Compute Library
 21.02
NEHarrisCorners.cpp
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25 
26 #include "arm_compute/core/Error.h"
40 
41 #include <cmath>
42 #include <utility>
43 
44 namespace arm_compute
45 {
47 
48 NEHarrisCorners::NEHarrisCorners(std::shared_ptr<IMemoryManager> memory_manager) // NOLINT
49  : _memory_group(std::move(memory_manager)),
50  _sobel(),
51  _harris_score(),
52  _non_max_suppr(),
53  _candidates(),
54  _sort_euclidean(),
55  _border_gx(),
56  _border_gy(),
57  _gx(),
58  _gy(),
59  _score(),
60  _nonmax(),
61  _corners_list(),
62  _num_corner_candidates(0)
63 {
64 }
65 
66 void NEHarrisCorners::configure(IImage *input, float threshold, float min_dist,
67  float sensitivity, int32_t gradient_size, int32_t block_size, KeyPointArray *corners,
68  BorderMode border_mode, uint8_t constant_border_value)
69 {
72  ARM_COMPUTE_ERROR_ON(!(block_size == 3 || block_size == 5 || block_size == 7));
73 
74  const TensorShape shape = input->info()->tensor_shape();
75  TensorInfo tensor_info_gxgy;
76 
77  if(gradient_size < 7)
78  {
79  tensor_info_gxgy.init(shape, Format::S16);
80  }
81  else
82  {
83  tensor_info_gxgy.init(shape, Format::S32);
84  }
85 
86  _gx.allocator()->init(tensor_info_gxgy);
87  _gy.allocator()->init(tensor_info_gxgy);
88 
89  // Manage intermediate buffers
90  _memory_group.manage(&_gx);
91  _memory_group.manage(&_gy);
92 
93  TensorInfo tensor_info_score(shape, Format::F32);
94  _score.allocator()->init(tensor_info_score);
95  _nonmax.allocator()->init(tensor_info_score);
96 
97  _corners_list.resize(shape.x() * shape.y());
98 
99  // Set/init Sobel kernel accordingly with gradient_size
100  switch(gradient_size)
101  {
102  case 3:
103  {
104  auto k = std::make_unique<NESobel3x3>();
105  k->configure(input, &_gx, &_gy, border_mode, constant_border_value);
106  _sobel = std::move(k);
107  break;
108  }
109  case 5:
110  {
111  auto k = std::make_unique<NESobel5x5>();
112  k->configure(input, &_gx, &_gy, border_mode, constant_border_value);
113  _sobel = std::move(k);
114  break;
115  }
116  case 7:
117  {
118  auto k = std::make_unique<NESobel7x7>();
119  k->configure(input, &_gx, &_gy, border_mode, constant_border_value);
120  _sobel = std::move(k);
121  break;
122  }
123  default:
124  ARM_COMPUTE_ERROR("Gradient size not implemented");
125  }
126 
127  // Normalization factor
128  const float norm_factor = 1.0f / (255.0f * pow(4.0f, gradient_size / 2) * block_size);
129 
130  // Manage intermediate buffers
131  _memory_group.manage(&_score);
132 
133  // Set/init Harris Score kernel accordingly with block_size
134  switch(block_size)
135  {
136  case 3:
137  {
138  auto k = std::make_unique<NEHarrisScoreKernel<3>>();
139  k->configure(&_gx, &_gy, &_score, norm_factor, threshold, sensitivity, border_mode == BorderMode::UNDEFINED);
140  _harris_score = std::move(k);
141  }
142  break;
143  case 5:
144  {
145  auto k = std::make_unique<NEHarrisScoreKernel<5>>();
146  k->configure(&_gx, &_gy, &_score, norm_factor, threshold, sensitivity, border_mode == BorderMode::UNDEFINED);
147  _harris_score = std::move(k);
148  }
149  break;
150  case 7:
151  {
152  auto k = std::make_unique<NEHarrisScoreKernel<7>>();
153  k->configure(&_gx, &_gy, &_score, norm_factor, threshold, sensitivity, border_mode == BorderMode::UNDEFINED);
154  _harris_score = std::move(k);
155  }
156  default:
157  break;
158  }
159 
160  // Configure border filling before harris score
161  _border_gx = std::make_unique<NEFillBorderKernel>();
162  _border_gy = std::make_unique<NEFillBorderKernel>();
163  _border_gx->configure(&_gx, _harris_score->border_size(), border_mode, constant_border_value);
164  _border_gy->configure(&_gy, _harris_score->border_size(), border_mode, constant_border_value);
165 
166  // Allocate once all the configure methods have been called
167  _gx.allocator()->allocate();
168  _gy.allocator()->allocate();
169 
170  // Manage intermediate buffers
171  _memory_group.manage(&_nonmax);
172 
173  // Init non-maxima suppression function
174  _non_max_suppr.configure(&_score, &_nonmax, border_mode);
175 
176  // Allocate once all the configure methods have been called
177  _score.allocator()->allocate();
178 
179  // Init corner candidates kernel
180  _candidates.configure(&_nonmax, _corners_list.data(), &_num_corner_candidates);
181 
182  // Allocate once all the configure methods have been called
183  _nonmax.allocator()->allocate();
184 
185  // Init euclidean distance
186  _sort_euclidean.configure(_corners_list.data(), corners, &_num_corner_candidates, min_dist);
187 }
188 
190 {
191  ARM_COMPUTE_ERROR_ON_MSG(_sobel == nullptr, "Unconfigured function");
192 
193  MemoryGroupResourceScope scope_mg(_memory_group);
194 
195  // Init to 0 number of corner candidates
196  _num_corner_candidates = 0;
197 
198  // Run Sobel kernel
199  _sobel->run();
200 
201  // Fill border before harris score kernel
202  NEScheduler::get().schedule(_border_gx.get(), Window::DimZ);
203  NEScheduler::get().schedule(_border_gy.get(), Window::DimZ);
204 
205  // Run harris score kernel
206  NEScheduler::get().schedule(_harris_score.get(), Window::DimY);
207 
208  // Run non-maxima suppression
209  _non_max_suppr.run();
210 
211  // Run corner candidate kernel
212  NEScheduler::get().schedule(&_candidates, Window::DimY);
213 
214  // Run sort & euclidean distance
215  NEScheduler::get().schedule(&_sort_euclidean, Window::DimY);
216 }
217 } // namespace arm_compute
BorderMode
Methods available to handle borders.
