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diff --git a/src/core/CL/kernels/CLCannyEdgeKernel.cpp b/src/core/CL/kernels/CLCannyEdgeKernel.cpp
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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/core/CL/kernels/CLCannyEdgeKernel.h"
+
+#include "arm_compute/core/CL/CLHelpers.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/Helpers.h"
+#include "arm_compute/core/Validate.h"
+
+using namespace arm_compute;
+
+CLGradientKernel::CLGradientKernel()
+ : _gx(nullptr), _gy(nullptr), _magnitude(nullptr), _phase(nullptr)
+{
+}
+
+void CLGradientKernel::configure(const ICLTensor *gx, const ICLTensor *gy, ICLTensor *magnitude, ICLTensor *phase, int32_t norm_type)
+{
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(gx, 1, DataType::S16, DataType::S32);
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(gy, 1, DataType::S16, DataType::S32);
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(magnitude, 1, DataType::U16, DataType::U32);
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(phase, 1, DataType::U8);
+ ARM_COMPUTE_ERROR_ON_MSG(data_size_from_type(gx->info()->data_type()) != data_size_from_type(gy->info()->data_type()),
+ "Gx and Gy must have the same pixel size");
+ ARM_COMPUTE_ERROR_ON_MSG(data_size_from_type(gx->info()->data_type()) != data_size_from_type(magnitude->info()->data_type()),
+ "Mag must have the same pixel size as Gx and Gy");
+
+ _gx = gx;
+ _gy = gy;
+ _magnitude = magnitude;
+ _phase = phase;
+
+ // Create build opts
+ std::set<std::string> built_opts;
+ built_opts.emplace("-DDATA_TYPE_IN=" + get_cl_type_from_data_type(gx->info()->data_type()));
+ built_opts.emplace("-DDATA_TYPE_OUT=" + get_cl_type_from_data_type(gx->info()->data_type()));
+
+ // Create kernel
+ const std::string kernel_name = (norm_type == 1) ? std::string("combine_gradients_L1") : std::string("combine_gradients_L2");
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, built_opts));
+
+ // Configure kernel window
+ constexpr unsigned int num_elems_processed_per_iteration = 4;
+
+ Window win = calculate_max_window(*_gx->info(), Steps(num_elems_processed_per_iteration));
+
+ AccessWindowHorizontal gx_access(_gx->info(), 0, num_elems_processed_per_iteration);
+ AccessWindowHorizontal gy_access(_gy->info(), 0, num_elems_processed_per_iteration);
+ AccessWindowHorizontal mag_access(_magnitude->info(), 0, num_elems_processed_per_iteration);
+ AccessWindowHorizontal phase_access(_phase->info(), 0, num_elems_processed_per_iteration);
+
+ update_window_and_padding(win, gx_access, gy_access, mag_access, phase_access);
+
+ mag_access.set_valid_region(win, _gx->info()->valid_region());
+ phase_access.set_valid_region(win, _gx->info()->valid_region());
+
+ ICLKernel::configure(win);
+}
+
+void CLGradientKernel::run(const Window &window, cl::CommandQueue &queue)
+{
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
+
+ Window slice = window.first_slice_window_2D();
+ do
+ {
+ unsigned int idx = 0;
+ add_2D_tensor_argument(idx, _gx, slice);
+ add_2D_tensor_argument(idx, _gy, slice);
+ add_2D_tensor_argument(idx, _magnitude, slice);
+ add_2D_tensor_argument(idx, _phase, slice);
+ enqueue(queue, *this, slice);
+ }
+ while(window.slide_window_slice_2D(slice));
+}
+
+CLEdgeNonMaxSuppressionKernel::CLEdgeNonMaxSuppressionKernel()
+ : _magnitude(nullptr), _phase(nullptr), _output(nullptr)
+{
+}
+
+BorderSize CLEdgeNonMaxSuppressionKernel::border_size() const
+{
+ return BorderSize(1);
+}
+
+void CLEdgeNonMaxSuppressionKernel::configure(const ICLTensor *magnitude, const ICLTensor *phase, ICLTensor *output, int32_t lower_thr, bool border_undefined)
+{
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(magnitude, 1, DataType::U16, DataType::U32);
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(phase, 1, DataType::U8);
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U16, DataType::U32);
+
+ _magnitude = magnitude;
+ _phase = phase;
+ _output = output;
+
+ // Create build opts
+ std::set<std::string> built_opts;
+ built_opts.emplace("-DDATA_TYPE_IN=" + get_cl_type_from_data_type(magnitude->info()->data_type()));
+ built_opts.emplace("-DDATA_TYPE_OUT=" + get_cl_type_from_data_type(output->info()->data_type()));
+
+ // Create kernel
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("suppress_non_maximum", built_opts));
+
+ // Set minimum threshold argument
+ unsigned int idx = 3 * num_arguments_per_2D_tensor(); //Skip the input and output parameters
+ _kernel.setArg(idx++, lower_thr);
+
+ // Configure kernel window
+ constexpr unsigned int num_elems_processed_per_iteration = 1;
+ constexpr unsigned int num_elems_read_written_per_iteration = 3;
+
