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1 /*
2  * Copyright (c) 2016-2020 Arm Limited.
3  *
4  * SPDX-License-Identifier: MIT
5  *
6  * Permission is hereby granted, free of charge, to any person obtaining a copy
7  * of this software and associated documentation files (the "Software"), to
8  * deal in the Software without restriction, including without limitation the
9  * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
10  * sell copies of the Software, and to permit persons to whom the Software is
11  * furnished to do so, subject to the following conditions:
12  *
13  * The above copyright notice and this permission notice shall be included in all
14  * copies or substantial portions of the Software.
15  *
16  * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
17  * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
18  * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
19  * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
20  * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
21  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
22  * SOFTWARE.
23  */
24 #include "arm_compute/runtime/NEON/functions/NEHarrisCorners.h"
25 
26 #include "arm_compute/core/Error.h"
27 #include "arm_compute/core/TensorInfo.h"
28 #include "arm_compute/core/Validate.h"
29 #include "arm_compute/runtime/Array.h"
30 #include "arm_compute/runtime/NEON/NEScheduler.h"
31 #include "arm_compute/runtime/NEON/functions/NESobel3x3.h"
32 #include "arm_compute/runtime/NEON/functions/NESobel5x5.h"
33 #include "arm_compute/runtime/NEON/functions/NESobel7x7.h"
34 #include "arm_compute/runtime/TensorAllocator.h"
35 #include "src/core/NEON/kernels/NEFillBorderKernel.h"
36 #include "src/core/NEON/kernels/NEFillBorderKernel.h"
37 #include "src/core/NEON/kernels/NEHarrisCornersKernel.h"
38 #include "src/core/NEON/kernels/NESobel5x5Kernel.h"
39 #include "src/core/NEON/kernels/NESobel7x7Kernel.h"
40 #include "support/MemorySupport.h"
41 
42 #include <cmath>
43 #include <utility>
44 
45 namespace arm_compute
46 {
47 NEHarrisCorners::~NEHarrisCorners() = default;
48 
NEHarrisCorners(std::shared_ptr<IMemoryManager> memory_manager)49 NEHarrisCorners::NEHarrisCorners(std::shared_ptr<IMemoryManager> memory_manager) // NOLINT
50     : _memory_group(std::move(memory_manager)),
51       _sobel(),
52       _harris_score(),
53       _non_max_suppr(),
54       _candidates(),
55       _sort_euclidean(),
56       _border_gx(),
57       _border_gy(),
58       _gx(),
59       _gy(),
60       _score(),
61       _nonmax(),
62       _corners_list(),
63       _num_corner_candidates(0)
64 {
65 }
66 
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)67 void NEHarrisCorners::configure(IImage *input, float threshold, float min_dist,
68                                 float sensitivity, int32_t gradient_size, int32_t block_size, KeyPointArray *corners,
69                                 BorderMode border_mode, uint8_t constant_border_value)
70 {
71     ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(input);
72     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
73     ARM_COMPUTE_ERROR_ON(!(block_size == 3 || block_size == 5 || block_size == 7));
74 
75     const TensorShape shape = input->info()->tensor_shape();
76     TensorInfo        tensor_info_gxgy;
77 
78     if(gradient_size < 7)
79     {
80         tensor_info_gxgy.init(shape, Format::S16);
81     }
82     else
83     {
84         tensor_info_gxgy.init(shape, Format::S32);
85     }
86 
87     _gx.allocator()->init(tensor_info_gxgy);
88     _gy.allocator()->init(tensor_info_gxgy);
89 
90     // Manage intermediate buffers
91     _memory_group.manage(&_gx);
92     _memory_group.manage(&_gy);
93 
94     TensorInfo tensor_info_score(shape, Format::F32);
95     _score.allocator()->init(tensor_info_score);
96     _nonmax.allocator()->init(tensor_info_score);
97 
98     _corners_list.resize(shape.x() * shape.y());
99 
100     // Set/init Sobel kernel accordingly with gradient_size
101     switch(gradient_size)
102     {
103         case 3:
104         {
105             auto k = arm_compute::support::cpp14::make_unique<NESobel3x3>();
106             k->configure(input, &_gx, &_gy, border_mode, constant_border_value);
107             _sobel = std::move(k);
108             break;
