mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-29 09:06:25 +08:00
Andreas Mueller
308 lines
8.2 KiB
Python
308 lines
8.2 KiB
Python
"""Data structures to hold collections of images, with optional caching."""
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from __future__ import with_statement
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__all__ = ['MultiImage', 'ImageCollection', 'imread']
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from glob import glob
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import numpy as np
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from ._io import imread
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class MultiImage(object):
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"""A class containing a single multi-frame image.
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Parameters
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----------
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filename : str
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The complete path to the image file.
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conserve_memory : bool, optional
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Whether to conserve memory by only caching a single frame. Default is
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True.
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Notes
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-----
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If ``conserve_memory=True`` the memory footprint can be reduced, however
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the performance can be affected because frames have to be read from file
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more often.
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The last accessed frame is cached, all other frames will have to be read
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from file.
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The current implementation makes use of PIL.
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Examples
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--------
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>>> from skimage import data_dir
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>>> img = MultiImage(data_dir + '/multipage.tif')
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>>> len(img)
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2
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>>> for frame in img:
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... print frame.shape
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(15, 10)
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(15, 10)
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The two frames in this image can be shown with matplotlib:
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.. plot:: show_collection.py
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"""
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def __init__(self, filename, conserve_memory=True, dtype=None):
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"""Load a multi-img."""
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self._filename = filename
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self._conserve_memory = conserve_memory
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self._dtype = dtype
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self._cached = None
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from PIL import Image
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img = Image.open(self._filename)
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if self._conserve_memory:
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self._numframes = self._find_numframes(img)
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else:
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self._frames = self._getallframes(img)
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self._numframes = len(self._frames)
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@property
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def filename(self):
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return self._filename
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@property
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def conserve_memory(self):
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return self._conserve_memory
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def _find_numframes(self, img):
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"""Find the number of frames in the multi-img."""
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i = 0
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while True:
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i += 1
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try:
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img.seek(i)
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except EOFError:
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break
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return i
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def _getframe(self, framenum):
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"""Open the image and extract the frame."""
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from PIL import Image
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img = Image.open(self.filename)
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img.seek(framenum)
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return np.asarray(img, dtype=self._dtype)
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def _getallframes(self, img):
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"""Extract all frames from the multi-img."""
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frames = []
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try:
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i = 0
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while True:
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frames.append(np.asarray(img, dtype=self._dtype))
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i += 1
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img.seek(i)
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except EOFError:
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return frames
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def __getitem__(self, n):
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"""Return the n-th frame as an array.
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Parameters
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----------
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n : int
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Number of the required frame.
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Returns
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-------
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frame : ndarray
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The n-th frame.
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"""
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numframes = self._numframes
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if -numframes <= n < numframes:
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n = n % numframes
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else:
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raise IndexError("There are only %s frames in the image"%numframes)
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if self.conserve_memory:
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if not self._cached == n:
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frame = self._getframe(n)
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self._cached = n
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self._cachedframe = frame
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return self._cachedframe
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else:
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return self._frames[n]
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def __iter__(self):
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"""Iterate over the frames."""
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for i in range(len(self)):
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yield self[i]
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def __len__(self):
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"""Number of images in collection."""
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return self._numframes
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def __str__(self):
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return str(self.filename) + ' [%s frames]' % self._numframes
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class ImageCollection(object):
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"""Load and manage a collection of image files.
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Note that files are always stored in alphabetical order.
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Parameters
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----------
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load_pattern : str or list
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Pattern glob or filenames to load. The path can be absolute or
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relative. Multiple patterns should be separated by a colon,
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e.g. '/tmp/work/*.png:/tmp/other/*.jpg'. Also see
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implementation notes below.
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conserve_memory : bool, optional
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If True, never keep more than one in memory at a specific
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time. Otherwise, images will be cached once they are loaded.
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Other parameters
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----------------
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load_func : callable
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``imread`` by default. See notes below.
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Attributes
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----------
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files : list of str
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If a glob string is given for `load_pattern`, this attribute
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stores the expanded file list. Otherwise, this is simply
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equal to `load_pattern`.
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Notes
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-----
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ImageCollection can be modified to load images from an arbitrary
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source by specifying a combination of `load_pattern` and
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`load_func`. For an ImageCollection ``ic``, ``ic[5]`` uses
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``load_func(file_pattern[5])`` to load the image.
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Imagine, for example, an ImageCollection that loads every tenth
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frame from a video file::
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class AVILoader:
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video_file = 'myvideo.avi'
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def __call__(self, frame):
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return video_read(self.video_file, frame)
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avi_load = AVILoader()
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frames = range(0, 1000, 10) # 0, 10, 20, ...
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ic = ImageCollection(frames, load_func=avi_load)
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x = ic[5] # calls avi_load(frames[5]) or equivalently avi_load(50)
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Another use of ``load_func`` would be to convert all images to ``uint8``::
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def imread_convert(f):
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return imread(f).astype(np.uint8)
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ic = ImageCollection('/tmp/*.png', load_func=imread_convert)
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Examples
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--------
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>>> import skimage.io as io
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>>> from skimage import data_dir
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>>> coll = io.ImageCollection(data_dir + '/lena*.png')
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>>> len(coll)
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2
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>>> coll[0].shape
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(128, 128, 3)
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>>> ic = io.ImageCollection('/tmp/work/*.png:/tmp/other/*.jpg')
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"""
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def __init__(self, load_pattern, conserve_memory=True, load_func=None):
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"""Load and manage a collection of images."""
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if isinstance(load_pattern, basestring):
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load_pattern = load_pattern.split(':')
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self._files = []
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for pattern in load_pattern:
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self._files.extend(glob(pattern))
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self._files.sort()
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else:
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self._files = load_pattern
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if conserve_memory:
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memory_slots = 1
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else:
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memory_slots = len(self._files)
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self._conserve_memory = conserve_memory
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self._cached = None
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if load_func is None:
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self.load_func = imread
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else:
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self.load_func = load_func
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self.data = np.empty(memory_slots, dtype=object)
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@property
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def files(self):
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return self._files
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@property
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def conserve_memory(self):
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return self._conserve_memory
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def __getitem__(self, n):
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"""Return image n in the collection.
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Loading is done on demand.
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Parameters
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----------
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n : int
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The image number to be returned.
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Returns
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-------
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img : ndarray
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The `n`-th image in the collection.
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"""
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n = self._check_imgnum(n)
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idx = n % len(self.data)
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if (self.conserve_memory and n != self._cached) or \
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(self.data[idx] is None):
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self.data[idx] = self.load_func(self.files[n])
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self._cached = n
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return self.data[idx]
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def _check_imgnum(self, n):
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"""Check that the given image number is valid."""
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num = len(self.files)
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if -num <= n < num:
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n = n % num
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else:
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raise IndexError("There are only %s images in the collection"%num)
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return n
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def __iter__(self):
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"""Iterate over the images."""
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for i in range(len(self)):
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yield self[i]
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def __len__(self):
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"""Number of images in collection."""
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return len(self.files)
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def __str__(self):
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return str(self.files)
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def reload(self, n=None):
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"""Clear the image cache.
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Parameters
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----------
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n : None or int
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Clear the cache for this image only. By default, the
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entire cache is erased.
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"""
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self.data = np.empty_like(self.data)
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