def obb(opts,argv): poly = nv.readVTK(argv[0]) obb = vtk.vtkOBBTree() obb.SetMaxLevel(10) obb.SetNumberOfCellsPerNode(5) obb.AutomaticOn() sfilt = vtk.vtkSpatialRepresentationFilter() sfilt.SetSpatialRepresentation(obb) sfilt.SetInput(poly) sfilt.Update() nv.writeVTK(argv[1],sfilt.GetOutput())
def concomp(opts, argv): p = nv.readVTK(argv[0]) c = vtk.vtkPolyDataConnectivityFilter() c.SetInput(p) c.SetExtractionModeToLargestRegion() c.Update() d = vtk.vtkCleanPolyData() d.SetInput(c.GetOutput()) d.Update() p = d.GetOutput() nv.writeVTK(argv[1],p)
def obb(opts, argv):
poly = nv.readVTK(argv[0])
obb = vtk.vtkOBBTree()
obb.SetMaxLevel(10)
obb.SetNumberOfCellsPerNode(5)
obb.AutomaticOn()
sfilt = vtk.vtkSpatialRepresentationFilter()
sfilt.SetSpatialRepresentation(obb)
sfilt.SetInput(poly)
sfilt.Update()
nv.writeVTK(argv[1], sfilt.GetOutput())
def concomp(opts, argv):
p = nv.readVTK(argv[0])
c = vtk.vtkPolyDataConnectivityFilter()
c.SetInput(p)
c.SetExtractionModeToLargestRegion()
c.Update()
d = vtk.vtkCleanPolyData()
d.SetInput(c.GetOutput())
d.Update()
p = d.GetOutput()
nv.writeVTK(argv[1], p)
def main(opts, argv):
inputvtk = argv[0]
outputvtk = argv[1]
inVTK = nv.readVTK(inputvtk);
if (opts.sep == "0"):
csvreader = csv.reader(open(opts.csvfile, "r"))
elif (opts.sep == "1"):
csvreader = csv.reader(open(opts.csvfile, "r"), delimiter=',')
elif (opts.sep == "2"):
csvreader = csv.reader(open(opts.csvfile, "r"), delimiter='\t')
first = csvreader.next()
if (opts.header):
header = first
first = csvreader.next()
if (opts.names != ""):
header = opts.names.split(",")
print header
nCols = len(first)
nPoints = inVTK.GetNumberOfPoints()
data = np.zeros([nPoints,nCols])
for k in range(0,nCols):
data[0,k] = float(first[k])
print "# points:", nPoints
for j in range(1,nPoints):
print j
first = csvreader.next()
for k in range(0,nCols):
data[j,k] = float(first[k])
for k in range(0,nCols):
arr = vtkDoubleArray()
if (len(header) > 0):
arr.SetName(header[k])
arr.SetNumberOfTuples(nPoints)
for j in range(0,nPoints):
arr.SetValue(j,data[j,k])
inVTK.GetPointData().AddArray(arr)
nv.writeVTK(outputvtk, inVTK)
def removeAttributes(opts, args):
print args
inputvtk = args[0]
outputvtk = args[1]
inVTK = nv.readVTK(inputvtk);
nArrays = inVTK.GetPointData().GetNumberOfArrays()
arrayNames = []
for k in range(0,nArrays):
arrayNames.append(inVTK.GetPointData().GetArrayName(k))
print arrayNames
for name in arrayNames:
inVTK.GetPointData().RemoveArray(name)
nv.writeVTK(outputvtk, inVTK)
def removeAttributes(opts, args):
print args
inputvtk = args[0]
outputvtk = args[1]
inVTK = nv.readVTK(inputvtk)
nArrays = inVTK.GetPointData().GetNumberOfArrays()
arrayNames = []
for k in range(0, nArrays):
arrayNames.append(inVTK.GetPointData().GetArrayName(k))
print arrayNames
for name in arrayNames:
inVTK.GetPointData().RemoveArray(name)
nv.writeVTK(outputvtk, inVTK)
def principalAxes(opts, argv): p = nv.readVTK(argv[0]) for i in range(0,p.GetNumberOfPoints()): s = p.GetPoint(i) s = (-s[0],-s[1],s[2]) p.GetPoints().SetPoint(i,s) #g = vtk.vtkUnstructuredGrid() #g.SetPoints(vtk.vtkPoints()) pOBB = OBB() vtk.vtkOBBTree.ComputeOBB(p.GetPoints(), pOBB.corner, pOBB.m1, pOBB.m2, pOBB.m3, pOBB.sz) #pOBB.MakeCube(g) translateToMean(p,pOBB.Center(),-1) pR = pOBB.AxisAlign() print pR pOut = transform(p,pR) nv.writeVTK(argv[1], pOut) writeITKTransform(argv[2], pR, np.asarray((255,255,79)) - pOBB.Center(), pOBB.Center())
def main(opts, argv):
inputvtk = argv[0]
outputvtk = argv[1]
inVTK = nv.readVTK(inputvtk)
if (opts.sep == "0"):
csvreader = csv.reader(open(opts.csvfile, "r"))
elif (opts.sep == "1"):
csvreader = csv.reader(open(opts.csvfile, "r"), delimiter=',')
