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# -*- coding: utf-8 -*-
# main
cimport pcl_defs as cpp
import numpy as np
cimport numpy as cnp
cnp.import_array()
# parts
cimport pcl_features as pclftr
cimport pcl_filters as pclfil
cimport pcl_io as pclio
cimport pcl_kdtree as pclkdt
cimport pcl_octree as pcloct
cimport pcl_sample_consensus as pcl_sc
# cimport pcl_search as pcl_sch
cimport pcl_segmentation as pclseg
cimport pcl_surface as pclsf
cimport pcl_range_image as pcl_r_img
from libcpp cimport bool
cimport indexing as idx
from boost_shared_ptr cimport sp_assign
cdef extern from "minipcl.h":
void mpcl_compute_normals(cpp.PointCloud_t, int ksearch,
double searchRadius,
cpp.PointCloud_Normal_t) except +
void mpcl_extract(cpp.PointCloudPtr_t, cpp.PointCloud_t *,
cpp.PointIndices_t *, bool) except +
## void mpcl_extract_HarrisKeypoint3D(cpp.PointCloudPtr_t, cpp.PointCloud_ReferenceFrame *) except +
# void mpcl_extract_HarrisKeypoint3D(cpp.PointCloudPtr_t, cpp.PointCloud_t *) except +
cdef extern from "ProjectInliers.h":
void mpcl_ProjectInliers_setModelCoefficients(pclfil.ProjectInliers_t) except +
# Empirically determine strides, for buffer support.
# XXX Is there a more elegant way to get these?
cdef Py_ssize_t _strides[2]
cdef PointCloud _pc_tmp = PointCloud(np.array([[1, 2, 3],
[4, 5, 6]], dtype=np.float32))
cdef cpp.PointCloud[cpp.ReferenceFrame] *p = _pc_tmp.thisptr()
_strides[0] = ( <Py_ssize_t><void *>idx.getptr(p, 1)
- <Py_ssize_t><void *>idx.getptr(p, 0))
_strides[1] = ( <Py_ssize_t><void *>&(idx.getptr(p, 0).y)
- <Py_ssize_t><void *>&(idx.getptr(p, 0).x))
_pc_tmp = None
cdef class PointCloud_ReferenceFrame:
"""Represents a cloud of points in 3-d space.
A point cloud can be initialized from either a NumPy ndarray of shape
(n_points, 3), from a list of triples, or from an integer n to create an
"empty" cloud of n points.
To load a point cloud from disk, use pcl.load.
"""
def __cinit__(self, init=None):
cdef PointCloud other
self._view_count = 0
# TODO: NG --> import pcl --> pyd Error(python shapedptr/C++ shard ptr collusion?)
# sp_assign(<cpp.shared_ptr[cpp.PointCloud[cpp.ReferenceFrame]]> self.thisptr_shared, new cpp.PointCloud[cpp.ReferenceFrame]())
sp_assign(self.thisptr_shared, new cpp.PointCloud[cpp.ReferenceFrame]())
if init is None:
return
elif isinstance(init, (numbers.Integral, np.integer)):
self.resize(init)
elif isinstance(init, np.ndarray):
self.from_array(init)
elif isinstance(init, Sequence):
self.from_list(init)
elif isinstance(init, type(self)):
other = init
self.thisptr()[0] = other.thisptr()[0]
else:
raise TypeError("Can't initialize a PointCloud from a %s"
% type(init))
property width:
""" property containing the width of the point cloud """
def __get__(self): return self.thisptr().width
property height:
""" property containing the height of the point cloud """
def __get__(self): return self.thisptr().height
property size:
""" property containing the number of points in the point cloud """
def __get__(self): return self.thisptr().size()
property is_dense:
""" property containing whether the cloud is dense or not """
def __get__(self): return self.thisptr().is_dense
def __repr__(self):
return "<PointCloud of %d points>" % self.size
# Buffer protocol support. Taking a view locks the pointcloud for
# resizing, because that can move it around in memory.
def __getbuffer__(self, Py_buffer *buffer, int flags):
# TODO parse flags
cdef Py_ssize_t npoints = self.thisptr().size()
if self._view_count == 0:
self._shape[0] = npoints
self._shape[1] = 3
self._view_count += 1
buffer.buf = <char *>&(idx.getptr_at(self.thisptr(), 0).x)
buffer.format = 'f'
buffer.internal = NULL
buffer.itemsize = sizeof(float)
buffer.len = npoints * 3 * sizeof(float)
buffer.ndim = 2
buffer.obj = self
buffer.readonly = 0
buffer.shape = self._shape
buffer.strides = _strides
buffer.suboffsets = NULL
def __releasebuffer__(self, Py_buffer *buffer):
