/external/libgdx/extensions/gdx-bullet/jni/swig/collision/ |
btConvexHullShape.i | 9 btConvexHullShape(const btShapeHull *hull) { 11 for (int i = 0; i < hull->numVertices(); i++) { 12 result->addPoint(hull->getVertexPointer()[i]);
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/external/libgdx/gdx/src/com/badlogic/gdx/math/ |
ConvexHull.java | 23 /** Computes the convex hull of a set of points using the monotone chain convex hull algorithm (aka Andrew's algorithm).
28 private final FloatArray hull = new FloatArray();
field in class:ConvexHull 42 /** Returns a list of points on the convex hull in counter-clockwise order. Note: the last point in the returned list is the
44 /** Returns the convex hull polygon for the given point cloud.
47 * hull algorithm. If sorting is done the input array is not modified and count additional working memory is needed.
48 * @return pairs of coordinates that describe the convex hull polygon in counterclockwise order. Note the returned array is
61 FloatArray hull = this.hull;
local 62 hull.clear(); 112 FloatArray hull = this.hull; local 154 FloatArray hull = this.hull; local [all...] |
/external/opencv3/samples/cpp/ |
convexhull.cpp | 39 vector<int> hull; local 40 convexHull(Mat(points), hull, true); local 46 int hullcount = (int)hull.size(); 47 Point pt0 = points[hull[hullcount-1]]; 51 Point pt = points[hull[i]]; 56 imshow("hull", img);
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/external/opencv3/samples/cpp/tutorial_code/ShapeDescriptors/ |
hull_demo.cpp | 65 /// Find the convex hull object for each contour 66 vector<vector<Point> >hull( contours.size() ); 68 { convexHull( Mat(contours[i]), hull[i], false ); } local 70 /// Draw contours + hull results 76 drawContours( drawing, hull, (int)i, color, 1, 8, vector<Vec4i>(), 0, Point() ); 80 namedWindow( "Hull demo", WINDOW_AUTOSIZE ); 81 imshow( "Hull demo", drawing );
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/external/libgdx/extensions/gdx-bullet/jni/src/bullet/LinearMath/ |
btGrahamScan2dConvexHull.h | 59 inline void GrahamScanConvexHull2D(btAlignedObjectArray<GrahamVector3>& originalPoints, btAlignedObjectArray<GrahamVector3>& hull, const btVector3& normalAxis) 68 hull.push_back(originalPoints[0]); 107 hull.push_back(originalPoints[i]); 113 while (!isConvex&& hull.size()>1) { 114 btVector3& a = hull[hull.size()-2]; 115 btVector3& b = hull[hull.size()-1]; 118 hull.pop_back(); 120 hull.push_back(originalPoints[i]) [all...] |
btConvexHullComputer.h | 21 /// Convex hull implementation based on Preparata and Hong 68 // Vertices of the output hull 71 // Edges of the output hull 74 // Faces of the convex hull. Each entry is an index into the "edges" array pointing to an edge of the face. Faces are planar n-gons 78 Compute convex hull of "count" vertices stored in "coords". "stride" is the difference in bytes 79 between the addresses of consecutive vertices. If "shrink" is positive, the convex hull is shrunken 82 is the minimum distance of a face to the center of the convex hull. 84 The returned value is the amount by which the hull has been shrunken. If it is negative, the amount was so large 85 that the resulting convex hull is empty. 87 The output convex hull can be found in the member variables "vertices", "edges", "faces" [all...] |
btConvexHull.h | 3 Stan Melax Convex Hull Computation 38 unsigned int mNumOutputVertices; // number of vertices in the output hull 66 mMaxVertices = 4096; // maximum number of points to be considered for a convex hull. 99 unsigned int mFlags; // flags to use when generating the convex hull. 104 unsigned int mMaxVertices; // maximum number of vertices to be considered for the hull! 182 ///The HullLibrary class can create a convex hull from a collection of vertices, using the ComputeHull method. 224 //BringOutYourDead (John Ratcliff): When you create a convex hull you hand it a large input set of vertices forming a 'point cloud'. 225 //After the hull is generated it give you back a set of polygon faces which index the *original* point cloud. 226 //The thing is, often times, there are many 'dead vertices' in the point cloud that are on longer referenced by the hull. 227 //The routine 'BringOutYourDead' find only the referenced vertices, copies them to an new buffer, and re-indexes the hull so that it is a minimal representation [all...] |
/external/opencv3/modules/imgproc/src/ |
