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11 // For Open Source Computer Vision Library
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41 //M*/
42
43 #include "precomp.hpp"
44
45 using namespace cv;
46 using namespace cv::cuda;
47
48 #if !defined (HAVE_CUDA) || defined (CUDA_DISABLER) || !defined(HAVE_OPENCV_CUDAFILTERS)
49
createHoughCirclesDetector(float,float,int,int,int,int,int)50 Ptr<cuda::HoughCirclesDetector> cv::cuda::createHoughCirclesDetector(float, float, int, int, int, int, int) { throw_no_cuda(); return Ptr<HoughCirclesDetector>(); }
51
52 #else /* !defined (HAVE_CUDA) */
53
54 namespace cv { namespace cuda { namespace device
55 {
56 namespace hough
57 {
58 int buildPointList_gpu(PtrStepSzb src, unsigned int* list);
59 }
60
61 namespace hough_circles
62 {
63 void circlesAccumCenters_gpu(const unsigned int* list, int count, PtrStepi dx, PtrStepi dy, PtrStepSzi accum, int minRadius, int maxRadius, float idp);
64 int buildCentersList_gpu(PtrStepSzi accum, unsigned int* centers, int threshold);
65 int circlesAccumRadius_gpu(const unsigned int* centers, int centersCount, const unsigned int* list, int count,
66 float3* circles, int maxCircles, float dp, int minRadius, int maxRadius, int threshold, bool has20);
67 }
68 }}}
69
70 namespace
71 {
72 class HoughCirclesDetectorImpl : public HoughCirclesDetector
73 {
74 public:
75 HoughCirclesDetectorImpl(float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles);
76
77 void detect(InputArray src, OutputArray circles, Stream& stream);
78
setDp(float dp)79 void setDp(float dp) { dp_ = dp; }
getDp() const80 float getDp() const { return dp_; }
81
setMinDist(float minDist)82 void setMinDist(float minDist) { minDist_ = minDist; }
getMinDist() const83 float getMinDist() const { return minDist_; }
84
setCannyThreshold(int cannyThreshold)85 void setCannyThreshold(int cannyThreshold) { cannyThreshold_ = cannyThreshold; }
getCannyThreshold() const86 int getCannyThreshold() const { return cannyThreshold_; }
87
setVotesThreshold(int votesThreshold)88 void setVotesThreshold(int votesThreshold) { votesThreshold_ = votesThreshold; }
getVotesThreshold() const89 int getVotesThreshold() const { return votesThreshold_; }
90
setMinRadius(int minRadius)91 void setMinRadius(int minRadius) { minRadius_ = minRadius; }
getMinRadius() const92 int getMinRadius() const { return minRadius_; }
93
setMaxRadius(int maxRadius)94 void setMaxRadius(int maxRadius) { maxRadius_ = maxRadius; }
getMaxRadius() const95 int getMaxRadius() const { return maxRadius_; }
96
setMaxCircles(int maxCircles)97 void setMaxCircles(int maxCircles) { maxCircles_ = maxCircles; }
getMaxCircles() const98 int getMaxCircles() const { return maxCircles_; }
99
write(FileStorage & fs) const100 void write(FileStorage& fs) const
101 {
102 fs << "name" << "HoughCirclesDetector_CUDA"
103 << "dp" << dp_
104 << "minDist" << minDist_
105 << "cannyThreshold" << cannyThreshold_
106 << "votesThreshold" << votesThreshold_
107 << "minRadius" << minRadius_
108 << "maxRadius" << maxRadius_
109 << "maxCircles" << maxCircles_;
110 }
111
read(const FileNode & fn)112 void read(const FileNode& fn)
113 {
