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-rw-r--r--src/core/CL/kernels/CLHOGDetectorKernel.cpp130
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diff --git a/src/core/CL/kernels/CLHOGDetectorKernel.cpp b/src/core/CL/kernels/CLHOGDetectorKernel.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/CLHOGDetectorKernel.h"
+
+#include "arm_compute/core/CL/CLHelpers.h"
+#include "arm_compute/core/CL/CLKernelLibrary.h"
+#include "arm_compute/core/CL/ICLHOG.h"
+#include "arm_compute/core/CL/ICLTensor.h"
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/Window.h"
+
+using namespace arm_compute;
+
+CLHOGDetectorKernel::CLHOGDetectorKernel()
+ : _input(nullptr), _detection_windows(), _num_detection_windows(nullptr)
+{
+}
+
+void CLHOGDetectorKernel::configure(const ICLTensor *input, const ICLHOG *hog, ICLDetectionWindowArray *detection_windows, cl::Buffer *num_detection_windows, const Size2D &detection_window_stride,
+ float threshold, uint16_t idx_class)
+{
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::F32);
+ ARM_COMPUTE_ERROR_ON(hog == nullptr);
+ ARM_COMPUTE_ERROR_ON(detection_windows == nullptr);
+ ARM_COMPUTE_ERROR_ON(num_detection_windows == nullptr);
+ ARM_COMPUTE_ERROR_ON((detection_window_stride.width % hog->info()->block_stride().width) != 0);
+ ARM_COMPUTE_ERROR_ON((detection_window_stride.height % hog->info()->block_stride().height) != 0);
+
+ const Size2D &detection_window_size = hog->info()->detection_window_size();
+ const Size2D &block_size = hog->info()->block_size();
+ const Size2D &block_stride = hog->info()->block_stride();
+
+ _input = input;
+ _detection_windows = detection_windows;
+ _num_detection_windows = num_detection_windows;
+
+ const unsigned int num_bins_per_descriptor_x = ((detection_window_size.width - block_size.width) / block_stride.width + 1) * input->info()->num_channels();
+ const unsigned int num_blocks_per_descriptor_y = (detection_window_size.height - block_size.height) / block_stride.height + 1;
+
+ ARM_COMPUTE_ERROR_ON((num_bins_per_descriptor_x * num_blocks_per_descriptor_y + 1) != hog->info()->descriptor_size());
+
+ std::stringstream args_str;
+ args_str << "-DNUM_BLOCKS_PER_DESCRIPTOR_Y=" << num_blocks_per_descriptor_y << " ";
+ args_str << "-DNUM_BINS_PER_DESCRIPTOR_X=" << num_bins_per_descriptor_x << " ";
+ args_str << "-DTHRESHOLD=" << threshold << " ";
+ args_str << "-DMAX_NUM_DETECTION_WINDOWS=" << detection_windows->max_num_values() << " ";
+ args_str << "-DIDX_CLASS=" << idx_class << " ";
+ args_str << "-DBLOCK_STRIDE_WIDTH=" << block_stride.width << " ";
+ args_str << "-DBLOCK_STRIDE_HEIGHT=" << block_stride.height << " ";
+ args_str << "-DDETECTION_WINDOW_WIDTH=" << detection_window_size.width << " ";
+ args_str << "-DDETECTION_WINDOW_HEIGHT=" << detection_window_size.height << " ";
+
+ // Construct kernel name
+ std::set<std::string> build_opts = {};
+ build_opts.insert(args_str.str());
+
+ // Create kernel
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("hog_detector", build_opts));
+
+ // Set static kernel arguments
+ unsigned int idx = num_arguments_per_2D_tensor(); // Skip the input parameters
+ _kernel.setArg(idx++, hog->cl_buffer());
+ _kernel.setArg(idx++, detection_windows->cl_buffer());
+ _kernel.setArg(idx++, *_num_detection_windows);
+
+ // Get the number of blocks along the x and y directions of the input tensor
+ const ValidRegion &valid_region = input->info()->valid_region();
+ const size_t num_blocks_x = valid_region.shape[0];
+ const size_t num_blocks_y = valid_region.shape[1];
+
+ // Get the number of blocks along the x and y directions of the detection window
+ const size_t num_blocks_per_detection_window_x = detection_window_size.width / block_stride.width;
+ const size_t num_blocks_per_detection_window_y = detection_window_size.height / block_stride.height;
+
+ const size_t window_step_x = detection_window_stride.width / block_stride.width;
+ const size_t window_step_y = detection_window_stride.height / block_stride.height;
+
+ // Configure kernel window
+ Window win;
+ win.set(Window::DimX, Window::Dimension(0, floor_to_multiple(num_blocks_x - num_blocks_per_detection_window_x, window_step_x), window_step_x));
+ win.set(Window::DimY, Window::Dimension(0, floor_to_multiple(num_blocks_y - num_blocks_per_detection_window_y, window_step_y), window_step_y));
+
+ constexpr unsigned int num_elems_read_per_iteration = 1;
+ const unsigned int num_rows_read_per_iteration = num_blocks_per_descriptor_y;
+
+ update_window_and_padding(win, AccessWindowRectangle(input->info(), 0, 0, num_elems_read_per_iteration, num_rows_read_per_iteration));
+
+ ICLKernel::configure(win);
+}
+
+void CLHOGDetectorKernel::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);
+
+ enqueue(queue, *this, slice);
+ }
+ while(window.slide_window_slice_2D(slice));
+}