Definition: Types.h:265
Shape of a tensor.
Definition: TensorShape.h:39
void init(const TensorAllocator &allocator, const Coordinates &coords, TensorInfo &sub_info)
Shares the same backing memory with another tensor allocator, while the tensor info might be differen...
#define ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(t)
Definition: Validate.h:856
void run() override final
Run the kernels contained in the function.
NEHarrisCorners(std::shared_ptr< IMemoryManager > memory_manager=nullptr)
Constructor.
#define ARM_COMPUTE_ERROR(msg)
Print the given message then throw an std::runtime_error.
Definition: Error.h:352
1 channel, 1 U8 per channel
1 channel, 1 F32 per channel
#define ARM_COMPUTE_ERROR_ON(cond)
If the condition is true then an error message is printed and an exception thrown.
Definition: Error.h:466
Interface for Neon tensor.
Definition: ITensor.h:36
Copyright (c) 2017-2021 Arm Limited.
TensorAllocator * allocator()
Return a pointer to the tensor&#39;s allocator.
Definition: Tensor.cpp:48
Basic implementation of the IArray interface which allocates a static number of T values...
Definition: Array.h:36
1 channel, 1 S32 per channel
void manage(IMemoryManageable *obj) override
Sets a object to be managed by the given memory group.
Definition: MemoryGroup.h:79
T x() const
Alias to access the size of the first dimension.
Definition: Dimensions.h:87
~NEHarrisCorners()
Default destructor.
void run() override
Run the kernels contained in the function.
void configure(InternalKeypoint *in_out, IKeyPointArray *output, const int32_t *num_corner_candidates, float min_distance)
Initialise the kernel&#39;s source, destination and border mode.
virtual const TensorShape & tensor_shape() const =0
Size for each dimension of the tensor.
#define ARM_COMPUTE_ERROR_ON_MSG(cond, msg)
Definition: Error.h:456
void allocate() override
Allocate size specified by TensorInfo of CPU memory.
virtual ITensorInfo * info() const =0
Interface to be implemented by the child class to return the tensor&#39;s metadata.
1 channel, 1 S16 per channel
void configure(ITensor *input, ITensor *output, BorderMode border_mode)
Initialise the function&#39;s source, destinations and border mode.
#define ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)
Definition: Validate.h:790
void init(Format format)
Initialize the tensor info with just a format.
Definition: TensorInfo.cpp:109
static constexpr size_t DimY
Alias for dimension 1 also known as Y dimension.
Definition: Window.h:45
Memory group resources scope handling class.
Definition: IMemoryGroup.h:82
virtual void schedule(ICPPKernel *kernel, const Hints &hints)=0
Runs the kernel in the same thread as the caller synchronously.
static constexpr size_t DimZ
Alias for dimension 2 also known as Z dimension.
Definition: Window.h:47
Borders are left undefined.
void configure(IImage *input, float threshold, float min_dist, float sensitivity, int32_t gradient_size, int32_t block_size, KeyPointArray *corners, BorderMode border_mode, uint8_t constant_border_value=0)
Initialize the function&#39;s source, destination, conv and border_mode.
Store the tensor&#39;s metadata.
Definition: TensorInfo.h:45
T y() const
Alias to access the size of the second dimension.
Definition: Dimensions.h:92
SimpleTensor< T > threshold(const SimpleTensor< T > &src, T threshold, T false_value, T true_value, ThresholdType type, T upper)
Definition: Threshold.cpp:35
void configure(const IImage *input, InternalKeypoint *output, int32_t *num_corner_candidates)
Setup the kernel parameters.
static IScheduler & get()
Access the scheduler singleton.
Definition: Scheduler.cpp:94