Docs for 0.13.1
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Module: io

Utilities to read and write images in various formats.

The following plug-ins are available:

Plugin Description
pil Image reading via the Python Imaging Library
tifffile Load and save TIFF and TIFF-based images using tifffile.py
freeimage Load images using the FreeImage library
imread Image reading and writing via imread
imageio Image reading via the ImageIO Library
gtk Fast image display using the GTK library
simpleitk Image reading and writing via SimpleITK
fits FITS image reading via PyFITS
gdal Image reading via the GDAL Library (www.gdal.org)
qt Fast image display using the Qt library
matplotlib Display or save images using Matplotlib
skimage.io.call_plugin(kind, *args, **kwargs) Find the appropriate plugin of ‘kind’ and execute it.
skimage.io.concatenate_images(ic) Concatenate all images in the image collection into an array.
skimage.io.find_available_plugins([loaded]) List available plugins.
skimage.io.imread(fname[, as_grey, plugin, …]) Load an image from file.
skimage.io.imread_collection(load_pattern[, …]) Load a collection of images.
skimage.io.imread_collection_wrapper(imread)
skimage.io.imsave(fname, arr[, plugin]) Save an image to file.
skimage.io.imshow(arr[, plugin]) Display an image.
skimage.io.imshow_collection(ic[, plugin]) Display a collection of images.
skimage.io.load_sift(f) Read SIFT or SURF features from externally generated file.
skimage.io.load_surf(f) Read SIFT or SURF features from externally generated file.
skimage.io.plugin_info(plugin) Return plugin meta-data.
skimage.io.plugin_order() Return the currently preferred plugin order.
skimage.io.pop() Pop an image from the shared image stack.
skimage.io.push(img) Push an image onto the shared image stack.
skimage.io.reset_plugins()
skimage.io.show() Display pending images.
skimage.io.use_plugin(name[, kind]) Set the default plugin for a specified operation.
skimage.io.ImageCollection(load_pattern[, …]) Load and manage a collection of image files.
skimage.io.MultiImage(filename[, …]) A class containing a single multi-frame image.
skimage.io.collection Data structures to hold collections of images, with optional caching.
skimage.io.manage_plugins Handle image reading, writing and plotting plugins.
skimage.io.sift Read SIFT and SURF feature files.
skimage.io.util

call_plugin

skimage.io.call_plugin(kind, *args, **kwargs)[source]

Find the appropriate plugin of ‘kind’ and execute it.

Parameters:

kind : {‘imshow’, ‘imsave’, ‘imread’, ‘imread_collection’}

Function to look up.

plugin : str, optional

Plugin to load. Defaults to None, in which case the first matching plugin is used.

*args, **kwargs : arguments and keyword arguments

Passed to the plugin function.

concatenate_images

skimage.io.concatenate_images(ic)[source]

Concatenate all images in the image collection into an array.

Parameters:

ic: an iterable of images (including ImageCollection and MultiImage)

The images to be concatenated.

Returns:

ar : np.ndarray

An array having one more dimension than the images in ic.

Raises:

ValueError

If images in ic don’t have identical shapes.

See also

ImageCollection.concatenate, MultiImage.concatenate

find_available_plugins

skimage.io.find_available_plugins(loaded=False)[source]

List available plugins.

Parameters:

loaded : bool

If True, show only those plugins currently loaded. By default, all plugins are shown.

Returns:

p : dict

Dictionary with plugin names as keys and exposed functions as values.

imread

skimage.io.imread(fname, as_grey=False, plugin=None, flatten=None, **plugin_args)[source]

Load an image from file.

Parameters:

fname : string

Image file name, e.g. test.jpg or URL.

as_grey : bool

If True, convert color images to grey-scale (64-bit floats). Images that are already in grey-scale format are not converted.

plugin : str

Name of plugin to use. By default, the different plugins are tried (starting with the Python Imaging Library) until a suitable candidate is found. If not given and fname is a tiff file, the tifffile plugin will be used.

Returns:

img_array : ndarray

The different colour bands/channels are stored in the third dimension, such that a grey-image is MxN, an RGB-image MxNx3 and an RGBA-image MxNx4.

Other Parameters:
 

plugin_args : keywords

Passed to the given plugin.

flatten : bool

Backward compatible keyword, superseded by as_grey.

plugin_args : keywords

Passed to the given plugin.

imread_collection

skimage.io.imread_collection(load_pattern, conserve_memory=True, plugin=None, **plugin_args)[source]

Load a collection of images.

Parameters:

load_pattern : str or list

List of objects to load. These are usually filenames, but may vary depending on the currently active plugin. See the docstring for ImageCollection for the default behaviour of this parameter.

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.

Returns:

ic : ImageCollection

Collection of images.

Other Parameters:
 

plugin_args : keywords

Passed to the given plugin.

imread_collection_wrapper

skimage.io.imread_collection_wrapper(imread)[source]

imsave

skimage.io.imsave(fname, arr, plugin=None, **plugin_args)[source]

Save an image to file.

Parameters:

fname : str

Target filename.

arr : ndarray of shape (M,N) or (M,N,3) or (M,N,4)

Image data.

plugin : str

Name of plugin to use. By default, the different plugins are tried (starting with the Python Imaging Library) until a suitable candidate is found. If not given and fname is a tiff file, the tifffile plugin will be used.

Other Parameters:
 

plugin_args : keywords

Passed to the given plugin.

imshow

skimage.io.imshow(arr, plugin=None, **plugin_args)[source]

Display an image.

