mirror of
https://github.com/wassname/scikit-image.git
synced 2026-07-20 12:40:31 +08:00
Added a MultiImg class similar to the ImageCollection one, to function as the data structure for multi-image files.
This commit is contained in:
Ralf Gommers
+172
-40
@@ -2,33 +2,39 @@
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from __future__ import with_statement
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__all__ = ['Image','ImageCollection','imread']
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__all__ = ['Img', 'ImgCollection', 'imread']
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from glob import glob
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import os.path
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import numpy as N
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from numpy.testing import set_local_path, restore_path
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from scipy.misc.pilutil import imread
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import numpy as np
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from pil_imread import imread
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set_local_path('../..')
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import supreme
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from supreme.lib import EXIF
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restore_path()
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try:
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from PIL import Image
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except ImportError:
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raise ImportError("Could not import the Python Imaging Library (PIL)"
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" required to load image files. Please refer to"
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" http://pypi.python.org/pypi/PIL/ for installation"
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" instructions.")
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class Image(N.ndarray):
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#import supreme
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#from supreme.lib import EXIF
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class Img(np.ndarray):
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"""Image data with tags."""
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tags = {'filename' : '',
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'EXIF' : {},
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'info' : {}}
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def __new__(image_cls,arr,**kwargs):
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def __new__(image_cls, arr, **kwargs):
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"""Set the image data and tags according to given parameters.
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Input:
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------
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`image_cls` : Image class specification
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`image_cls` : Img class specification
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This is not normally specified by the user.
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`arr` : ndarray
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Image data.
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@@ -36,42 +42,168 @@ class Image(N.ndarray):
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Specified in the form ``tag0=value``, ``tag1=value``.
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"""
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x = N.asarray(arr).view(image_cls)
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for tag,value in Image.tags.items():
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setattr(x,tag,kwargs.get(tag,getattr(arr,tag,value)))
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x = np.asarray(arr).view(image_cls)
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for tag, value in Img.tags.items():
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setattr(x, tag, kwargs.get(tag, getattr(arr, tag, value)))
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return x
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def __array_finalize__(self, obj):
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"""Copy object tags."""
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for tag,value in Image.tags.items():
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setattr(self,tag,getattr(obj,tag,value))
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for tag, value in Img.tags.items():
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setattr(self, tag, getattr(obj, tag, value))
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return
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def __reduce__(self):
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object_state = list(N.ndarray.__reduce__(self))
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object_state = list(np.ndarray.__reduce__(self))
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subclass_state = {}
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for tag in self.tags:
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subclass_state[tag] = getattr(self,tag)
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object_state[2] = (object_state[2],subclass_state)
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subclass_state[tag] = getattr(self, tag)
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object_state[2] = (object_state[2], subclass_state)
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return tuple(object_state)
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def __setstate__(self,state):
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nd_state,subclass_state = state
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N.ndarray.__setstate__(self,nd_state)
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def __setstate__(self, state):
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nd_state, subclass_state = state
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np.ndarray.__setstate__(self, nd_state)
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for tag in subclass_state:
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setattr(self,tag,subclass_state[tag])
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setattr(self, tag, subclass_state[tag])
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@property
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def exposure(self):
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"""Return exposure time based on EXIF tag."""
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exposure = self.EXIF['EXIF ExposureTime'].values[0]
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return exposure.num / float(exposure.den)
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#@property
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#def exposure(self):
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# """Return exposure time based on EXIF tag."""
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# exposure = self.EXIF['EXIF ExposureTime'].values[0]
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# return exposure.num / float(exposure.den)
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class ImageCollection(object):
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class MultiImg(object):
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"""A class containing a single multi-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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Attributes
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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
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Whether memory is conserved by only caching a single frame.
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numframes : int
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The number of frames in the image.
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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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Examples
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--------
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::
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>>> img = MultiImg(fname)
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>>> img.numframes
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3
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>>> for frame in img:
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... frame.shape
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(576, 384)
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(576, 384)
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(576, 384)
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"""
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def __init__(self, filename, conserve_memory=True):
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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._cached = None
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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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def _find_numframes(self, img):
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"""Find the number of frames in the multi-img."""
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try:
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i = 0
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while True:
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i += 1
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img.seek(i)
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except EOFError:
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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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img = Image.open(self.filename)
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img.seek(framenum)
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return np.asarray(img)
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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))
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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)
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class ImgCollection(object):
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"""Load and manage a collection of images."""
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def __init__(self,file_pattern,conserve_memory=True,grey=False):
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def __init__(self, file_pattern, conserve_memory=True, grey=False):
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"""Load image files.
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Note that files are always stored in alphabetical order.
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@@ -89,9 +221,9 @@ class ImageCollection(object):
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Example:
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--------
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>>> from os.path import dirname, join
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>>> data_dir = join(dirname(__file__),'tests')
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>>> data_dir = join(dirname(__file__), 'tests')
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>>> c = ImageCollection(data_dir + '/*.png')
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>>> c = ImgCollection(data_dir + '/*.png')
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>>> len(c)
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3
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>>> c[2].shape
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@@ -107,9 +239,9 @@ class ImageCollection(object):
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self.conserve_memory = conserve_memory
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self.grey = grey
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self.data = N.empty(memory_slots,dtype=object)
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self.data = np.empty(memory_slots, dtype=object)
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def __getitem__(self,n,_cached=N.array(-1)):
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def __getitem__(self, n, _cached=np.array(-1)):
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"""Return image n in the queue.
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Loading is done on demand.
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@@ -127,14 +259,14 @@ class ImageCollection(object):
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"""
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idx = n % len(self.data)
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if (_cached != n and self.conserve_memory) or (self.data[idx] is None):
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image_data = imread(self.files[n],self.grey)
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image_data = imread(self.files[n], self.grey)
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with file(self.files[n]) as f:
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exif = EXIF.process_file(f)
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#with file(self.files[n]) as f:
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#exif = EXIF.process_file(f)
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self.data[idx] = Image(image_data,
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filename=os.path.basename(self.files[n]),
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EXIF=exif,info={})
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#self.data[idx] = Img(image_data,
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#filename=os.path.basename(self.files[n]),
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#EXIF=exif, info={})
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_cached.flat = n
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