1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
|
/*
* Copyright (c) 2017-2020 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/CPP/kernels/CPPDetectionWindowNonMaximaSuppressionKernel.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 "arm_compute/runtime/MemoryGroup.h"
#include <memory>
namespace arm_compute
{
class CLCompileContext;
class CLHOGOrientationBinningKernel;
class CLHOGBlockNormalizationKernel;
/** 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;
/** Default destructor */
~CLHOGMultiDetection();
/** 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);
/** Initialise the function's source, destination, detection window strides, border mode, threshold and non-maxima suppression
*
* @param[in] compile_context The compile context to be used.
* @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(const CLCompileContext &compile_context, 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:
MemoryGroup _memory_group;
CLHOGGradient _gradient_kernel;
std::vector<std::unique_ptr<CLHOGOrientationBinningKernel>> _orient_bin_kernel;
std::vector<std::unique_ptr<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 */
|
