| /external/ceres-solver/internal/ceres/ |
| canonical_views_clustering.cc | 56 // graph. centers will contain the vertices that are the identified
57 // as the canonical views/cluster centers, and membership is a map
65 vector<int>* centers,
71 const vector<int>& centers) const;
73 void ComputeClusterMembership(const vector<int>& centers,
89 vector<int>* centers,
93 cv.ComputeClustering(options, graph, centers, membership);
102 vector<int>* centers,
105 CHECK_NOTNULL(centers)->clear();
121 ComputeClusteringQualityDifference(*view, *centers);
[all...] |
| canonical_views_clustering.h | 94 // centers will contain the vertices that are the identified
95 // as the canonical views/cluster centers, and membership is a map
105 vector<int>* centers,
|
| /external/opencv3/modules/features2d/src/ |
| blobdetector.cpp | 79 virtual void findBlobs(InputArray image, InputArray binaryImage, std::vector<Center> ¢ers) const;
190 void SimpleBlobDetectorImpl::findBlobs(InputArray _image, InputArray _binaryImage, std::vector<Center> ¢ers) const
194 centers.clear();
291 centers.push_back(center);
314 std::vector < std::vector<Center> > centers; local
326 for (size_t j = 0; j < centers.size(); j++)
328 double dist = norm(centers[j][ centers[j].size() / 2 ].location - curCenters[i].location);
329 isNew = dist >= params.minDistBetweenBlobs && dist >= centers[j][ centers[j].size() / 2 ].radius && dist >= curCenters[i].radius
[all...] |
| /external/opencv3/modules/core/src/ |
| kmeans.cpp | 108 int* centers = &_centers[0]; local
113 centers[0] = (unsigned)rng % N;
117 dist[i] = normL2Sqr(data + step*i, data + step*centers[0], dims);
148 centers[k] = bestCenter;
155 const float* src = data + step*centers[k];
172 centers(_centers)
180 const int K = centers.rows;
181 const int dims = centers.cols;
191 const float* center = centers.ptr<float>(k);
212 const Mat& centers; member in class:cv::KMeansDistanceComputer
[all...] |
| /external/opencv3/3rdparty/libwebp/enc/ |
| analysis.c | 80 const int centers[NUM_MB_SEGMENTS],
83 int min = centers[0], max = centers[0];
88 if (min > centers[n]) min = centers[n];
89 if (max < centers[n]) max = centers[n];
95 const int alpha = 255 * (centers[n] - mid) / (max - min);
96 const int beta = 255 * (centers[n] - min) / (max - min);
148 int centers[NUM_MB_SEGMENTS] local
[all...] |
| /external/opencv3/modules/flann/include/opencv2/flann/ |
| hierarchical_clustering_index.h | 63 // Algorithm used for picking the initial cluster centers
92 * The function used for choosing the cluster centers.
99 * Chooses the initial centers in the k-means clustering in a random manner.
102 * k = number of centers
108 void chooseCentersRandom(int k, int* dsindices, int indices_length, int* centers, int& centers_length)
124 centers[index] = dsindices[rnd];
127 DistanceType sq = distance(dataset[centers[index]], dataset[centers[j]], dataset.cols);
140 * Chooses the initial centers in the k-means using Gonzales' algorithm
141 * so that the centers are spaced apart from each other
[all...] |
| kmeans_index.h | 65 // algorithm used for picking the initial cluster centers for kmeans tree
91 * The function used for choosing the cluster centers.
98 * Chooses the initial centers in the k-means clustering in a random manner.
