443 lines
14 KiB
Python
443 lines
14 KiB
Python
"""Data structures to hold collections of images, with optional caching."""
|
|
|
|
|
|
import os
|
|
from glob import glob
|
|
import re
|
|
from collections.abc import Sequence
|
|
from copy import copy
|
|
|
|
import numpy as np
|
|
from PIL import Image
|
|
|
|
from tifffile import TiffFile
|
|
|
|
|
|
__all__ = ['MultiImage', 'ImageCollection', 'concatenate_images',
|
|
'imread_collection_wrapper']
|
|
|
|
|
|
def concatenate_images(ic):
|
|
"""Concatenate all images in the image collection into an array.
|
|
|
|
Parameters
|
|
----------
|
|
ic : an iterable of images
|
|
The images to be concatenated.
|
|
|
|
Returns
|
|
-------
|
|
array_cat : ndarray
|
|
An array having one more dimension than the images in `ic`.
|
|
|
|
See Also
|
|
--------
|
|
ImageCollection.concatenate, MultiImage.concatenate
|
|
|
|
Raises
|
|
------
|
|
ValueError
|
|
If images in `ic` don't have identical shapes.
|
|
|
|
Notes
|
|
-----
|
|
``concatenate_images`` receives any iterable object containing images,
|
|
including ImageCollection and MultiImage, and returns a NumPy array.
|
|
"""
|
|
all_images = [image[np.newaxis, ...] for image in ic]
|
|
try:
|
|
array_cat = np.concatenate(all_images)
|
|
except ValueError:
|
|
raise ValueError('Image dimensions must agree.')
|
|
return array_cat
|
|
|
|
|
|
def alphanumeric_key(s):
|
|
"""Convert string to list of strings and ints that gives intuitive sorting.
|
|
|
|
Parameters
|
|
----------
|
|
s : string
|
|
|
|
Returns
|
|
-------
|
|
k : a list of strings and ints
|
|
|
|
Examples
|
|
--------
|
|
>>> alphanumeric_key('z23a')
|
|
['z', 23, 'a']
|
|
>>> filenames = ['f9.10.png', 'e10.png', 'f9.9.png', 'f10.10.png',
|
|
... 'f10.9.png']
|
|
>>> sorted(filenames)
|
|
['e10.png', 'f10.10.png', 'f10.9.png', 'f9.10.png', 'f9.9.png']
|
|
>>> sorted(filenames, key=alphanumeric_key)
|
|
['e10.png', 'f9.9.png', 'f9.10.png', 'f10.9.png', 'f10.10.png']
|
|
"""
|
|
k = [int(c) if c.isdigit() else c for c in re.split('([0-9]+)', s)]
|
|
return k
|
|
|
|
|
|
def _is_multipattern(input_pattern):
|
|
"""Helping function. Returns True if pattern contains a tuple, list, or a
|
|
string separated with os.pathsep."""
|
|
# Conditions to be accepted by ImageCollection:
|
|
has_str_ospathsep = (isinstance(input_pattern, str)
|
|
and os.pathsep in input_pattern)
|
|
not_a_string = not isinstance(input_pattern, str)
|
|
has_iterable = isinstance(input_pattern, Sequence)
|
|
has_strings = all(isinstance(pat, str) for pat in input_pattern)
|
|
|
|
is_multipattern = (has_str_ospathsep or
|
|
(not_a_string
|
|
and has_iterable
|
|
and has_strings))
|
|
return is_multipattern
|
|
|
|
|
|
class ImageCollection(object):
|
|
"""Load and manage a collection of image files.
|
|
|
|
Parameters
|
|
----------
|
|
load_pattern : str or list of str
|
|
Pattern string or list of strings to load. The filename path can be
|
|
absolute or relative.
|
|
conserve_memory : bool, optional
|
|
If True, `ImageCollection` does not keep more than one in memory at a
|
|
specific time. Otherwise, images will be cached once they are loaded.
