Page MenuHome
Differential D163 Diff 474 release/scripts/freestyle/modules/freestyle/predicates.py

Changeset View

Standalone View

View Options

release/scripts/freestyle/modules/freestyle/predicates.py

  • This file was added.
# ##### BEGIN GPL LICENSE BLOCK #####
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software Foundation,
# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
#
# ##### END GPL LICENSE BLOCK #####
"""
Predicates operating on vertices (0D elements) and polylines (1D
elements). Also intended to be a collection of examples for predicate
definition in Python
"""
# module members
from _freestyle import (
ContourUP1D,
DensityLowerThanUP1D,
EqualToChainingTimeStampUP1D,
EqualToTimeStampUP1D,
ExternalContourUP1D,
FalseBP1D,
FalseUP0D,
FalseUP1D,
Length2DBP1D,
QuantitativeInvisibilityUP1D,
SameShapeIdBP1D,
ShapeUP1D,
TrueBP1D,
TrueUP0D,
TrueUP1D,
ViewMapGradientNormBP1D,
WithinImageBoundaryUP1D,
)
# constructs for predicate definition in Python
from freestyle.types import (
BinaryPredicate1D,
IntegrationType,
Nature,
TVertex,
UnaryPredicate0D,
UnaryPredicate1D,
)
from freestyle.functions import (
Curvature2DAngleF0D,
CurveNatureF1D,
DensityF1D,
GetCompleteViewMapDensityF1D,
GetCurvilinearAbscissaF0D,
GetDirectionalViewMapDensityF1D,
GetOccludersF1D,
GetProjectedZF1D,
GetShapeF1D,
GetSteerableViewMapDensityF1D,
GetZF1D,
QuantitativeInvisibilityF0D,
ZDiscontinuityF1D,
pyCurvilinearLengthF0D,
pyDensityAnisotropyF1D,
pyViewMapGradientNormF1D,
)
import random
## Unary predicates for 0D elements (vertices)
##############################################
class pyHigherCurvature2DAngleUP0D(UnaryPredicate0D):
def __init__(self,a):
UnaryPredicate0D.__init__(self)
self._a = a
def __call__(self, inter):
func = Curvature2DAngleF0D()
a = func(inter)
return (a > self._a)
class pyUEqualsUP0D(UnaryPredicate0D):
def __init__(self,u, w):
UnaryPredicate0D.__init__(self)
self._u = u
self._w = w
def __call__(self, inter):
func = pyCurvilinearLengthF0D()
u = func(inter)
return (u > (self._u-self._w)) and (u < (self._u+self._w))
class pyVertexNatureUP0D(UnaryPredicate0D):
def __init__(self,nature):
UnaryPredicate0D.__init__(self)
self._nature = nature
def __call__(self, inter):
v = inter.object
return (v.nature & self._nature) != 0
## check whether an Interface0DIterator
## is a TVertex and is the one that is
## hidden (inferred from the context)
class pyBackTVertexUP0D(UnaryPredicate0D):
def __init__(self):
UnaryPredicate0D.__init__(self)
self._getQI = QuantitativeInvisibilityF0D()
def __call__(self, iter):
if (iter.object.nature & Nature.T_VERTEX) == 0:
return False
if iter.is_end:
return False
if self._getQI(iter) != 0:
return True
return False
class pyParameterUP0DGoodOne(UnaryPredicate0D):
def __init__(self,pmin,pmax):
UnaryPredicate0D.__init__(self)
self._m = pmin
self._M = pmax
def __call__(self, inter):
u = inter.u
return ((u>=self._m) and (u<=self._M))
class pyParameterUP0D(UnaryPredicate0D):
def __init__(self,pmin,pmax):
UnaryPredicate0D.__init__(self)
self._m = pmin
self._M = pmax
def __call__(self, inter):
func = Curvature2DAngleF0D()
c = func(inter)
b1 = (c>0.1)
u = inter.u
b = ((u>=self._m) and (u<=self._M))
return b and b1
## Unary predicates for 1D elements (curves)
############################################
class AndUP1D(UnaryPredicate1D):
def __init__(self, pred1, pred2):
UnaryPredicate1D.__init__(self)
self.__pred1 = pred1
self.__pred2 = pred2
def __call__(self, inter):