109         }
110         case 5:
111         {
112             auto k = arm_compute::support::cpp14::make_unique<NESobel5x5>();
113             k->configure(input, &_gx, &_gy, border_mode, constant_border_value);
114             _sobel = std::move(k);
115             break;
116         }
117         case 7:
118         {
119             auto k = arm_compute::support::cpp14::make_unique<NESobel7x7>();
120             k->configure(input, &_gx, &_gy, border_mode, constant_border_value);
121             _sobel = std::move(k);
122             break;
123         }
124         default:
125             ARM_COMPUTE_ERROR("Gradient size not implemented");
126     }
127 
128     // Normalization factor
129     const float norm_factor = 1.0f / (255.0f * pow(4.0f, gradient_size / 2) * block_size);
130 
131     // Manage intermediate buffers
132     _memory_group.manage(&_score);
133 
134     // Set/init Harris Score kernel accordingly with block_size
135     switch(block_size)
136     {
137         case 3:
138         {
139             auto k = arm_compute::support::cpp14::make_unique<NEHarrisScoreKernel<3>>();
140             k->configure(&_gx, &_gy, &_score, norm_factor, threshold, sensitivity, border_mode == BorderMode::UNDEFINED);
141             _harris_score = std::move(k);
142         }
143         break;
144         case 5:
145         {
146             auto k = arm_compute::support::cpp14::make_unique<NEHarrisScoreKernel<5>>();
147             k->configure(&_gx, &_gy, &_score, norm_factor, threshold, sensitivity, border_mode == BorderMode::UNDEFINED);
148             _harris_score = std::move(k);
149         }
150         break;
151         case 7:
152         {
153             auto k = arm_compute::support::cpp14::make_unique<NEHarrisScoreKernel<7>>();
154             k->configure(&_gx, &_gy, &_score, norm_factor, threshold, sensitivity, border_mode == BorderMode::UNDEFINED);
155             _harris_score = std::move(k);
156         }
157         default:
158             break;
159     }
160 
161     // Configure border filling before harris score
162     _border_gx = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>();
163     _border_gy = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>();
164     _border_gx->configure(&_gx, _harris_score->border_size(), border_mode, constant_border_value);
165     _border_gy->configure(&_gy, _harris_score->border_size(), border_mode, constant_border_value);
166 
167     // Allocate once all the configure methods have been called
168     _gx.allocator()->allocate();
169     _gy.allocator()->allocate();
170 
171     // Manage intermediate buffers
172     _memory_group.manage(&_nonmax);
173 
174     // Init non-maxima suppression function
175     _non_max_suppr.configure(&_score, &_nonmax, border_mode);
176 
177     // Allocate once all the configure methods have been called
178     _score.allocator()->allocate();
179 
180     // Init corner candidates kernel
181     _candidates.configure(&_nonmax, _corners_list.data(), &_num_corner_candidates);
182 
183     // Allocate once all the configure methods have been called
184     _nonmax.allocator()->allocate();
185 
186     // Init euclidean distance
187     _sort_euclidean.configure(_corners_list.data(), corners, &_num_corner_candidates, min_dist);
188 }
189 
run()190 void NEHarrisCorners::run()
191 {
192     ARM_COMPUTE_ERROR_ON_MSG(_sobel == nullptr, "Unconfigured function");
193 
194     MemoryGroupResourceScope scope_mg(_memory_group);
195 
196     // Init to 0 number of corner candidates
197     _num_corner_candidates = 0;
198 
199     // Run Sobel kernel
200     _sobel->run();
201 
202     // Fill border before harris score kernel
203     NEScheduler::get().schedule(_border_gx.get(), Window::DimZ);
204     NEScheduler::get().schedule(_border_gy.get(), Window::DimZ);
205 
206     // Run harris score kernel
207     NEScheduler::get().schedule(_harris_score.get(), Window::DimY);
208 
209     // Run non-maxima suppression
210     _non_max_suppr.run();
211 
212     // Run corner candidate kernel
213     NEScheduler::get().schedule(&_candidates, Window::DimY);
214 
215     // Run sort & euclidean distance
216     NEScheduler::get().schedule(&_sort_euclidean, Window::DimY);
217 }
218 } // namespace arm_compute
219