|
|
|
|
Other parameters
|
|
----------------
|
|
load_func : callable
|
|
``imread`` by default. See notes below.
|
|
|
|
Attributes
|
|
----------
|
|
files : list of str
|
|
If a pattern string is given for `load_pattern`, this attribute
|
|
stores the expanded file list. Otherwise, this is equal to
|
|
`load_pattern`.
|
|
|
|
Notes
|
|
-----
|
|
Note that files are always returned in alphanumerical order. Also note
|
|
that slicing returns a new ImageCollection, *not* a view into the data.
|
|
|
|
ImageCollection can be modified to load images from an arbitrary
|
|
source by specifying a combination of `load_pattern` and
|
|
`load_func`. For an ImageCollection ``ic``, ``ic[5]`` uses
|
|
``load_func(file_pattern[5])`` to load the image.
|
|
|
|
Imagine, for example, an ImageCollection that loads every tenth
|
|
frame from a video file::
|
|
|
|
class AVILoader:
|
|
video_file = 'myvideo.avi'
|
|
|
|
def __call__(self, frame):
|
|
return video_read(self.video_file, frame)
|
|
|
|
avi_load = AVILoader()
|
|
|
|
frames = range(0, 1000, 10) # 0, 10, 20, ...
|
|
ic = ImageCollection(frames, load_func=avi_load)
|
|
|
|
x = ic[5] # calls avi_load(frames[5]) or equivalently avi_load(50)
|
|
|
|
Another use of ``load_func`` would be to convert all images to ``uint8``::
|
|
|
|
def imread_convert(f):
|
|
return imread(f).astype(np.uint8)
|
|
|
|
ic = ImageCollection('/tmp/*.png', load_func=imread_convert)
|
|
|
|
For files with multiple images, the images will be flattened into a list
|
|
and added to the list of available images. In this case, ``load_func``
|
|
should accept the keyword argument ``img_num``.
|
|
|
|
Examples
|
|
--------
|
|
>>> import skimage.io as io
|
|
>>> from skimage import data_dir
|
|
|
|
>>> coll = io.ImageCollection(data_dir + '/chess*.png')
|
|
>>> len(coll)
|
|
2
|
|
>>> coll[0].shape
|
|
(200, 200)
|
|
|
|
>>> ic = io.ImageCollection(['/tmp/work/*.png', '/tmp/other/*.jpg'])
|
|
"""
|
|
def __init__(self, load_pattern, conserve_memory=True, load_func=None,
|
|
**load_func_kwargs):
|
|
"""Load and manage a collection of images."""
|
|
self._files = []
|
|
if _is_multipattern(load_pattern):
|
|
if isinstance(load_pattern, str):
|
|
load_pattern = load_pattern.split(os.pathsep)
|
|
for pattern in load_pattern:
|
|
self._files.extend(glob(pattern))
|
|
self._files = sorted(self._files, key=alphanumeric_key)
|
|
self._numframes = self._find_images()
|
|
elif isinstance(load_pattern, str):
|
|
self._files.extend(glob(load_pattern))
|
|
self._files = sorted(self._files, key=alphanumeric_key)
|
|
self._numframes = self._find_images()
|
|
else:
|
|
raise TypeError('Invalid pattern as input.')