return self.__pred1(inter) and self.__pred2(inter)
class OrUP1D(UnaryPredicate1D):
def __init__(self, pred1, pred2):
UnaryPredicate1D.__init__(self)
self.__pred1 = pred1
self.__pred2 = pred2
def __call__(self, inter):
return self.__pred1(inter) or self.__pred2(inter)
class NotUP1D(UnaryPredicate1D):
def __init__(self, pred):
UnaryPredicate1D.__init__(self)
self.__pred = pred
def __call__(self, inter):
return not self.__pred(inter)
class pyNFirstUP1D(UnaryPredicate1D):
def __init__(self, n):
UnaryPredicate1D.__init__(self)
self.__n = n
self.__count = 0
def __call__(self, inter):
self.__count = self.__count + 1
if self.__count <= self.__n:
return True
return False
class pyHigherLengthUP1D(UnaryPredicate1D):
def __init__(self,l):
UnaryPredicate1D.__init__(self)
self._l = l
def __call__(self, inter):
return (inter.length_2d > self._l)
class pyNatureUP1D(UnaryPredicate1D):
def __init__(self,nature):
UnaryPredicate1D.__init__(self)
self._nature = nature
self._getNature = CurveNatureF1D()
def __call__(self, inter):
if(self._getNature(inter) & self._nature):
return True
return False
class pyHigherNumberOfTurnsUP1D(UnaryPredicate1D):
def __init__(self,n,a):
UnaryPredicate1D.__init__(self)
self._n = n
self._a = a
def __call__(self, inter):
count = 0
func = Curvature2DAngleF0D()
it = inter.vertices_begin()
while not it.is_end:
if func(it) > self._a:
count = count+1
if count > self._n:
return True
it.increment()
return False
class pyDensityUP1D(UnaryPredicate1D):
def __init__(self,wsize,threshold, integration = IntegrationType.MEAN, sampling=2.0):
UnaryPredicate1D.__init__(self)
self._wsize = wsize
self._threshold = threshold
self._integration = integration
self._func = DensityF1D(self._wsize, self._integration, sampling)
def __call__(self, inter):
return (self._func(inter) < self._threshold)
class pyLowSteerableViewMapDensityUP1D(UnaryPredicate1D):
def __init__(self,threshold, level,integration = IntegrationType.MEAN):
UnaryPredicate1D.__init__(self)
self._threshold = threshold
self._level = level
self._integration = integration
def __call__(self, inter):
func = GetSteerableViewMapDensityF1D(self._level, self._integration)
return (func(inter) < self._threshold)
class pyLowDirectionalViewMapDensityUP1D(UnaryPredicate1D):
def __init__(self,threshold, orientation, level,integration = IntegrationType.MEAN):
UnaryPredicate1D.__init__(self)
self._threshold = threshold
self._orientation = orientation
self._level = level
self._integration = integration
def __call__(self, inter):
func = GetDirectionalViewMapDensityF1D(self._orientation, self._level, self._integration)
return (func(inter) < self._threshold)
class pyHighSteerableViewMapDensityUP1D(UnaryPredicate1D):
def __init__(self,threshold, level,integration = IntegrationType.MEAN):
UnaryPredicate1D.__init__(self)
self._threshold = threshold
self._level = level
self._integration = integration
self._func = GetSteerableViewMapDensityF1D(self._level, self._integration)
def __call__(self, inter):
return (self._func(inter) > self._threshold)
class pyHighDirectionalViewMapDensityUP1D(UnaryPredicate1D):
def __init__(self,threshold, orientation, level,integration = IntegrationType.MEAN, sampling=2.0):
UnaryPredicate1D.__init__(self)
self._threshold = threshold
self._orientation = orientation
self._level = level
self._integration = integration
self._sampling = sampling
def __call__(self, inter):
func = GetDirectionalViewMapDensityF1D(self._orientation, self._level, self._integration, self._sampling)