elif (opts.sep == "2"):
csvreader = csv.reader(open(opts.csvfile, "r"), delimiter='\t')
first = csvreader.next()
if (opts.header):
header = first
first = csvreader.next()
if (opts.names != ""):
header = opts.names.split(",")
print header
nCols = len(first)
nPoints = inVTK.GetNumberOfPoints()
data = np.zeros([nPoints, nCols])
for k in range(0, nCols):
data[0, k] = float(first[k])
print "# points:", nPoints
for j in range(1, nPoints):
print j
first = csvreader.next()
for k in range(0, nCols):
data[j, k] = float(first[k])
for k in range(0, nCols):
arr = vtkDoubleArray()
if (len(header) > 0):
arr.SetName(header[k])
arr.SetNumberOfTuples(nPoints)
for j in range(0, nPoints):
arr.SetValue(j, data[j, k])
inVTK.GetPointData().AddArray(arr)
nv.writeVTK(outputvtk, inVTK)
def normalHistogram(opts,argv):
poly = nv.readVTK(argv[0])
normfilt = vtk.vtkPolyDataNormals()
normfilt.ConsistencyOn()
normfilt.AutoOrientNormalsOn()
normfilt.ComputeCellNormalsOn()
normfilt.SetInput(poly)
normfilt.SetFeatureAngle(90)
normfilt.Update()
poly = normfilt.GetOutput()
nv.writeVTK("nrom.vtk", poly)
normals = poly.GetCellData().GetArray("Normals", vtk.mutable(0))
normMap = vtk.vtkUnstructuredGrid()
normMap.SetPoints(vtk.vtkPoints())
normPts = normMap.GetPoints()
for i in range(0, normals.GetNumberOfTuples()):
norm = [0,0,0]
normals.GetTuple(i, norm)
normPts.InsertNextPoint(norm)
nv.writeVTK(argv[1], normMap)
def icp(opts,args): v1 = nv.readVTK(args[0]) v2 = nv.readVTK(args[1]) icp = vtk.vtkIterativeClosestPointTransform() icp.SetSource(v2) icp.SetTarget(v1) icp.StartByMatchingCentroidsOn() icp.SetMaximumNumberOfIterations(500) icp.SetMaximumNumberOfLandmarks(20000) tx = icp.GetLandmarkTransform() tx.SetModeToRigidBody() icp.Update() tx = icp.GetLandmarkTransform() txf = vtk.vtkTransformPolyDataFilter() txf.SetInput(v2) txf.SetTransform(tx) txf.Update() v3 = txf.GetOutput() nv.writeVTK(args[2], v3) return
def normalHistogram(opts, argv):
poly = nv.readVTK(argv[0])
normfilt = vtk.vtkPolyDataNormals()
normfilt.ConsistencyOn()
normfilt.AutoOrientNormalsOn()
normfilt.ComputeCellNormalsOn()
normfilt.SetInput(poly)
normfilt.SetFeatureAngle(90)
normfilt.Update()
poly = normfilt.GetOutput()
nv.writeVTK("nrom.vtk", poly)
normals = poly.GetCellData().GetArray("Normals", vtk.mutable(0))
normMap = vtk.vtkUnstructuredGrid()
normMap.SetPoints(vtk.vtkPoints())
normPts = normMap.GetPoints()
for i in range(0, normals.GetNumberOfTuples()):
norm = [0, 0, 0]
normals.GetTuple(i, norm)
normPts.InsertNextPoint(norm)
nv.writeVTK(argv[1], normMap)
def icp(opts, args):
v1 = nv.readVTK(args[0])
v2 = nv.readVTK(args[1])
icp = vtk.vtkIterativeClosestPointTransform()
icp.SetSource(v2)
icp.SetTarget(v1)
icp.StartByMatchingCentroidsOn()
icp.SetMaximumNumberOfIterations(500)
icp.SetMaximumNumberOfLandmarks(20000)
tx = icp.GetLandmarkTransform()
tx.SetModeToRigidBody()
icp.Update()
tx = icp.GetLandmarkTransform()
txf = vtk.vtkTransformPolyDataFilter()
txf.SetInput(v2)
txf.SetTransform(tx)
txf.Update()
v3 = txf.GetOutput()
nv.writeVTK(args[2], v3)
return
def principalAxes(opts, argv):
p = nv.readVTK(argv[0])
for i in range(0, p.GetNumberOfPoints()):
s = p.GetPoint(i)
s = (-s[0], -s[1], s[2])
p.GetPoints().SetPoint(i, s)
#g = vtk.vtkUnstructuredGrid()
#g.SetPoints(vtk.vtkPoints())
pOBB = OBB()
vtk.vtkOBBTree.ComputeOBB(p.GetPoints(), pOBB.corner, pOBB.m1, pOBB.m2,
pOBB.m3, pOBB.sz)
#pOBB.MakeCube(g)
translateToMean(p, pOBB.Center(), -1)
pR = pOBB.AxisAlign()
print pR
pOut = transform(p, pR)
nv.writeVTK(argv[1], pOut)
writeITKTransform(argv[2], pR,
np.asarray((255, 255, 79)) - pOBB.Center(),
pOBB.Center())