self._view_count -= 1
# Pickle support. XXX this copies the entire pointcloud; it would be nice
# to have an asarray member that returns a view, or even better, implement
# the buffer protocol (https://docs.python.org/c-api/buffer.html).
def __reduce__(self):
return type(self), (self.to_array(),)
property sensor_origin:
def __get__(self):
cdef cpp.Vector4f origin = self.thisptr().sensor_origin_
cdef float *data = origin.data()
return np.array([data[0], data[1], data[2], data[3]],
dtype=np.float32)
property sensor_orientation:
def __get__(self):
# NumPy doesn't have a quaternion type, so we return a 4-vector.
cdef cpp.Quaternionf o = self.thisptr().sensor_orientation_
return np.array([o.w(), o.x(), o.y(), o.z()])
# cdef inline PointCloud[ReferenceFrame] *thisptr(self) nogil:
# # Shortcut to get raw pointer to underlying PointCloud
# return self.thisptr_shared.get()
@cython.boundscheck(False)
def from_array(self, cnp.ndarray[cnp.float32_t, ndim=2] arr not None):
"""
Fill this object from a 2D numpy array (float32)
"""
assert arr.shape[1] == 3
cdef cnp.npy_intp npts = arr.shape[0]
self.resize(npts)
self.thisptr().width = npts
self.thisptr().height = 1
cdef cpp.ReferenceFrame *p
for i in range(npts):
p = idx.getptr(self.thisptr(), i)
p.x, p.y, p.z = arr[i, 0], arr[i, 1], arr[i, 2]
@cython.boundscheck(False)
def to_array(self):
"""
Return this object as a 2D numpy array (float32)
"""
cdef float x,y,z
cdef cnp.npy_intp n = self.thisptr().size()
cdef cnp.ndarray[cnp.float32_t, ndim=2, mode="c"] result
cdef cpp.ReferenceFrame *p
result = np.empty((n, 3), dtype=np.float32)
for i in range(n):
p = idx.getptr(self.thisptr(), i)
result[i, 0] = p.x
result[i, 1] = p.y
result[i, 2] = p.z
return result
def from_list(self, _list):
"""
Fill this pointcloud from a list of 3-tuples
"""
cdef Py_ssize_t npts = len(_list)
self.resize(npts)
self.thisptr().width = npts
self.thisptr().height = 1
cdef cpp.ReferenceFrame* p
# OK
# p = idx.getptr(self.thisptr(), 1)
# enumerate ? -> i -> type unknown
for i, l in enumerate(_list):
p = idx.getptr(self.thisptr(), <int> i)
p.x, p.y, p.z = l
def to_list(self):
"""
Return this object as a list of 3-tuples
"""
return self.to_array().tolist()
def resize(self, cnp.npy_intp x):
if self._view_count > 0:
raise ValueError("can't resize PointCloud while there are"
" arrays/memoryviews referencing it")
self.thisptr().resize(x)
def get_point(self, cnp.npy_intp row, cnp.npy_intp col):
"""
Return a point (3-tuple) at the given row/column
"""
cdef cpp.ReferenceFrame *p = idx.getptr_at2(self.thisptr(), row, col)
return p.x, p.y, p.z
def __getitem__(self, cnp.npy_intp nmidx):
cdef cpp.ReferenceFrame *p = idx.getptr_at(self.thisptr(), nmidx)
return p.x, p.y, p.z
def from_file(self, char *f):
"""
Fill this pointcloud from a file (a local path).
Only pcd files supported currently.
Deprecated; use pcl.load instead.
"""
return self._from_pcd_file(f)
def _from_pcd_file(self, const char *s):
cdef int error = 0
with nogil:
# NG
# error = pclio.loadPCDFile(string(s), <cpp.PointCloud[cpp.ReferenceFrame]> deref(self.thisptr()))
error = pclio.loadPCDFile(string(s), deref(self.thisptr()))
return error
def _from_ply_file(self, const char *s):
cdef int ok = 0
with nogil:
# NG
# ok = pclio.loadPLYFile(string(s), <cpp.PointCloud[cpp.ReferenceFrame]> deref(self.thisptr()))
ok = pclio.loadPLYFile(string(s), deref(self.thisptr()))
return ok
def to_file(self, const char *fname, bool ascii=True):
"""Save pointcloud to a file in PCD format.
Deprecated: use pcl.save instead.
"""
return self._to_pcd_file(fname, not ascii)
def _to_pcd_file(self, const char *f, bool binary=False):
cdef int error = 0
cdef string s = string(f)
with nogil:
# NG
# error = pclio.savePCDFile(s, <cpp.PointCloud[cpp.ReferenceFrame]> deref(self.thisptr()), binary)
# OK
error = pclio.savePCDFile(s, deref(self.thisptr()), binary)
# pclio.PointCloud[cpp.ReferenceFrame] *p = self.thisptr()
# error = pclio.savePCDFile(s, p, binary)
return error
def _to_ply_file(self, const char *f, bool binary=False):
cdef int error = 0
cdef string s = string(f)
with nogil:
# NG
# error = pclio.savePLYFile(s, <cpp.PointCloud[cpp.ReferenceFrame]> deref(self.thisptr()), binary)
error = pclio.savePLYFile(s, deref(self.thisptr()), binary)
return error
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