mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-28 04:39:13 +08:00
Thomas Robitaille
151 lines
4.6 KiB
Python
151 lines
4.6 KiB
Python
__all__ = ['imread', 'imread_collection']
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import skimage.io as io
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try:
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from astropy.io import fits as pyfits
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except ImportError:
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try:
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import pyfits
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except ImportError:
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raise ImportError("PyFITS could not be found. Please refer to\n"
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"http://www.stsci.edu/resources/software_hardware/pyfits\n"
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"for further instructions.")
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def imread(fname, dtype=None):
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"""Load an image from a FITS file.
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Parameters
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----------
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fname : string
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Image file name, e.g. ``test.fits``.
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dtype : dtype, optional
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For FITS, this argument is ignored because Stefan is planning on
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removing the dtype argument from imread anyway.
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Returns
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-------
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img_array : ndarray
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Unlike plugins such as PIL, where different colour bands/channels are
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stored in the third dimension, FITS images are greyscale-only and can
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be N-dimensional, so an array of the native FITS dimensionality is
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returned, without colour channels.
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Currently if no image is found in the file, None will be returned
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Notes
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-----
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Currently FITS ``imread()`` always returns the first image extension when
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given a Multi-Extension FITS file; use ``imread_collection()`` (which does
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lazy loading) to get all the extensions at once.
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"""
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hdulist = pyfits.open(fname)
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# Iterate over FITS image extensions, ignoring any other extension types
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# such as binary tables, and get the first image data array:
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img_array = None
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for hdu in hdulist:
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if isinstance(hdu, pyfits.ImageHDU) or \
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isinstance(hdu, pyfits.PrimaryHDU):
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if hdu.data is not None:
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img_array = hdu.data
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break
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hdulist.close()
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return img_array
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def imread_collection(load_pattern, conserve_memory=True):
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"""Load a collection of images from one or more FITS files
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Parameters
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----------
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load_pattern : str or list
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List of extensions to load. Filename globbing is currently
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unsupported.
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converve_memory : bool
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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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Returns
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-------
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ic : ImageCollection
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Collection of images.
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"""
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intype = type(load_pattern)
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if intype is not list and intype is not str:
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raise TypeError("Input must be a filename or list of filenames")
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# Ensure we have a list, otherwise we'll end up iterating over the string:
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if intype is not list:
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load_pattern = [load_pattern]
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# Generate a list of filename/extension pairs by opening the list of
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# files and finding the image extensions in each one:
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ext_list = []
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for filename in load_pattern:
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hdulist = pyfits.open(filename)
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for n, hdu in zip(range(len(hdulist)), hdulist):
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if isinstance(hdu, pyfits.ImageHDU) or \
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isinstance(hdu, pyfits.PrimaryHDU):
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# Ignore (primary) header units with no data (use '.size'
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# rather than '.data' to avoid actually loading the image):
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try:
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data_size = hdu.size()
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except TypeError: # (size changed to int in PyFITS 3.1)
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data_size = hdu.size
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if data_size > 0:
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ext_list.append((filename, n))
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hdulist.close()
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return io.ImageCollection(ext_list, load_func=FITSFactory,
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conserve_memory=conserve_memory)
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def FITSFactory(image_ext):
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"""Load an image extension from a FITS file and return a NumPy array
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Parameters
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----------
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image_ext : tuple
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FITS extension to load, in the format ``(filename, ext_num)``.
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The FITS ``(extname, extver)`` format is unsupported, since this
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function is not called directly by the user and
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``imread_collection()`` does the work of figuring out which
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extensions need loading.
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"""
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# Expect a length-2 tuple with a filename as the first element:
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if not isinstance(image_ext, tuple):
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raise TypeError("Expected a tuple")
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if len(image_ext) != 2:
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raise ValueError("Expected a tuple of length 2")
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filename = image_ext[0]
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extnum = image_ext[1]
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if type(filename) is not str or type(extnum) is not int:
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raise ValueError("Expected a (filename, extension) tuple")
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hdulist = pyfits.open(filename)
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data = hdulist[extnum].data
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hdulist.close()
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if data is None:
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raise RuntimeError("Extension %d of %s has no data" %
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(extnum, filename))
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return data
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