/* * Copyright (c) 2016-2018 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_NEHOGDETECTORKERNEL_H__ #define __ARM_COMPUTE_NEHOGDETECTORKERNEL_H__ #include "arm_compute/core/IArray.h" #include "arm_compute/core/IHOG.h" #include "arm_compute/core/NEON/INEKernel.h" #include "support/Mutex.h" namespace arm_compute { class ITensor; /** NEON kernel to perform HOG detector kernel using linear SVM */ class NEHOGDetectorKernel : public INEKernel { public: const char *name() const override { return "NEHOGDetectorKernel"; } /** Default constructor */ NEHOGDetectorKernel(); /** Prevent instances of this class from being copied (As this class contains pointers) */ NEHOGDetectorKernel(const NEHOGDetectorKernel &) = delete; /** Prevent instances of this class from being copied (As this class contains pointers) */ NEHOGDetectorKernel &operator=(const NEHOGDetectorKernel &) = delete; /** Allow instances of this class to be moved */ NEHOGDetectorKernel(NEHOGDetectorKernel &&) = default; /** Allow instances of this class to be moved */ NEHOGDetectorKernel &operator=(NEHOGDetectorKernel &&) = default; /** Default destructor */ ~NEHOGDetectorKernel() = default; /** Initialise the kernel's input, HOG data-object, detection window, the stride of the detection window, the threshold and index of the object to detect * * @param[in] input Input tensor which stores the HOG descriptor obtained with @ref NEHOGOrientationBinningKernel. Data type supported: F32. Number of channels supported: equal to the number of histogram bins per block * @param[in] hog HOG data object used by @ref NEHOGOrientationBinningKernel and @ref NEHOGBlockNormalizationKernel * @param[out] detection_windows Array of @ref DetectionWindow. This array stores all the detected objects * @param[in] detection_window_stride Distance in pixels between 2 consecutive detection windows in x and y directions. * It must be multiple of the hog->info()->block_stride() * @param[in] threshold (Optional) Threshold for the distance between features and SVM classifying plane * @param[in] idx_class (Optional) Index of the class used for evaluating which class the detection window belongs to */ void configure(const ITensor *input, const IHOG *hog, IDetectionWindowArray *detection_windows, const Size2D &detection_window_stride, float threshold = 0.0f, uint16_t idx_class = 0); // Inherited methods overridden: void run(const Window &window, const ThreadInfo &info) override; private: const ITensor *_input; IDetectionWindowArray *_detection_windows; const float *_hog_descriptor; float _bias; float _threshold; uint16_t _idx_class; size_t _num_bins_per_descriptor_x; size_t _num_blocks_per_descriptor_y; size_t _block_stride_width; size_t _block_stride_height; size_t _detection_window_width; size_t _detection_window_height; size_t _max_num_detection_windows; arm_compute::Mutex _mutex; }; } // namespace arm_compute #endif /* __ARM_COMPUTE_NEHOGDETECTORKERNEL_H__ */