+ Window win = calculate_max_window(*_magnitude->info(), Steps(num_elems_processed_per_iteration), border_undefined, border_size());
+
+ AccessWindowRectangle mag_access(_magnitude->info(), -border_size().left, -border_size().top,
+ num_elems_read_written_per_iteration, num_elems_read_written_per_iteration);
+ AccessWindowHorizontal phase_access(_phase->info(), 0, num_elems_processed_per_iteration);
+ AccessWindowHorizontal output_access(_output->info(), 0, num_elems_processed_per_iteration);
+
+ update_window_and_padding(win, mag_access, phase_access, output_access);
+
+ output_access.set_valid_region(win, _magnitude->info()->valid_region(), border_undefined, border_size());
+
+ ICLKernel::configure(win);
+}
+
+void CLEdgeNonMaxSuppressionKernel::run(const Window &window, cl::CommandQueue &queue)
+{
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
+
+ Window slice = window.first_slice_window_2D();
+ do
+ {
+ unsigned int idx = 0;
+ add_2D_tensor_argument(idx, _magnitude, slice);
+ add_2D_tensor_argument(idx, _phase, slice);
+ add_2D_tensor_argument(idx, _output, slice);
+ enqueue(queue, *this, slice);
+ }
+ while(window.slide_window_slice_2D(slice));
+}
+
+CLEdgeTraceKernel::CLEdgeTraceKernel()
+ : _input(nullptr), _output(nullptr), _lower_thr(0), _upper_thr(0), _visited(nullptr), _recorded(nullptr), _l1_stack(nullptr), _l1_stack_counter(nullptr)
+{
+}
+
+void CLEdgeTraceKernel::configure(const ICLTensor *input, ICLTensor *output, int32_t upper_thr, int32_t lower_thr,
+ ICLTensor *visited, ICLTensor *recorded, ICLTensor *l1_stack, ICLTensor *l1_stack_counter)
+{
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U16, DataType::U32);
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(visited, 1, DataType::U32);
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(recorded, 1, DataType::U32);
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(l1_stack, 1, DataType::S32);
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(l1_stack_counter, 1, DataType::U8);
+
+ _input = input;
+ _output = output;
+ _lower_thr = lower_thr;
+ _upper_thr = upper_thr;
+ _visited = visited;
+ _recorded = recorded;
+ _l1_stack = l1_stack;
+ _l1_stack_counter = l1_stack_counter;
+
+ // Create build opts
+ std::set<std::string> built_opts;
+ built_opts.emplace("-DDATA_TYPE_IN=" + get_cl_type_from_data_type(input->info()->data_type()));
+ built_opts.emplace("-DDATA_TYPE_OUT=" + get_cl_type_from_data_type(output->info()->data_type()));
+
+ // Create kernel
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("hysteresis", built_opts));
+
+ // Set constant kernel args
+ unsigned int width = _input->info()->dimension(0);
+ unsigned int height = _input->info()->dimension(1);
+ unsigned int idx = 6 * num_arguments_per_2D_tensor(); //Skip the input and output parameters
+ _kernel.setArg(idx++, static_cast<cl_uint>(_lower_thr));
+ _kernel.setArg(idx++, static_cast<cl_uint>(_upper_thr));
+ _kernel.setArg(idx++, static_cast<cl_uint>(width));
+ _kernel.setArg(idx++, static_cast<cl_uint>(height));
+
+ // 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));
+
+ AccessWindowHorizontal output_access(_output->info(), 0, num_elems_processed_per_iteration);
+ AccessWindowHorizontal visited_access(_visited->info(), 0, num_elems_processed_per_iteration);
+ AccessWindowHorizontal recorded_access(_recorded->info(), 0, num_elems_processed_per_iteration);
+ AccessWindowHorizontal l1_stack_access(_l1_stack->info(), 0, num_elems_processed_per_iteration);
+ AccessWindowHorizontal l1_stack_counter_access(_l1_stack_counter->info(), 0, num_elems_processed_per_iteration);
+
+ update_window_and_padding(win,
+ AccessWindowHorizontal(_input->info(), 0, num_elems_processed_per_iteration),
+ output_access,
+ visited_access,
+ recorded_access,
+ l1_stack_access,
+ l1_stack_counter_access);
+
+ output_access.set_valid_region(win, _input->info()->valid_region());
+ visited_access.set_valid_region(win, _input->info()->valid_region());
+ recorded_access.set_valid_region(win, _input->info()->valid_region());
+ l1_stack_access.set_valid_region(win, _input->info()->valid_region());
+ l1_stack_counter_access.set_valid_region(win, _input->info()->valid_region());
+
+ ICLKernel::configure(win);
+}
+
+void CLEdgeTraceKernel::run(const Window &window, cl::CommandQueue &queue)
+{
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::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);
+ add_2D_tensor_argument(idx, _visited, slice);
+ add_2D_tensor_argument(idx, _recorded, slice);
+ add_2D_tensor_argument(idx, _l1_stack, slice);
+ add_2D_tensor_argument(idx, _l1_stack_counter, slice);
+
+ enqueue(queue, *this, slice);
+ }
+ while(window.slide_window_slice_2D(slice));
+}
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