101 * k = number of centers
107 void chooseCentersRandom(int k, int* indices, int indices_length, int* centers, int& centers_length)
123 centers[index] = indices[rnd];
126 DistanceType sq = distance_(dataset_[centers[index]], dataset_[centers[j]], dataset_.cols);
139 * Chooses the initial centers in the k-means using Gonzales' algorithm
140 * so that the centers are spaced apart from each other
832 DistanceType** centers = new DistanceType*[branching]; local
[all...] |
| flann_base.hpp | 271 * @param centers The computed cluster centres. Matrix should be preallocated and centers.rows is the
279 int hierarchicalClustering(const Matrix<typename Distance::ElementType>& points, Matrix<typename Distance::ResultType>& centers,
285 int clusterNum = kmeans.getClusterCenters(centers);
|
| /external/opencv3/samples/cpp/ |
| kmeans.cpp | 13 // "centers and uses kmeans to move those cluster centers to their representitive location\n"
40 Mat centers; local
58 3, KMEANS_PP_CENTERS, centers);
|
| delaunay2.cpp | 81 vector<Point2f> centers; local
82 subdiv.getVoronoiFacetList(vector<int>(), facets, centers); local
101 circle(img, centers[i], 3, Scalar(), FILLED, LINE_AA, 0);
|
| /external/webp/src/enc/ |
| analysis.c | 77 const int centers[NUM_MB_SEGMENTS],
80 int min = centers[0], max = centers[0];
85 if (min > centers[n]) min = centers[n];
86 if (max < centers[n]) max = centers[n];
92 const int alpha = 255 * (centers[n] - mid) / (max - min);
93 const int beta = 255 * (centers[n] - min) / (max - min);
146 // array bounds of 'centers' with some compilers (noticed with gcc-4.9)
149 int centers[NUM_MB_SEGMENTS]; local
[all...] |
| /external/opencv3/modules/cudaimgproc/src/cuda/ |
| hough_circles.cu | 130 __global__ void buildCentersList(const PtrStepSzi accum, unsigned int* centers, const int threshold)
149 centers[idx] = val;
154 int buildCentersList_gpu(PtrStepSzi accum, unsigned int* centers, int threshold)
166 buildCentersList<<<grid, block>>>(accum, centers, threshold);
180 __global__ void circlesAccumRadius(const unsigned int* centers, const unsigned int* list, const int count,
190 unsigned int val = centers[blockIdx.x];
229 int circlesAccumRadius_gpu(const unsigned int* centers, int centersCount, const unsigned int* list, int count,
243 circlesAccumRadius<<<grid, block, smemSize>>>(centers, list, count, circles, maxCircles, dp, minRadius, maxRadius, histSize, threshold);
|
| /external/opencv3/modules/cudaimgproc/src/ |
| hough_circles.cpp | 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,
188 unsigned int* centers = list_.ptr<unsigned int>(1);
204 int centersCount = buildCentersList_gpu(accum_, centers, votesThreshold_);
220 cudaSafeCall( cudaMemcpy(oldBuf, centers, centersCount * sizeof(ushort2), cudaMemcpyDeviceToHost) );
292 cudaSafeCall( cudaMemcpy(centers, newBuf, newCount * sizeof(unsigned int), cudaMemcpyHostToDevice) );
298 int circlesCount = circlesAccumRadius_gpu(centers, centersCount, srcPoints, pointsCount, result_.ptr<float3>(), maxCircles_,
|
| /external/opencv3/modules/calib3d/misc/java/test/ |
| Calib3dTest.java | 196 Mat centers = new Mat(); local
198 assertFalse(Calib3d.findCirclesGrid(img, new Size(5, 5), centers));
206 assertTrue(Calib3d.findCirclesGrid(img, new Size(5, 5), centers));
208 assertEquals(25, centers.rows());
209 assertEquals(1, centers.cols());
210 assertEquals(CvType.CV_32FC2, centers.type());
217 Mat centers = new Mat(); local
219 assertFalse(Calib3d.findCirclesGrid(img, new Size(3, 5), centers, Calib3d.CALIB_CB_CLUSTERING
231 assertTrue(Calib3d.findCirclesGrid(img, new Size(3, 5), centers, Calib3d.CALIB_CB_CLUSTERING
234 assertEquals(15, centers.rows())
[all...] |
| /external/opencv3/modules/core/perf/ |
| perf_math.cpp | 37 Mat labels, centers; local
56 attempts, KMEANS_PP_CENTERS, centers);
|
| /development/ndk/platforms/android-18/samples/gles3jni/jni/ |
| gles3jni.cpp | 169 float centers[2][MAX_INSTANCES_PER_SIDE]; local