114 CV_Assert( String(fn["name"]) == "HoughCirclesDetector_CUDA" );
115 dp_ = (float)fn["dp"];
116 minDist_ = (float)fn["minDist"];
117 cannyThreshold_ = (int)fn["cannyThreshold"];
118 votesThreshold_ = (int)fn["votesThreshold"];
119 minRadius_ = (int)fn["minRadius"];
120 maxRadius_ = (int)fn["maxRadius"];
121 maxCircles_ = (int)fn["maxCircles"];
122 }
123
124 private:
125 float dp_;
126 float minDist_;
127 int cannyThreshold_;
128 int votesThreshold_;
129 int minRadius_;
130 int maxRadius_;
131 int maxCircles_;
132
133 GpuMat dx_, dy_;
134 GpuMat edges_;
135 GpuMat accum_;
136 Mat tt; //CPU copy of accum_
137 GpuMat list_;
138 GpuMat result_;
139 Ptr<cuda::Filter> filterDx_;
140 Ptr<cuda::Filter> filterDy_;
141 Ptr<cuda::CannyEdgeDetector> canny_;
142 };
143
centersCompare(Vec3f a,Vec3f b)144 bool centersCompare(Vec3f a, Vec3f b) {return (a[2] > b[2]);}
145
HoughCirclesDetectorImpl(float dp,float minDist,int cannyThreshold,int votesThreshold,int minRadius,int maxRadius,int maxCircles)146 HoughCirclesDetectorImpl::HoughCirclesDetectorImpl(float dp, float minDist, int cannyThreshold, int votesThreshold,
147 int minRadius, int maxRadius, int maxCircles) :
148 dp_(dp), minDist_(minDist), cannyThreshold_(cannyThreshold), votesThreshold_(votesThreshold),
149 minRadius_(minRadius), maxRadius_(maxRadius), maxCircles_(maxCircles)
150 {
151 canny_ = cuda::createCannyEdgeDetector(std::max(cannyThreshold_ / 2, 1), cannyThreshold_);
152
153 filterDx_ = cuda::createSobelFilter(CV_8UC1, CV_32S, 1, 0);
154 filterDy_ = cuda::createSobelFilter(CV_8UC1, CV_32S, 0, 1);
155 }
156
detect(InputArray _src,OutputArray circles,Stream & stream)157 void HoughCirclesDetectorImpl::detect(InputArray _src, OutputArray circles, Stream& stream)
158 {
159 // TODO : implement async version
160 (void) stream;
161
162 using namespace cv::cuda::device::hough;
163 using namespace cv::cuda::device::hough_circles;
164
165 GpuMat src = _src.getGpuMat();
166
167 CV_Assert( src.type() == CV_8UC1 );
168 CV_Assert( src.cols < std::numeric_limits<unsigned short>::max() );
169 CV_Assert( src.rows < std::numeric_limits<unsigned short>::max() );
170 CV_Assert( dp_ > 0 );
171 CV_Assert( minRadius_ > 0 && maxRadius_ > minRadius_ );
172 CV_Assert( cannyThreshold_ > 0 );
173 CV_Assert( votesThreshold_ > 0 );
174 CV_Assert( maxCircles_ > 0 );
175
176 const float idp = 1.0f / dp_;
177
178 filterDx_->apply(src, dx_);
179 filterDy_->apply(src, dy_);
180
181 canny_->setLowThreshold(std::max(cannyThreshold_ / 2, 1));
182 canny_->setHighThreshold(cannyThreshold_);
183
184 canny_->detect(dx_, dy_, edges_);
185
186 ensureSizeIsEnough(2, src.size().area(), CV_32SC1, list_);
187 unsigned int* srcPoints = list_.ptr<unsigned int>(0);
188 unsigned int* centers = list_.ptr<unsigned int>(1);
189
190 const int pointsCount = buildPointList_gpu(edges_, srcPoints);
191 if (pointsCount == 0)
192 {
193 circles.release();
194 return;
195 }
196
197 ensureSizeIsEnough(cvCeil(src.rows * idp) + 2, cvCeil(src.cols * idp) + 2, CV_32SC1, accum_);
198 accum_.setTo(Scalar::all(0));
199
200 circlesAccumCenters_gpu(srcPoints, pointsCount, dx_, dy_, accum_, minRadius_, maxRadius_, idp);
201
