139 lines
9.2 KiB
C++
139 lines
9.2 KiB
C++
/*
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* Copyright (c) 2017-2020 Arm Limited.
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*
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* SPDX-License-Identifier: MIT
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to
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* deal in the Software without restriction, including without limitation the
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* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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* sell copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*/
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#ifndef ARM_COMPUTE_CLHOGMULTIDETECTION_H
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#define ARM_COMPUTE_CLHOGMULTIDETECTION_H
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#include "arm_compute/core/CL/ICLArray.h"
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#include "arm_compute/core/CL/ICLMultiHOG.h"
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#include "arm_compute/core/CPP/kernels/CPPDetectionWindowNonMaximaSuppressionKernel.h"
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#include "arm_compute/runtime/CL/CLTensor.h"
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#include "arm_compute/runtime/CL/functions/CLHOGDetector.h"
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#include "arm_compute/runtime/CL/functions/CLHOGGradient.h"
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#include "arm_compute/runtime/IFunction.h"
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#include "arm_compute/runtime/IMemoryManager.h"
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#include "arm_compute/runtime/MemoryGroup.h"
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#include <memory>
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namespace arm_compute
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{
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class CLCompileContext;
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class CLHOGOrientationBinningKernel;
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class CLHOGBlockNormalizationKernel;
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/** 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:
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*
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* -# @ref CLHOGGradient
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* -# @ref CLHOGOrientationBinningKernel
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* -# @ref CLHOGBlockNormalizationKernel
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* -# @ref CLHOGDetector
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* -# @ref CPPDetectionWindowNonMaximaSuppressionKernel (executed if non_maxima_suppression == true)
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*
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* @note This implementation works if all the HOG data-objects within the IMultiHOG container have the same:
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* -# Phase type
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-# Normalization type
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-# L2 hysteresis threshold if the normalization type is L2HYS_NORM
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*
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*
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* @deprecated This function is deprecated and is intended to be removed in 21.05 release
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*
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*/
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class CLHOGMultiDetection : public IFunction
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{
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public:
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/** Default constructor */
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CLHOGMultiDetection(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
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/** Prevent instances of this class from being copied (As this class contains pointers) */
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CLHOGMultiDetection(const CLHOGMultiDetection &) = delete;
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/** Prevent instances of this class from being copied (As this class contains pointers) */
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CLHOGMultiDetection &operator=(const CLHOGMultiDetection &) = delete;
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/** Default destructor */
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~CLHOGMultiDetection();
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/** Initialise the function's source, destination, detection window strides, border mode, threshold and non-maxima suppression
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*
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* @param[in, out] input Input tensor. Data type supported: U8
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* (Written to only for @p border_mode != UNDEFINED)
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* @param[in] multi_hog Container of multiple HOG data object. Each HOG data object describes one HOG model to detect.
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* This container should store the HOG data-objects in descending or ascending cell_size width order.
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* This will help to understand if the HOG descriptor computation can be skipped for some HOG data-objects
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* @param[out] detection_windows Array of @ref DetectionWindow used for locating the detected objects
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* @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
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* The dimension of this array must be the same of multi_hog->num_models()
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* The i-th detection_window_stride of this array must be multiple of the block_stride stored in the i-th multi_hog array
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* @param[in] border_mode Border mode to use.
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* @param[in] constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT.
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* @param[in] threshold (Optional) Threshold for the distance between features and SVM classifying plane
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* @param[in] non_maxima_suppression (Optional) Flag to specify whether the non-maxima suppression is required or not.
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* True if the non-maxima suppression stage has to be computed
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* @param[in] min_distance (Optional) Radial Euclidean distance to use for the non-maxima suppression stage
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*
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*/
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void configure(ICLTensor *input, const ICLMultiHOG *multi_hog, ICLDetectionWindowArray *detection_windows, ICLSize2DArray *detection_window_strides, BorderMode border_mode,
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uint8_t constant_border_value = 0, float threshold = 0.0f, bool non_maxima_suppression = false, float min_distance = 1.0f);
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/** Initialise the function's source, destination, detection window strides, border mode, threshold and non-maxima suppression
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*
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* @param[in] compile_context The compile context to be used.
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* @param[in, out] input Input tensor. Data type supported: U8
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* (Written to only for @p border_mode != UNDEFINED)
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* @param[in] multi_hog Container of multiple HOG data object. Each HOG data object describes one HOG model to detect.
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* This container should store the HOG data-objects in descending or ascending cell_size width order.
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* This will help to understand if the HOG descriptor computation can be skipped for some HOG data-objects
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* @param[out] detection_windows Array of @ref DetectionWindow used for locating the detected objects
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* @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
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* The dimension of this array must be the same of multi_hog->num_models()
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* The i-th detection_window_stride of this array must be multiple of the block_stride stored in the i-th multi_hog array
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* @param[in] border_mode Border mode to use.
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* @param[in] constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT.
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* @param[in] threshold (Optional) Threshold for the distance between features and SVM classifying plane
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* @param[in] non_maxima_suppression (Optional) Flag to specify whether the non-maxima suppression is required or not.
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* True if the non-maxima suppression stage has to be computed
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* @param[in] min_distance (Optional) Radial Euclidean distance to use for the non-maxima suppression stage
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*
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*/
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void configure(const CLCompileContext &compile_context, ICLTensor *input, const ICLMultiHOG *multi_hog, ICLDetectionWindowArray *detection_windows, ICLSize2DArray *detection_window_strides,
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BorderMode border_mode, uint8_t constant_border_value = 0, float threshold = 0.0f, bool non_maxima_suppression = false, float min_distance = 1.0f);
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// Inherited method overridden:
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void run() override;
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private:
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MemoryGroup _memory_group;
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CLHOGGradient _gradient_kernel;
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std::vector<std::unique_ptr<CLHOGOrientationBinningKernel>> _orient_bin_kernel;
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std::vector<std::unique_ptr<CLHOGBlockNormalizationKernel>> _block_norm_kernel;
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std::vector<CLHOGDetector> _hog_detect_kernel;
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CPPDetectionWindowNonMaximaSuppressionKernel _non_maxima_kernel;
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std::vector<CLTensor> _hog_space;
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std::vector<CLTensor> _hog_norm_space;
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ICLDetectionWindowArray *_detection_windows;
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CLTensor _mag;
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CLTensor _phase;
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bool _non_maxima_suppression;
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size_t _num_orient_bin_kernel;
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size_t _num_block_norm_kernel;
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size_t _num_hog_detect_kernel;
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};
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}
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#endif /* ARM_COMPUTE_CLHOGMULTIDETECTION_H */
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