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# -*- coding: utf-8 -*-
cimport _pcl
from libcpp.vector cimport vector
from libcpp cimport bool
cimport pcl_defs as cpp
cimport pcl_features as pclftr
from boost_shared_ptr cimport sp_assign
cdef extern from "minipcl.h":
void mpcl_features_NormalEstimationMethod_AVERAGE_3D_GRADIENT(pclftr.IntegralImageNormalEstimation_t ) except +
void mpcl_features_NormalEstimationMethod_COVARIANCE_MATRIX(pclftr.IntegralImageNormalEstimation_t ) except +
void mpcl_features_NormalEstimationMethod_AVERAGE_DEPTH_CHANGE(pclftr.IntegralImageNormalEstimation_t ) except +
void mpcl_features_NormalEstimationMethod_SIMPLE_3D_GRADIENT(pclftr.IntegralImageNormalEstimation_t ) except +
void mpcl_features_NormalEstimationMethod_compute(pclftr.IntegralImageNormalEstimation_t, cpp.PointCloud_Normal_t ) except +
cdef class IntegralImageNormalEstimation:
"""
IntegralImageNormalEstimation class for Surface normal estimation on organized data using integral images.
"""
cdef pclftr.IntegralImageNormalEstimation_t *me
def __cinit__(self, _pcl.PointCloud pc not None):
# sp_assign(self.thisptr_shared, new pclftr.IntegralImageNormalEstimation[cpp.PointXYZ, cpp.Normal]())
# self.thisptr().setInputCloud(pc.thisptr_shared)
# NG : Reference Count
self.me = new pclftr.IntegralImageNormalEstimation_t()
self.me.setInputCloud(pc.thisptr_shared)
# pass
def __dealloc__(self):
del self.me
def set_NormalEstimation_Method_AVERAGE_3D_GRADIENT (self):
# mpcl_features_NormalEstimationMethod_AVERAGE_3D_GRADIENT(<pclftr.IntegralImageNormalEstimation_t> deref(self.thisptr()))
mpcl_features_NormalEstimationMethod_AVERAGE_3D_GRADIENT(<pclftr.IntegralImageNormalEstimation_t> deref(self.me))
def set_NormalEstimation_Method_COVARIANCE_MATRIX (self):
# mpcl_features_NormalEstimationMethod_COVARIANCE_MATRIX(<pclftr.IntegralImageNormalEstimation_t> deref(self.thisptr()))
mpcl_features_NormalEstimationMethod_COVARIANCE_MATRIX(<pclftr.IntegralImageNormalEstimation_t> deref(self.me))
def set_NormalEstimation_Method_AVERAGE_DEPTH_CHANGE (self):
# mpcl_features_NormalEstimationMethod_AVERAGE_DEPTH_CHANGE(<pclftr.IntegralImageNormalEstimation_t> deref(self.thisptr()))
mpcl_features_NormalEstimationMethod_AVERAGE_DEPTH_CHANGE(<pclftr.IntegralImageNormalEstimation_t> deref(self.me))
def set_NormalEstimation_Method_SIMPLE_3D_GRADIENT (self):
# mpcl_features_NormalEstimationMethod_SIMPLE_3D_GRADIENT(<pclftr.IntegralImageNormalEstimation_t> deref(self.thisptr()))
mpcl_features_NormalEstimationMethod_SIMPLE_3D_GRADIENT(<pclftr.IntegralImageNormalEstimation_t> deref(self.me))
# enum Set NG
# def set_NormalEstimation_Method (self):
# self.thisptr().setNormalEstimationMethod(pclftr.NormalEstimationMethod2.ESTIMATIONMETHOD_COVARIANCE_MATRIX)
def set_MaxDepthChange_Factor(self, double param):
# self.thisptr().setMaxDepthChangeFactor(param)
self.me.setMaxDepthChangeFactor(param)
def set_NormalSmoothingSize(self, double param):
# self.thisptr().setNormalSmoothingSize(param)
self.me.setNormalSmoothingSize(param)
def compute(self):
normal = PointCloud_Normal()
sp_assign(normal.thisptr_shared, new cpp.PointCloud[cpp.Normal]())
cdef cpp.PointCloud_Normal_t *cNormal = <cpp.PointCloud_Normal_t*>normal.thisptr()
# (<pclftr.Feature_t*>self.thisptr()).compute(deref(cNormal))
(<pclftr.Feature_t*>self.me).compute(deref(cNormal))
return normal
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