173 centers[d][i] = scene2clip[d] * (CELL_SIZE*(i + 0.5f) + offset);
179 // outer product of centers[0] and centers[1]
183 offsets[2*idx + major] = centers[0][i];
184 offsets[2*idx + minor] = centers[1][j];
|
| /external/opencv3/samples/python2/ |
| kmeans.py | 35 ret, labels, centers = cv2.kmeans(points, cluster_n, None, term_crit, 10, 0)
|
| /external/opencv3/modules/flann/include/opencv2/ |
| flann.hpp | 504 @param centers The centers of the clusters obtained. The matrix must have type
518 int hierarchicalClustering(const Mat& features, Mat& centers, const ::cvflann::KMeansIndexParams& params,
528 CV_Assert(centers.type() == CvType<DistanceType>::type());
529 CV_Assert(centers.isContinuous());
530 ::cvflann::Matrix<DistanceType> m_centers((DistanceType*)centers.ptr<DistanceType>(0), centers.rows, centers.cols);
538 FLANN_DEPRECATED int hierarchicalClustering(const Mat& features, Mat& centers, const ::cvflann::KMeansIndexParams& params)
544 return hierarchicalClustering< L2<ELEM_TYPE> >(features, centers, params)
[all...] |
| /external/libgdx/extensions/gdx-box2d/gdx-box2d-gwt/src/com/badlogic/gdx/physics/box2d/gwt/emu/org/jbox2d/callbacks/ |
| DebugDraw.java | 180 public abstract void drawParticles(Vec2[] centers, float radius, ParticleColor[] colors, int count);
187 public abstract void drawParticlesWireframe(Vec2[] centers, float radius, ParticleColor[] colors,
|
| /external/opencv3/modules/calib3d/src/ |
| calibinit.cpp | 1952 std::vector<Point2f> centers; local
[all...] |
| circlesgrid.hpp | 65 void findGrid(const std::vector<cv::Point2f> &points, cv::Size patternSize, std::vector<cv::Point2f>& centers);
74 void parsePatternPoints(const std::vector<cv::Point2f> &patternPoints, const std::vector<cv::Point2f> &rectifiedPatternPoints, std::vector<cv::Point2f> ¢ers);
152 static cv::Mat rectifyGrid(cv::Size detectedGridSize, const std::vector<cv::Point2f>& centers, const std::vector<
|
| circlesgrid.cpp | 138 void CirclesGridClusterFinder::findGrid(const std::vector<cv::Point2f> &points, cv::Size _patternSize, std::vector<Point2f>& centers)
141 centers.clear();
188 parsePatternPoints(patternPoints, rectifiedPatternPoints, centers);
392 void CirclesGridClusterFinder::parsePatternPoints(const std::vector<cv::Point2f> &patternPoints, const std::vector<cv::Point2f> &rectifiedPatternPoints, std::vector<cv::Point2f> ¢ers)
397 centers.clear();
415 centers.push_back(patternPoints.at(indicesbuf[0]));
422 centers.clear();
816 Mat CirclesGridFinder::rectifyGrid(Size detectedGridSize, const std::vector<Point2f>& centers,
819 CV_Assert( !centers.empty() );
825 getDirection(centers[0], centers[detectedGridSize.width - 1], centers[centers.size() - 1]) < 0
[all...] |
| /external/opencv/ml/src/ |
| ml_inner_functions.cpp | 267 CvMat* centers = _centers; local
286 CV_CALL(centers = cvCreateMat (num_of_clusters, dim, CV_32FC1));
295 CV_CALL(centers = cvCreateMat (num_of_clusters, dim, CV_64FC1));
308 CV_CALL(cvGetCol (centers, ¢ers_comp, i));
314 if( (cvGetErrStatus () < 0) || (centers != _centers) )
315 cvReleaseMat (¢ers);
317 return _centers ? _centers : centers;
[all...] |
| mlem.cpp | 576 CvMat* centers = 0; local
595 CV_CALL( centers = cvCreateMat( nclusters, dims, CV_64FC1 ));
602 CV_CALL( cvConvert( centers0, centers ));
625 const double* c = (double*)(centers->data.ptr + k*centers->step);
658 CV_SWAP( centers, old_centers, temp );
659 cvZero( centers );
662 // update centers
667 double* c = (double*)(centers->data.ptr + k*centers->step)
[all...] |
| /external/opencv3/apps/traincascade/ |
| old_ml_inner_functions.cpp | 267 CvMat* centers = _centers; local
286 CV_CALL(centers = cvCreateMat (num_of_clusters, dim, CV_32FC1));
295 CV_CALL(centers = cvCreateMat (num_of_clusters, dim, CV_64FC1));
308 CV_CALL(cvGetCol (centers, ¢ers_comp, i));
314 if( (cvGetErrStatus () < 0) || (centers != _centers) )
315 cvReleaseMat (¢ers);
317 return _centers ? _centers : centers;
[all...] |