|
|
|
|
if conserve_memory:
|
|
memory_slots = 1
|
|
else:
|
|
memory_slots = self._numframes
|
|
|
|
self._conserve_memory = conserve_memory
|
|
self._cached = None
|
|
|
|
if load_func is None:
|
|
from ._io import imread
|
|
self.load_func = imread
|
|
else:
|
|
self.load_func = load_func
|
|
|
|
self.load_func_kwargs = load_func_kwargs
|
|
self.data = np.empty(memory_slots, dtype=object)
|
|
|
|
@property
|
|
def files(self):
|
|
return self._files
|
|
|
|
@property
|
|
def conserve_memory(self):
|
|
return self._conserve_memory
|
|
|
|
def _find_images(self):
|
|
index = []
|
|
for fname in self._files:
|
|
if fname.lower().endswith(('.tiff', '.tif')):
|
|
with open(fname, 'rb') as f:
|
|
img = TiffFile(f)
|
|
index += [(fname, i) for i in range(len(img.pages))]
|
|
else:
|
|
try:
|
|
im = Image.open(fname)
|
|
im.seek(0)
|
|
except (IOError, OSError):
|
|
continue
|
|
i = 0
|
|
while True:
|
|
try:
|
|
im.seek(i)
|
|
except EOFError:
|
|
break
|
|
index.append((fname, i))
|
|
i += 1
|
|
if hasattr(im, 'fp') and im.fp:
|
|
im.fp.close()
|
|
self._frame_index = index
|
|
return len(index)
|
|
|
|
def __getitem__(self, n):
|
|
"""Return selected image(s) in the collection.
|
|
|
|
Loading is done on demand.
|
|
|
|
Parameters
|
|
----------
|
|
n : int or slice
|
|
The image number to be returned, or a slice selecting the images
|
|
and ordering to be returned in a new ImageCollection.
|
|
|
|
Returns
|
|
-------
|
|
img : ndarray or ImageCollection.
|
|
The `n`-th image in the collection, or a new ImageCollection with
|
|
the selected images.
|
|
"""
|
|
if hasattr(n, '__index__'):
|
|
n = n.__index__()
|
|
|
|
if type(n) not in [int, slice]:
|
|
raise TypeError('slicing must be with an int or slice object')
|
|
|
|
if type(n) is int:
|
|
n = self._check_imgnum(n)
|
|
idx = n % len(self.data)
|
|
|
|
if ((self.conserve_memory and n != self._cached) or
|
|
(self.data[idx] is None)):
|
|
kwargs = self.load_func_kwargs
|
|
if self._frame_index:
|
|
fname, img_num = self._frame_index[n]
|
|
if img_num is not None:
|
|
kwargs['img_num'] = img_num
|
|
try:
|
|
self.data[idx] = self.load_func(fname, **kwargs)
|
|
# Account for functions that do not accept an img_num kwarg
|
|
except TypeError as e:
|
|
if "unexpected keyword argument 'img_num'" in str(e):
|
|
del kwargs['img_num']
|
|
self.data[idx] = self.load_func(fname, **kwargs)
|
|
else:
|
|
raise
|
|
else:
|
|
self.data[idx] = self.load_func(self.files[n], **kwargs)
|
|
self._cached = n
|
|
|
|
return self.data[idx]
|
|
else:
|
|
# A slice object was provided, so create a new ImageCollection
|
|
# object. Any loaded image data in the original ImageCollection
|
|
# will be copied by reference to the new object. Image data
|
|
# loaded after this creation is not linked.
|
|
fidx = range(self._numframes)[n]
|
|
new_ic = copy(self)
|
|
|
|
if self._frame_index:
|
|
new_ic._files = [self._frame_index[i][0] for i in fidx]
|
|
new_ic._frame_index = [self._frame_index[i] for i in fidx]
|
|
else:
|
|
new_ic._files = [self._files[i] for i in fidx]
|
|
|
|
new_ic._numframes = len(fidx)
|
|
|
|
if self.conserve_memory:
|
|
if self._cached in fidx:
|
|
new_ic._cached = fidx.index(self._cached)
|
|
new_ic.data = np.copy(self.data)
|
|
else:
|
|
new_ic.data = np.empty(1, dtype=object)
|
|
else:
|
|
new_ic.data = self.data[fidx]
|
|
return new_ic
|
|
|
|
def _check_imgnum(self, n):
|
|
"""Check that the given image number is valid."""
|
|
num = self._numframes
|
|
if -num <= n < num:
|
|
n = n % num
|
|
else:
|
|
raise IndexError("There are only %s images in the collection"
|
|
% num)
|
|
return n
|
|
|
|
def __iter__(self):
|
|
"""Iterate over the images."""
