Compute Library
 21.02
NEHOGMultiDetection.h
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24 #ifndef ARM_COMPUTE_NEHOGMULTIDETECTION_H
25 #define ARM_COMPUTE_NEHOGMULTIDETECTION_H
26 
36 
37 #include <memory>
38 
39 namespace arm_compute
40 {
41 class NEHOGOrientationBinningKernel;
42 class NEHOGBlockNormalizationKernel;
43 
44 /** 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 Neon kernels:
45  *
46  * -# @ref NEHOGGradient
47  * -# @ref NEHOGOrientationBinningKernel
48  * -# @ref NEHOGBlockNormalizationKernel
49  * -# @ref NEHOGDetector
50  * -# @ref CPPDetectionWindowNonMaximaSuppressionKernel (executed if non_maxima_suppression == true)
51  *
52  * @note This implementation works if all the HOG data-objects within the IMultiHOG container have the same:
53  * -# Phase type
54  -# Normalization type
55  -# L2 hysteresis threshold if the normalization type is L2HYS_NORM
56  *
57  * @deprecated This function is deprecated and is intended to be removed in 21.05 release
58  *
59  */
61 {
62 public:
63  /** Default constructor */
64  NEHOGMultiDetection(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
65  /** Prevent instances of this class from being copied (As this class contains pointers) */
66  NEHOGMultiDetection(const NEHOGMultiDetection &) = delete;
67  /** Prevent instances of this class from being moved (As this class contains pointers) */
69  /** Prevent instances of this class from being copied (As this class contains pointers) */
71  /** Prevent instances of this class from being moved (As this class contains pointers) */
73  /** Default destructor */
75  /** Initialise the function's source, destination, detection window strides, border mode, threshold and non-maxima suppression
76  *
77  * @param[in, out] input Input tensor. Data type supported: U8
78  * (Written to only for @p border_mode != UNDEFINED)
79  * @param[in] multi_hog Container of multiple HOG data object. Each HOG data object describes one HOG model to detect.
80  * This container should store the HOG data-objects in descending or ascending cell_size width order.
81  * This will help to understand if the HOG descriptor computation can be skipped for some HOG data-objects
82  * @param[out] detection_windows Array of @ref DetectionWindow used for locating the detected objects
83  * @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
84  * The dimension of this array must be the same of multi_hog->num_models()
85  * The i-th detection_window_stride of this array must be multiple of the block_stride stored in the i-th multi_hog array
86  * @param[in] border_mode Border mode to use.
87  * @param[in] constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT.
88  * @param[in] threshold (Optional) Threshold for the distance between features and SVM classifying plane
89  * @param[in] non_maxima_suppression (Optional) Flag to specify whether the non-maxima suppression is required or not.
90  * True if the non-maxima suppression stage has to be computed
91  * @param[in] min_distance (Optional) Radial Euclidean distance to use for the non-maxima suppression stage
92  *
93  */
94  void configure(ITensor *input, const IMultiHOG *multi_hog, IDetectionWindowArray *detection_windows, const ISize2DArray *detection_window_strides, BorderMode border_mode,
95  uint8_t constant_border_value = 0,
96  float threshold = 0.0f, bool non_maxima_suppression = false, float min_distance = 1.0f);
97 
98  // Inherited method overridden:
99  void run() override;
100 
101 private:
102  MemoryGroup _memory_group;
103  NEHOGGradient _gradient_kernel;
104  std::vector<NEHOGOrientationBinningKernel> _orient_bin_kernel;
105  std::vector<NEHOGBlockNormalizationKernel> _block_norm_kernel;
106  std::vector<NEHOGDetector> _hog_detect_kernel;
108  std::vector<Tensor> _hog_space;
109  std::vector<Tensor> _hog_norm_space;
110  IDetectionWindowArray *_detection_windows;
111  Tensor _mag;
112  Tensor _phase;
113  bool _non_maxima_suppression;
114  size_t _num_orient_bin_kernel;
115  size_t _num_block_norm_kernel;
116  size_t _num_hog_detect_kernel;
117 };
118 } // namespace arm_compute
119 #endif /* ARM_COMPUTE_NEHOGMULTIDETECTION_H */
BorderMode
Methods available to handle borders.
Definition: Types.h:265
Base class for all functions.
Definition: IFunction.h:30
~NEHOGMultiDetection()
Default destructor.
Array of type T.
Definition: IArray.h:40
Interface for Neon tensor.
Definition: ITensor.h:36
Copyright (c) 2017-2021 Arm Limited.
Basic function to detect multiple objects (or the same object at different scales) on the same input ...
Basic function to calculate the gradient for HOG.
Definition: NEHOGGradient.h:50
Basic implementation of the tensor interface.
Definition: Tensor.h:37
void run() override
Run the kernels contained in the function.
NEHOGMultiDetection & operator=(const NEHOGMultiDetection &)=delete
Prevent instances of this class from being copied (As this class contains pointers) ...
CPP kernel to perform in-place computation of euclidean distance on IDetectionWindowArray.
void configure(ITensor *input, const IMultiHOG *multi_hog, IDetectionWindowArray *detection_windows, const ISize2DArray *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&#39;s source, destination, detection window strides, border mode, threshold and non-maxima suppression.
Interface for storing multiple HOG data-objects.
Definition: IMultiHOG.h:34
SimpleTensor< T > non_maxima_suppression(const SimpleTensor< T > &src, BorderMode border_mode, T constant_border_value)
NEHOGMultiDetection(std::shared_ptr< IMemoryManager > memory_manager=nullptr)
Default constructor.
SimpleTensor< T > threshold(const SimpleTensor< T > &src, T threshold, T false_value, T true_value, ThresholdType type, T upper)
Definition: Threshold.cpp:35