<std::string> build_opts;
+
+ if(update_number)
+ {
+ build_opts.emplace("-DUPDATE_NUMBER");
+ }
+
+ // Create kernel
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("copy_to_keypoint", build_opts));
+
+ //Get how many pixels skipped in the x dimension in the previous stages
+ unsigned int offset = _input->info()->valid_region().anchor.x();
+
+ // Set static kernel arguments
+ unsigned int idx = num_arguments_per_2D_tensor(); // Skip the input and output parameters
+ _kernel.setArg<unsigned int>(idx++, corners->max_num_values());
+ _kernel.setArg<cl_uint>(idx++, offset);
+ _kernel.setArg(idx++, *_num_buffer);
+ _kernel.setArg(idx++, _corners->cl_buffer());
+
+ // Configure kernel window
+ constexpr unsigned int num_elems_processed_per_iteration = 1;
+ Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
+ update_window_and_padding(win,
+ AccessWindowHorizontal(input->info(), 0, num_elems_processed_per_iteration));
+ ICLKernel::configure(win);
+}
+
+void CLCopyToArrayKernel::run(const Window &window, cl::CommandQueue &queue)
+{
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
+
+ //Initialise the _num_buffer as it used as both input and output
+ static const unsigned int zero_init = 0;
+ queue.enqueueWriteBuffer(*_num_buffer, CL_FALSE, 0, sizeof(unsigned int), &zero_init);
+
+ Window slice = window.first_slice_window_2D();
+
+ do
+ {
+ unsigned int idx = 0;
+ add_2D_tensor_argument(idx, _input, slice);
+ enqueue(queue, *this, slice);
+ }
+ while(window.slide_window_slice_2D(slice));
+}