return (func(inter) > self._threshold)
class pyHighViewMapDensityUP1D(UnaryPredicate1D):
def __init__(self,threshold, level,integration = IntegrationType.MEAN, sampling=2.0):
UnaryPredicate1D.__init__(self)
self._threshold = threshold
self._level = level
self._integration = integration
self._sampling = sampling
self._func = GetCompleteViewMapDensityF1D(self._level, self._integration, self._sampling) # 2.0 is the smpling
def __call__(self, inter):
return (self._func(inter) > self._threshold)
class pyDensityFunctorUP1D(UnaryPredicate1D):
def __init__(self,wsize,threshold, functor, funcmin=0.0, funcmax=1.0, integration = IntegrationType.MEAN):
UnaryPredicate1D.__init__(self)
self._wsize = wsize
self._threshold = float(threshold)
self._functor = functor
self._funcmin = float(funcmin)
self._funcmax = float(funcmax)
self._integration = integration
def __call__(self, inter):
func = DensityF1D(self._wsize, self._integration)
res = self._functor(inter)
k = (res-self._funcmin)/(self._funcmax-self._funcmin)
return (func(inter) < (self._threshold * k))
class pyZSmallerUP1D(UnaryPredicate1D):
def __init__(self,z, integration=IntegrationType.MEAN):
UnaryPredicate1D.__init__(self)
self._z = z
self._integration = integration
def __call__(self, inter):
func = GetProjectedZF1D(self._integration)
return (func(inter) < self._z)
class pyIsOccludedByUP1D(UnaryPredicate1D):
def __init__(self,id):
UnaryPredicate1D.__init__(self)
self._id = id
def __call__(self, inter):
func = GetShapeF1D()
shapes = func(inter)
for s in shapes:
if(s.id == self._id):
return False
it = inter.vertices_begin()
itlast = inter.vertices_end()
itlast.decrement()
v = it.object
vlast = itlast.object
tvertex = v.viewvertex
if type(tvertex) is TVertex:
#print("TVertex: [ ", tvertex.id.first, ",", tvertex.id.second," ]")
eit = tvertex.edges_begin()
while not eit.is_end:
ve, incoming = eit.object
if ve.id == self._id:
return True
#print("-------", ve.id.first, "-", ve.id.second)
eit.increment()
tvertex = vlast.viewvertex
if type(tvertex) is TVertex:
#print("TVertex: [ ", tvertex.id.first, ",", tvertex.id.second," ]")
eit = tvertex.edges_begin()
while not eit.is_end:
ve, incoming = eit.object
if ve.id == self._id:
return True
#print("-------", ve.id.first, "-", ve.id.second)
eit.increment()
return False
class pyIsInOccludersListUP1D(UnaryPredicate1D):
def __init__(self,id):
UnaryPredicate1D.__init__(self)
self._id = id
def __call__(self, inter):
func = GetOccludersF1D()
occluders = func(inter)
for a in occluders:
if a.id == self._id:
return True
return False
class pyIsOccludedByItselfUP1D(UnaryPredicate1D):
def __init__(self):
UnaryPredicate1D.__init__(self)
self.__func1 = GetOccludersF1D()
self.__func2 = GetShapeF1D()
def __call__(self, inter):
lst1 = self.__func1(inter)
lst2 = self.__func2(inter)
for vs1 in lst1:
for vs2 in lst2:
if vs1.id == vs2.id:
return True
return False
class pyIsOccludedByIdListUP1D(UnaryPredicate1D):
def __init__(self, idlist):
UnaryPredicate1D.__init__(self)
self._idlist = idlist
self.__func1 = GetOccludersF1D()
def __call__(self, inter):
lst1 = self.__func1(inter)
for vs1 in lst1:
for _id in self._idlist:
if vs1.id == _id:
return True
return False
class pyShapeIdListUP1D(UnaryPredicate1D):
def __init__(self,idlist):
UnaryPredicate1D.__init__(self)
self._idlist = idlist
self._funcs = []
for _id in idlist :
self._funcs.append(ShapeUP1D(_id.first, _id.second))
def __call__(self, inter):
for func in self._funcs:
if func(inter) == 1:
return True
return False
