# -*- coding: utf-8 -*-
# Created on Thu Mar 24 13:51:50 2022
# @author: toj
"""
Objects
=======
.. autosummary::
:toctree: generated/
.. currentmodule:: mymesh.mesh
mesh
.. currentmodule:: mymesh
Submodules
==========
.. autosummary::
:toctree: generated/
booleans
contour
converter
curvature
delaunay
image
implicit
improvement
tree
primitives
quality
rays
register
utils
visualize
Functions
=========
.. autosummary::
:toctree: generated/
demo_mesh
demo_image
"""
from functools import wraps
import warnings, urllib, tarfile, io, re
import numpy as np
try:
from numba import njit
_MYMESH_USE_NUMBA = True
except ImportError:
njit = None
_MYMESH_USE_NUMBA = False
def use_numba(enabled=True):
global _MYMESH_USE_NUMBA
if njit is None:
warnings.warn('numba is not available for import. Install with `conda install numba` or `pip install numba`.')
_MYMESH_USE_NUMBA = enabled and (njit is not None)
def check_numba():
global _MYMESH_USE_NUMBA
if _MYMESH_USE_NUMBA and (njit is not None):
check = True
else:
check = False
return check
def try_njit(func=None, *njit_args, **njit_kwargs):
@wraps(func)
def decorator(func):
if check_numba():
jit_func = njit(*njit_args, **njit_kwargs)(func)
else:
jit_func = func
return jit_func
return decorator(func) if func else decorator
[docs]
def demo_image(name='bunny', normalize=True):
"""
Example image data from online databases
Since data is obtained on-demand from online sources, internet connectivity
is required.
Parameters
----------
name : str, optional
Name of the image to access, by default 'bunny'.
Available options are:
- "bunny" - CT scan of the Stanford Bunny from the Stanford volume data archive
normalize : bool, optional
Normalize image data to the range 0-255 in uint8 format, by default True
Returns
-------
img : np.ndarray
Image array
"""
if name == 'bunny':
# CT scan of "Stanford Bunny" from the Stanford volume data archive
# https://graphics.stanford.edu/data/voldata/voldata.html
url = 'https://graphics.stanford.edu/data/voldata/bunny-ctscan.tar.gz'
# Get data and extract archive
response = urllib.request.urlopen(url)
tar_bytes = response.read()
tar_file = tarfile.open(fileobj=io.BytesIO(tar_bytes), mode="r:gz")
# Parse file names
file_names = np.array([name for name in tar_file.getnames() if re.match('bunny/[0-9]', name)], dtype=object)
file_numbers = [int(name.split('/')[1]) for name in file_names]
file_names = file_names[np.argsort(file_numbers)]
# Load image data - "The data is raw 512x512 slices, unsigned, 12 bit data stored as 16bit (2-byte) pixels."
# Binary data stored in big-endian ">u2" format
img = np.array([np.frombuffer(tar_file.extractfile(file).read(),dtype='>u2').reshape((512,512)) for file in file_names])
img[img == np.max(img)] = 0 # Set the outer boundary to 0 ("black")
else:
raise ValueError(f'Unknown image option: {name:s}')
if normalize:
# normalize the image to 0-255, unit8
img = (img/np.max(img)*255).astype(dtype=np.uint8)
return img
[docs]
def demo_mesh(name='bunny'):
"""
Example mesh models from online databases
Since data is obtained on-demand from online sources, internet connectivity
is required.
The Stanford models (bunny, dragon, Lucy) are obtained from the
`Stanford Computer Graphics Library <https://graphics.stanford.edu/data/3Dscanrep/>`__.
The following notices from the library's website apply to these models:
Please be sure to acknowledge the source of the data and models you take
from this repository. In each of the listings below, we have cited the
source of the range data and reconstructed models. You are welcome to
use the data and models for research purposes. You are also welcome to
mirror or redistribute them for free. Finally, you may publish images
made using these models, or the images on this web site, in a scholarly
article or book - as long as credit is given to the Stanford Computer
Graphics Laboratory. However, such models or images are not to be used
for commercial purposes, nor should they appear in a product for sale
(with the exception of scholarly journals or books), without our
permission.
As you browse this repository and think about how you might use our 3D
models and range datasets, please remember that several of these
artifacts have religious or cultural significance. Aside from the buddha,
which is a religious symbol revered by hundreds of millions of people,
the dragon is a symbol of Chinese culture, the Thai statue contains
elements of religious significance to Hindus, and Lucy is a Christian
angel; statues like her are commonly seen in Italian churches. Keep your
renderings and other uses of these particular models in good taste.