Parameters:

arr : ndarray or str

Image data or name of image file.

plugin : str

Name of plugin to use. By default, the different plugins are tried (starting with the Python Imaging Library) until a suitable candidate is found.

Other Parameters:
 

plugin_args : keywords

Passed to the given plugin.

imshow_collection

skimage.io.imshow_collection(ic, plugin=None, **plugin_args)[source]

Display a collection of images.

Parameters:

ic : ImageCollection

Collection to display.

plugin : str

Name of plugin to use. By default, the different plugins are tried until a suitable candidate is found.

Other Parameters:
 

plugin_args : keywords

Passed to the given plugin.

load_sift

skimage.io.load_sift(f)[source]

Read SIFT or SURF features from externally generated file.

This routine reads SIFT or SURF files generated by binary utilities from http://people.cs.ubc.ca/~lowe/keypoints/ and http://www.vision.ee.ethz.ch/~surf/.

This routine does not generate SIFT/SURF features from an image. These algorithms are patent encumbered. Please use skimage.feature.CENSURE instead.

Parameters:

f : string or open file

Input file generated by the feature detectors from http://people.cs.ubc.ca/~lowe/keypoints/ or http://www.vision.ee.ethz.ch/~surf/

Returns:

data : record array with fields

  • row: int
    row position of feature
  • column: int
    column position of feature
  • scale: float
    feature scale
  • orientation: float
    feature orientation
  • data: array
    feature values

load_surf

skimage.io.load_surf(f)[source]

Read SIFT or SURF features from externally generated file.

This routine reads SIFT or SURF files generated by binary utilities from http://people.cs.ubc.ca/~lowe/keypoints/ and http://www.vision.ee.ethz.ch/~surf/.

This routine does not generate SIFT/SURF features from an image. These algorithms are patent encumbered. Please use skimage.feature.CENSURE instead.

Parameters:

f : string or open file

Input file generated by the feature detectors from http://people.cs.ubc.ca/~lowe/keypoints/ or http://www.vision.ee.ethz.ch/~surf/

Returns:

data : record array with fields

  • row: int
    row position of feature
  • column: int
    column position of feature
  • scale: float
    feature scale
  • orientation: float
    feature orientation
  • data: array
    feature values

plugin_info

skimage.io.plugin_info(plugin)[source]

Return plugin meta-data.

Parameters:

plugin : str

Name of plugin.

Returns:

m : dict

Meta data as specified in plugin .ini.

plugin_order

skimage.io.plugin_order()[source]

Return the currently preferred plugin order.

Returns:

p : dict

Dictionary of preferred plugin order, with function name as key and plugins (in order of preference) as value.

pop

skimage.io.pop()[source]

Pop an image from the shared image stack.

Returns:

img : ndarray

Image popped from the stack.

push

skimage.io.push(img)[source]

Push an image onto the shared image stack.

Parameters:

img : ndarray

Image to push.

reset_plugins

skimage.io.reset_plugins()[source]

show

skimage.io.show()[source]

Display pending images.

Launch the event loop of the current gui plugin, and display all pending images, queued via imshow. This is required when using imshow from non-interactive scripts.

A call to show will block execution of code until all windows have been closed.

Examples

>>> import skimage.io as io
>>> for i in range(4):
...     ax_im = io.imshow(np.random.rand(50, 50))
>>> io.show() 

use_plugin

skimage.io.use_plugin(name, kind=None)[source]

Set the default plugin for a specified operation. The plugin will be loaded if it hasn’t been already.

Parameters:

name : str

Name of plugin.

kind : {‘imsave’, ‘imread’, ‘imshow’, ‘imread_collection’, ‘imshow_collection’}, optional

Set the plugin for this function. By default, the plugin is set for all functions.

See also

available_plugins
List of available plugins

Examples

To use Matplotlib as the default image reader, you would write:

>>> from skimage import io
>>> io.use_plugin('matplotlib', 'imread')

To see a list of available plugins run io.available_plugins. Note that this lists plugins that are defined, but the full list may not be usable if your system does not have the required libraries installed.

ImageCollection

class skimage.io.ImageCollection(load_pattern, conserve_memory=True, load_func=None, **load_func_kwargs)[source]

Bases: object

Load and manage a collection of image files.

Note that files are always stored in alphabetical order. Also note that slicing returns a new ImageCollection, not a view into the data.

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 os.pathsep, 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.

Other Parameters:
 

load_func : callable

imread by default. See notes below.

Notes

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')

Attributes

files (list of str) If a glob string is given for load_pattern, this attribute stores the expanded file list. Otherwise, this is simply equal to load_pattern.
__init__(load_pattern, conserve_memory=True, load_func=None, **load_func_kwargs)[source]

Load and manage a collection of images.

concatenate()[source]

Concatenate all images in the collection into an array.

Returns:

ar : np.ndarray

An array having one more dimension than the images in self.

Raises:

ValueError

If images in the ImageCollection don’t have identical shapes.

conserve_memory
files
reload(n=None)[source]

Clear the image cache.

Parameters:

n : None or int

Clear the cache for this image only. By default, the entire cache is erased.

MultiImage

class skimage.io.MultiImage(filename, conserve_memory=True, dtype=None, **imread_kwargs)[source]

Bases: skimage.io.collection.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') 
>>> len(img) 
2
>>> for frame in img: 
...     print(frame.shape) 
(15, 10)
(15, 10)
__init__(filename, conserve_memory=True, dtype=None, **imread_kwargs)[source]

Load a multi-img.

filename