|
|
for i in range(len(self)):
|
|
yield self[i]
|
|
|
|
def __len__(self):
|
|
"""Number of images in collection."""
|
|
return self._numframes
|
|
|
|
def __str__(self):
|
|
return str(self.files)
|
|
|
|
def reload(self, n=None):
|
|
"""Clear the image cache.
|
|
|
|
Parameters
|
|
----------
|
|
n : None or int
|
|
Clear the cache for this image only. By default, the
|
|
entire cache is erased.
|
|
|
|
"""
|
|
self.data = np.empty_like(self.data)
|
|
|
|
def concatenate(self):
|
|
"""Concatenate all images in the collection into an array.
|
|
|
|
Returns
|
|
-------
|
|
ar : np.ndarray
|
|
An array having one more dimension than the images in `self`.
|
|
|
|
See Also
|
|
--------
|
|
concatenate_images
|
|
|
|
Raises
|
|
------
|
|
ValueError
|
|
If images in the `ImageCollection` don't have identical shapes.
|
|
"""
|
|
return concatenate_images(self)
|
|
|
|
|
|
def imread_collection_wrapper(imread):
|
|
def imread_collection(load_pattern, conserve_memory=True):
|
|
"""Return an `ImageCollection` from files matching the given pattern.
|
|
|
|
Note that files are always stored in alphabetical order. Also note that
|
|
slicing returns a new ImageCollection, *not* a view into the data.
|
|
|
|
See `skimage.io.ImageCollection` for details.
|
|
|
|
Parameters
|
|
----------
|
|
load_pattern : str or list
|
|
Pattern glob or filenames to load. The path can be absolute or
|
|
relative. Multiple patterns should be separated by a colon,
|
|
e.g. '/tmp/work/*.png:/tmp/other/*.jpg'. Also see
|
|
implementation notes below.
|
|
conserve_memory : bool, optional
|
|
If True, never keep more than one in memory at a specific
|
|
time. Otherwise, images will be cached once they are loaded.
|
|
|
|
"""
|
|
return ImageCollection(load_pattern, conserve_memory=conserve_memory,
|
|
load_func=imread)
|
|
return imread_collection
|
|
|
|
|
|
class MultiImage(ImageCollection):
|
|
"""A class containing a single multi-frame image.
|
|
|
|
Parameters
|
|
----------
|
|
filename : str
|
|
The complete path to the image file.
|
|
conserve_memory : bool, optional
|
|
Whether to conserve memory by only caching a single frame. Default is
|
|
True.
|
|
|
|
Notes
|
|
-----
|
|
If ``conserve_memory=True`` the memory footprint can be reduced, however
|
|
the performance can be affected because frames have to be read from file
|
|
more often.
|
|
|
|
The last accessed frame is cached, all other frames will have to be read
|
|
from file.
|
|
|
|
The current implementation makes use of ``tifffile`` for Tiff files and
|
|
PIL otherwise.
|
|
|
|
Examples
|
|
--------
|
|
>>> from skimage import data_dir
|
|
|
|
>>> img = MultiImage(data_dir + '/multipage.tif') # doctest: +SKIP
|
|
>>> len(img) # doctest: +SKIP
|
|
2
|
|
>>> for frame in img: # doctest: +SKIP
|
|
... print(frame.shape) # doctest: +SKIP
|
|
(15, 10)
|
|
(15, 10)
|
|
|
|
"""
|
|
|
|
def __init__(self, filename, conserve_memory=True, dtype=None,
|
|
**imread_kwargs):
|
|
"""Load a multi-img."""
|
|
from ._io import imread
|
|
|
|
self._filename = filename
|
|
super(MultiImage, self).__init__(filename, conserve_memory,
|
|
load_func=imread, **imread_kwargs)
|
|
|
|
@property
|
|
def filename(self):
|
|
return self._filename
|