Don't animate or morph them, don't apply Boolean operators to them, and
don't simulate nasty things happening to them (like breaking, exploding,
melting, etc.). Choose another model for these sorts of experiments.
(You can do anything you want to the Stanford bunny or the armadillo.)
Parameters
----------
name : str, optional
Name of the image to access, by default 'bunny'.
Available options are:
- "bunny" - Stanford Bunny from the Stanford 3D Scanning Repository.
- Coarser versions of the model are available as "bunny_res2", "bunny_res3", "bunny_res4"
- This is a non-manifold surface, the mesh has several holes on the bottom
- "dragon" - Stanford Dragon from the Stanford 3D Scanning Repository
- Coarser versions of the model are available as "dragon_res2", "dragon_res3", "dragon_res4"
- This is a non-manifold surface, the mesh has numerous small holes
- "Lucy" - "Angel of Light" statue from the Stanford 3D Scanning Repository
- This surface is hole free but has some topological defects/bridging
Returns
-------
M : mymesh.mesh
Mesh object
Examples
--------
.. code-block:: python
import mymesh
bunny = mymesh.demo_mesh("bunny")
bunny.plot(view='xy')
.. code-block:: python
import mymesh
dragon = mymesh.demo_mesh("dragon")
dragon.plot(view='xy')
.. code-block:: python
import mymesh
lucy = mymesh.demo_mesh("Lucy")
lucy.plot(view='-xz')
"""
try:
import meshio
except:
raise ImportError('meshio library is required to load demo meshes. Install with: pip install meshio')
if 'bunny' in name:
# "Stanford Bunny" from the Stanford 3D Scanning Repository
# https://graphics.stanford.edu/data/3Dscanrep/
url = 'https://graphics.stanford.edu/pub/3Dscanrep/bunny.tar.gz'
# Get data and extract archive
response = urllib.request.urlopen(url)
tar_bytes = response.read()
tar_file = tarfile.open(fileobj=io.BytesIO(tar_bytes), mode="r:gz")
if 'res2' in name:
f = tar_file.extractfile('bunny/reconstruction/bun_zipper_res2.ply')
elif 'res3' in name:
f = tar_file.extractfile('bunny/reconstruction/bun_zipper_res3.ply')
elif 'res4' in name:
f = tar_file.extractfile('bunny/reconstruction/bun_zipper_res4.ply')
else:
f = tar_file.extractfile('bunny/reconstruction/bun_zipper.ply')
m = meshio.ply._ply.read_buffer(f)
M = mesh.meshio2mymesh(m)
elif 'dragon' in name:
# "Stanford Dragon" from the Stanford 3D Scanning Repository
# https://graphics.stanford.edu/data/3Dscanrep/
url = 'https://graphics.stanford.edu/pub/3Dscanrep/dragon/dragon_recon.tar.gz'
# Get data and extract archive
response = urllib.request.urlopen(url)
tar_bytes = response.read()
tar_file = tarfile.open(fileobj=io.BytesIO(tar_bytes), mode="r:gz")
if 'res2' in name:
f = tar_file.extractfile('dragon_recon/dragon_vrip_res2.ply')
elif 'res3' in name:
f = tar_file.extractfile('dragon_recon/dragon_vrip_res3.ply')
elif 'res4' in name:
f = tar_file.extractfile('dragon_recon/dragon_vrip_res4.ply')
else:
f = tar_file.extractfile('dragon_recon/dragon_vrip.ply')
m = meshio.ply._ply.read_buffer(f)
M = mesh.meshio2mymesh(m)
elif 'Lucy' in name:
# Lucy statue from the Stanford 3D Scanning Repository
# https://graphics.stanford.edu/data/3Dscanrep/
url = 'https://graphics.stanford.edu/data/3Dscanrep/lucy.tar.gz'
# Get data and extract archive
response = urllib.request.urlopen(url)
tar_bytes = response.read()
tar_file = tarfile.open(fileobj=io.BytesIO(tar_bytes), mode="r:gz")
f = tar_file.extractfile('lucy.ply')
m = meshio.ply._ply.read_buffer(f)
M = mesh.meshio2mymesh(m)
else:
raise ValueError(f'Unknown image option: {name:s}')
return M
from .mesh import mesh
from . import booleans, contour, converter, curvature, delaunay, image, implicit, improvement, primitives, quality, rays, register, tree, utils, visualize
__all__ = ["check_numba", "use_numba", "try_njit", "mesh", "booleans", "contour", "converter",
"curvature", "delaunay", "image", "implicit", "improvement",
"primitives", "quality", "rays", "register", "tree", "utils", "visualize"]
