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/*
* 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 <memory>
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<IMemoryManager> 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<CLHOGOrientationBinningKernel> _orient_bin_kernel;
std::vector<CLHOGBlockNormalizationKernel> _block_norm_kernel;
std::vector<CLHOGDetector> _hog_detect_kernel;
CPPDetectionWindowNonMaximaSuppressionKernel _non_maxima_kernel;
std::vector<CLTensor> _hog_space;
std::vector<CLTensor> _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__ */
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