## deprecated
class pyShapeIdUP1D(UnaryPredicate1D):
def __init__(self, _id):
UnaryPredicate1D.__init__(self)
self._id = _id
def __call__(self, inter):
func = GetShapeF1D()
shapes = func(inter)
for a in shapes:
if a.id == self._id:
return True
return False
class pyHighDensityAnisotropyUP1D(UnaryPredicate1D):
def __init__(self,threshold, level, sampling=2.0):
UnaryPredicate1D.__init__(self)
self._l = threshold
self.func = pyDensityAnisotropyF1D(level, IntegrationType.MEAN, sampling)
def __call__(self, inter):
return (self.func(inter) > self._l)
class pyHighViewMapGradientNormUP1D(UnaryPredicate1D):
def __init__(self,threshold, l, sampling=2.0):
UnaryPredicate1D.__init__(self)
self._threshold = threshold
self._GetGradient = pyViewMapGradientNormF1D(l, IntegrationType.MEAN)
def __call__(self, inter):
gn = self._GetGradient(inter)
#print(gn)
return (gn > self._threshold)
class pyDensityVariableSigmaUP1D(UnaryPredicate1D):
def __init__(self,functor, sigmaMin,sigmaMax, lmin, lmax, tmin, tmax, integration = IntegrationType.MEAN, sampling=2.0):
UnaryPredicate1D.__init__(self)
self._functor = functor
self._sigmaMin = float(sigmaMin)
self._sigmaMax = float(sigmaMax)
self._lmin = float(lmin)
self._lmax = float(lmax)
self._tmin = tmin
self._tmax = tmax
self._integration = integration
self._sampling = sampling
def __call__(self, inter):
sigma = (self._sigmaMax-self._sigmaMin)/(self._lmax-self._lmin)*(self._functor(inter)-self._lmin) + self._sigmaMin
t = (self._tmax-self._tmin)/(self._lmax-self._lmin)*(self._functor(inter)-self._lmin) + self._tmin
sigma = max(sigma, self._sigmaMin)
self._func = DensityF1D(sigma, self._integration, self._sampling)
return (self._func(inter) < t)
class pyClosedCurveUP1D(UnaryPredicate1D):
def __call__(self, inter):
it = inter.vertices_begin()
itlast = inter.vertices_end()
itlast.decrement()
vlast = itlast.object
v = it.object
#print(v.id.first, v.id.second)
#print(vlast.id.first, vlast.id.second)
if v.id == vlast.id:
return True
return False
## Binary predicates for 1D elements (curves)
#############################################
class pyZBP1D(BinaryPredicate1D):
def __call__(self, i1, i2):
func = GetZF1D()
return (func(i1) > func(i2))
class pyZDiscontinuityBP1D(BinaryPredicate1D):
def __init__(self, iType = IntegrationType.MEAN):
BinaryPredicate1D.__init__(self)
self._GetZDiscontinuity = ZDiscontinuityF1D(iType)
def __call__(self, i1, i2):
return (self._GetZDiscontinuity(i1) > self._GetZDiscontinuity(i2))
class pyLengthBP1D(BinaryPredicate1D):
def __call__(self, i1, i2):
return (i1.length_2d > i2.length_2d)
class pySilhouetteFirstBP1D(BinaryPredicate1D):
def __call__(self, inter1, inter2):
bpred = SameShapeIdBP1D()
if (bpred(inter1, inter2) != 1):
return False
if (inter1.nature & Nature.SILHOUETTE):
return (inter2.nature & Nature.SILHOUETTE) != 0
return (inter1.nature == inter2.nature)
class pyNatureBP1D(BinaryPredicate1D):
def __call__(self, inter1, inter2):
return (inter1.nature & inter2.nature)
class pyViewMapGradientNormBP1D(BinaryPredicate1D):
def __init__(self,l, sampling=2.0):
BinaryPredicate1D.__init__(self)
self._GetGradient = pyViewMapGradientNormF1D(l, IntegrationType.MEAN)
def __call__(self, i1,i2):
#print("compare gradient")
return (self._GetGradient(i1) > self._GetGradient(i2))
class pyShuffleBP1D(BinaryPredicate1D):
def __init__(self):
BinaryPredicate1D.__init__(self)
random.seed(1)
def __call__(self, inter1, inter2):
r1 = random.uniform(0,1)
r2 = random.uniform(0,1)
return (r1<r2)