convhull.cpp | 201 // gather upper part of convex hull to output 239 // the bottom part of the convex hull is the mirrored top part 257 Mat hull = _hull.getMat(); local 258 size_t step = !hull.isContinuous() ? hull.step[0] : sizeof(Point); 260 *(Point*)(hull.ptr() + i*step) = data0[hullbuf[i]]; 277 Mat hull = _hull.getMat(); local 278 int hpoints = hull.checkVector(1, CV_32S); 282 const int* hptr = hull.ptr<int>(); 285 // 1. recognize co-orientation of the contour and its hull 398 union { CvContour* c; CvSeq* s; } hull; local 528 CvSeq *ptseq = (CvSeq*)array, *hull = (CvSeq*)hullarray; local [all...] |
rotcalipers.cpp | 65 // points - convex hull vertices ( any orientation ) 146 // find convex hull orientation 345 Mat hull; local 349 convexHull(_points, hull, true, true); 351 if( hull.depth() != CV_32F ) 354 hull.convertTo(temp, CV_32F); 355 hull = temp; 358 int n = hull.checkVector(2); 359 const Point2f* hpoints = hull.ptr<Point2f>();
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/external/opencv/cv/src/ |
cvconvhull.cpp | 231 union { CvContour* c; CvSeq* s; } hull; local 238 hull.s = 0; 298 "The hull matrix should be continuous and have a single row or a single column" ); 301 CV_ERROR( CV_StsBadSize, "The hull matrix size might be not enough to fit the hull" ); 306 "The hull matrix must have the same type as input or 32sC1 (integers)" ); 397 /* gather upper part of convex hull to output */ 452 the bottom part of the convex hull is the mirrored top part 496 hull.s = hullseq; 497 hull.c->rect = cvBoundingRect( ptseq 536 CvSeq *ptseq = (CvSeq*)array, *hull = (CvSeq*)hullarray; local [all...] |
/external/opencv3/doc/py_tutorials/py_imgproc/py_contours/py_contour_features/ |
py_contour_features.markdown | 80 5. Convex Hull 83 Convex Hull will look similar to contour approximation, but it is not (Both may provide same results 87 below image of hand. Red line shows the convex hull of hand. The double-sided arrow marks shows the 88 convexity defects, which are the local maximum deviations of hull from contours. 94 hull = cv2.convexHull(points[, hull[, clockwise[, returnPoints]] 99 - **hull** is the output, normally we avoid it. 100 - **clockwise** : Orientation flag. If it is True, the output convex hull is oriented clockwise. 102 - **returnPoints** : By default, True. Then it returns the coordinates of the hull points. If 103 False, it returns the indices of contour points corresponding to the hull points [all...] |
/external/opencv3/doc/py_tutorials/py_imgproc/py_contours/py_contours_more_functions/ |
py_contours_more_functions.markdown | 17 We saw what is convex hull in second chapter about contours. Any deviation of the object from this 18 hull can be considered as convexity defect. 23 hull = cv2.convexHull(cnt,returnPoints = False) 24 defects = cv2.convexityDefects(cnt,hull) 27 @note Remember we have to pass returnPoints = False while finding convex hull, in order to find 45 hull = cv2.convexHull(cnt,returnPoints = False) 46 defects = cv2.convexityDefects(cnt,hull)
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/external/libgdx/tests/gdx-tests/src/com/badlogic/gdx/tests/bullet/ |
ConvexHullTest.java | 60 final btShapeHull hull = new btShapeHull(shape); 61 hull.buildHull(shape.getMargin()); 62 final btConvexHullShape result = new btConvexHullShape(hull); 65 hull.dispose();
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ConvexHullDistanceTest.java | 104 final btShapeHull hull = new btShapeHull(shape); 105 hull.buildHull(shape.getMargin()); 106 final btConvexHullShape result = new btConvexHullShape(hull); 109 hull.dispose();
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/external/opencv3/doc/tutorials/imgproc/shapedescriptors/hull/ |
hull.markdown | 1 Convex Hull {#tutorial_hull}
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/external/libgdx/extensions/gdx-bullet/jni/src/bullet/BulletCollision/CollisionShapes/ |
btShapeHull.h | 25 ///The btShapeHull class takes a btConvexShape, builds a simplified convex hull using btConvexHull and provides triangle indices and vertices. 27 ///It approximates the convex hull using the supporting vertex of 42 directions.
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btPolyhedralConvexShape.cpp | 200 //do the merge: use Graham Scan 2d convex hull 239 btAlignedObjectArray<GrahamVector3> hull; local 242 GrahamScanConvexHull2D(orgpoints,hull,averageFaceNormal); 244 for (int i=0;i<hull.size();i++) 246 combinedFace.m_indices.push_back(hull[i].m_orgIndex); 249 if(orgpoints[k].m_orgIndex == hull[i].m_orgIndex) 264 continue; // this is in the hull...
