/* * Copyright (c) 2017-2019 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. */ #ifndef __ARM_COMPUTE_CLHOGMULTIDETECTION_H__ #define __ARM_COMPUTE_CLHOGMULTIDETECTION_H__ #include "arm_compute/core/CL/ICLArray.h" #include "arm_compute/core/CL/ICLMultiHOG.h" #include "arm_compute/core/CL/kernels/CLHOGDescriptorKernel.h" #include "arm_compute/core/CPP/kernels/CPPDetectionWindowNonMaximaSuppressionKernel.h" #include "arm_compute/runtime/CL/CLMemoryGroup.h" #include "arm_compute/runtime/CL/CLTensor.h" #include "arm_compute/runtime/CL/functions/CLHOGDetector.h" #include "arm_compute/runtime/CL/functions/CLHOGGradient.h" #include "arm_compute/runtime/IFunction.h" #include "arm_compute/runtime/IMemoryManager.h" #include namespace arm_compute { /** Basic function to detect multiple objects (or the same object at different scales) on the same input image using HOG. This function calls the following kernels: * * -# @ref CLHOGGradient * -# @ref CLHOGOrientationBinningKernel * -# @ref CLHOGBlockNormalizationKernel * -# @ref CLHOGDetector * -# @ref CPPDetectionWindowNonMaximaSuppressionKernel (executed if non_maxima_suppression == true) * * @note This implementation works if all the HOG data-objects within the IMultiHOG container have the same: * -# Phase type -# Normalization type -# L2 hysteresis threshold if the normalization type is L2HYS_NORM * */ class CLHOGMultiDetection : public IFunction { public: /** Default constructor */ CLHOGMultiDetection(std::shared_ptr memory_manager = nullptr); /** Prevent instances of this class from being copied (As this class contains pointers) */ CLHOGMultiDetection(const CLHOGMultiDetection &) = delete; /** Prevent instances of this class from being copied (As this class contains pointers) */ CLHOGMultiDetection &operator=(const CLHOGMultiDetection &) = delete; /** Initialise the function's source, destination, detection window strides, border mode, threshold and non-maxima suppression * * @param[in, out] input Input tensor. Data type supported: U8 * (Written to only for @p border_mode != UNDEFINED) * @param[in] multi_hog Container of multiple HOG data object. Each HOG data object describes one HOG model to detect. * This container should store the HOG data-objects in descending or ascending cell_size width order. * This will help to understand if the HOG descriptor computation can be skipped for some HOG data-objects * @param[out] detection_windows Array of @ref DetectionWindow used for locating the detected objects * @param[in] detection_window_strides Array of @ref Size2D used to specify the distance in pixels between 2 consecutive detection windows in x and y directions for each HOG data-object * The dimension of this array must be the same of multi_hog->num_models() * The i-th detection_window_stride of this array must be multiple of the block_stride stored in the i-th multi_hog array * @param[in] border_mode Border mode to use. * @param[in] constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT. * @param[in] threshold (Optional) Threshold for the distance between features and SVM classifying plane * @param[in] non_maxima_suppression (Optional) Flag to specify whether the non-maxima suppression is required or not. * True if the non-maxima suppression stage has to be computed * @param[in] min_distance (Optional) Radial Euclidean distance to use for the non-maxima suppression stage * */ void configure(ICLTensor *input, const ICLMultiHOG *multi_hog, ICLDetectionWindowArray *detection_windows, ICLSize2DArray *detection_window_strides, BorderMode border_mode, uint8_t constant_border_value = 0, float threshold = 0.0f, bool non_maxima_suppression = false, float min_distance = 1.0f); // Inherited method overridden: void run() override; private: CLMemoryGroup _memory_group; CLHOGGradient _gradient_kernel; std::vector _orient_bin_kernel; std::vector _block_norm_kernel; std::vector _hog_detect_kernel; CPPDetectionWindowNonMaximaSuppressionKernel _non_maxima_kernel; std::vector _hog_space; std::vector _hog_norm_space; ICLDetectionWindowArray *_detection_windows; CLTensor _mag; CLTensor _phase; bool _non_maxima_suppression; size_t _num_orient_bin_kernel; size_t _num_block_norm_kernel; size_t _num_hog_detect_kernel; }; } #endif /* __ARM_COMPUTE_CLHOGMULTIDETECTION_H__ */