202 accum_.download(tt);
203
204 int centersCount = buildCentersList_gpu(accum_, centers, votesThreshold_);
205 if (centersCount == 0)
206 {
207 circles.release();
208 return;
209 }
210
211 if (minDist_ > 1)
212 {
213 AutoBuffer<ushort2> oldBuf_(centersCount);
214 AutoBuffer<ushort2> newBuf_(centersCount);
215 int newCount = 0;
216
217 ushort2* oldBuf = oldBuf_;
218 ushort2* newBuf = newBuf_;
219
220 cudaSafeCall( cudaMemcpy(oldBuf, centers, centersCount * sizeof(ushort2), cudaMemcpyDeviceToHost) );
221
222 const int cellSize = cvRound(minDist_);
223 const int gridWidth = (src.cols + cellSize - 1) / cellSize;
224 const int gridHeight = (src.rows + cellSize - 1) / cellSize;
225
226 std::vector< std::vector<ushort2> > grid(gridWidth * gridHeight);
227
228 const float minDist2 = minDist_ * minDist_;
229
230 std::vector<Vec3f> sortBuf;
231 for(int i=0; i<centersCount; i++){
232 Vec3f temp;
233 temp[0] = oldBuf[i].x;
234 temp[1] = oldBuf[i].y;
235 temp[2] = tt.at<int>(temp[1]+1, temp[0]+1);
236 sortBuf.push_back(temp);
237 }
238 std::sort(sortBuf.begin(), sortBuf.end(), centersCompare);
239
240 for (int i = 0; i < centersCount; ++i)
241 {
242 ushort2 p;
243 p.x = sortBuf[i][0];
244 p.y = sortBuf[i][1];
245
246 bool good = true;
247
248 int xCell = static_cast<int>(p.x / cellSize);
249 int yCell = static_cast<int>(p.y / cellSize);
250
251 int x1 = xCell - 1;
252 int y1 = yCell - 1;
253 int x2 = xCell + 1;
254 int y2 = yCell + 1;
255
256 // boundary check
257 x1 = std::max(0, x1);
258 y1 = std::max(0, y1);
259 x2 = std::min(gridWidth - 1, x2);
260 y2 = std::min(gridHeight - 1, y2);
261
262 for (int yy = y1; yy <= y2; ++yy)
263 {
264 for (int xx = x1; xx <= x2; ++xx)
265 {
266 std::vector<ushort2>& m = grid[yy * gridWidth + xx];
267
268 for(size_t j = 0; j < m.size(); ++j)
269 {
270 float dx = (float)(p.x - m[j].x);
271 float dy = (float)(p.y - m[j].y);
272
273 if (dx * dx + dy * dy < minDist2)
274 {
275 good = false;
276 goto break_out;
277 }
278 }
279 }
280 }
281
282 break_out:
283
284 if(good)
285 {
286 grid[yCell * gridWidth + xCell].push_back(p);
287
288 newBuf[newCount++] = p;
289 }
290 }
291
292 cudaSafeCall( cudaMemcpy(centers, newBuf, newCount * sizeof(unsigned int), cudaMemcpyHostToDevice) );
293 centersCount = newCount;
294 }
295
296 ensureSizeIsEnough(1, maxCircles_, CV_32FC3, result_);
297
298 int circlesCount = circlesAccumRadius_gpu(centers, centersCount, srcPoints, pointsCount, result_.ptr<float3>(), maxCircles_,
299 dp_, minRadius_, maxRadius_, votesThreshold_, deviceSupports(FEATURE_SET_COMPUTE_20));
300
301 if (circlesCount == 0)
302 {
303 circles.release();
304 return;
305 }
306
307 result_.cols = circlesCount;
308 result_.copyTo(circles);
309 }
310 }
311
createHoughCirclesDetector(float dp,float minDist,int cannyThreshold,int votesThreshold,int minRadius,int maxRadius,int maxCircles)312 Ptr<HoughCirclesDetector> cv::cuda::createHoughCirclesDetector(float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles)
313 {
314 return makePtr<HoughCirclesDetectorImpl>(dp, minDist, cannyThreshold, votesThreshold, minRadius, maxRadius, maxCircles);
315 }
316
317 #endif /* !defined (HAVE_CUDA) */
318