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/packages/inputmethods/LatinIME/java/res/values-hu/ |
strings-letter-descriptions.xml | 36 <string name="spoken_accented_letter_00E3" msgid="8252569677935693343">"A, hullámvonallal"</string> 50 <string name="spoken_accented_letter_00F1" msgid="6983294908255378605">"N, hullámvonallal"</string> 54 <string name="spoken_accented_letter_00F5" msgid="7320512716652765243">"O, hullámvonallal"</string> 84 <string name="spoken_accented_letter_0129" msgid="7824912405885325754">"I, hullámvonallal"</string> 117 <string name="spoken_accented_letter_0169" msgid="413046581387735371">"U, hullámvonallal"</string> 139 <string name="spoken_accented_letter_1EAB" msgid="7236523151662538333">"A, kúpos ékezettel és hullámvonallal"</string> 144 <string name="spoken_accented_letter_1EB5" msgid="3720427596242746295">"A, rövidségi jellel és hullámvonallal"</string> 148 <string name="spoken_accented_letter_1EBD" msgid="181253633045931897">"E, hullámvonallal"</string> 152 <string name="spoken_accented_letter_1EC5" msgid="2216559244705714587">"E, kúpos ékezettel és hullámvonallal"</string> 161 <string name="spoken_accented_letter_1ED7" msgid="7924481354960306389">"O, kúpos ékezettel és hullámvonallal"</string [all...] |
/packages/apps/Launcher3/src/com/android/launcher3/util/ |
IconNormalizer.java | 70 * We first calculate the convex hull of the visible portion of the icon. 71 * This hull then compared with the bounding rectangle of the hull to find how closely it 75 * This closeness is used to determine the ratio of hull area to the full icon size. 151 // Area of the convex hull 160 // Area of the rectangle required to fit the convex hull
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/external/opencv3/doc/py_tutorials/py_imgproc/py_contours/py_contour_properties/ |
py_contour_properties.markdown | 38 Solidity is the ratio of contour area to its convex hull area. 40 \f[Solidity = \frac{Contour \; Area}{Convex \; Hull \; Area}\f] 43 hull = cv2.convexHull(cnt) 44 hull_area = cv2.contourArea(hull)
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/external/skia/src/pathops/ |
SkOpCubicHull.cpp | 44 /* Given a cubic, find the convex hull described by the end and control points. 45 The hull may have 3 or 4 points. Cubics that degenerate into a point or line 48 The hull is computed by assuming that three points, if unique and non-linear, 53 The indices returned in order describe the convex hull.
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/external/libgdx/extensions/gdx-bullet/jni/swig-src/collision/com/badlogic/gdx/physics/bullet/collision/ |
btConvexHullShape.java | 118 public btConvexHullShape(btShapeHull hull) { 119 this(CollisionJNI.new_btConvexHullShape__SWIG_4(btShapeHull.getCPtr(hull), hull), true);
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/external/opencv3/modules/python/test/ |
tickets.py | 30 hull = cv.ConvexHull2(pts, storage) 32 defects = cv.ConvexityDefects(pts, hull, storage) 50 # Draw the convex hull as a thick green line
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/external/libgdx/extensions/gdx-box2d/gdx-box2d/jni/Box2D/Collision/Shapes/ |
b2PolygonShape.cpp | 163 // Create the convex hull using the Gift wrapping algorithm 166 // Find the right most point on the hull 179 int32 hull[b2_maxPolygonVertices]; local 185 hull[m] = ih; 196 b2Vec2 r = ps[ie] - ps[hull[m]]; 197 b2Vec2 v = ps[j] - ps[hull[m]]; 233 m_vertices[i] = ps[hull[i]];
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/external/libgdx/extensions/gdx-box2d/gdx-box2d-gwt/src/com/badlogic/gdx/physics/box2d/gwt/emu/org/jbox2d/collision/shapes/ |
PolygonShape.java | 103 * Create a convex hull from the given array of points. The count must be in the range [3, 114 * Create a convex hull from the given array of points. The count must be in the range [3, 159 // Create the convex hull using the Gift wrapping algorithm 162 // Find the right most point on the hull 173 int[] hull = local 181 hull[m] = ih; 190 Vec2 r = pool1.set(ps[ie]).subLocal(ps[hull[m]]); 191 Vec2 v = pool2.set(ps[j]).subLocal(ps[hull[m]]); 218 m_vertices[i].set(ps[hull[i]]);
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