mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-29 00:55:44 +08:00
Tony S Yu
266 lines
7.6 KiB
Python
266 lines
7.6 KiB
Python
__all__ = ['imread', 'imsave']
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import numpy as np
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from six import string_types
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from PIL import Image
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from ...util import img_as_ubyte, img_as_uint
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from ...external.tifffile import imread as tif_imread, imsave as tif_imsave
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def imread(fname, dtype=None, img_num=None, **kwargs):
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"""Load an image from file.
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Parameters
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----------
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fname : str
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File name.
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dtype : numpy dtype object or string specifier
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Specifies data type of array elements.
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img_num : int, optional
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Specifies which image to read in a file with multiple images
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(zero-indexed).
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kwargs : keyword pairs, optional
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Addition keyword arguments to pass through (only applicable to Tiff
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files for now, see `tifffile`'s `imread` function).
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Notes
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-----
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Tiff files are handled by Christophe Golhke's tifffile.py [1]_, and support many
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advanced image types including multi-page and floating point.
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All other files are read using the Python Imaging Libary.
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See PIL docs [2]_ for a list of supported formats.
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References
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----------
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.. [1] http://www.lfd.uci.edu/~gohlke/code/tifffile.py.html
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.. [2] http://pillow.readthedocs.org/en/latest/handbook/image-file-formats.html
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"""
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if hasattr(fname, 'lower') and dtype is None:
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kwargs.setdefault('key', img_num)
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if fname.lower().endswith(('.tiff', '.tif')):
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return tif_imread(fname, **kwargs)
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im = Image.open(fname)
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try:
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# this will raise an IOError if the file is not readable
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im.getdata()[0]
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except IOError:
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site = "http://pillow.readthedocs.org/en/latest/installation.html#external-libraries"
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raise ValueError('Could not load "%s"\nPlease see documentation at: %s' % (fname, site))
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else:
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return pil_to_ndarray(im, dtype=dtype, img_num=img_num)
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def pil_to_ndarray(im, dtype=None, img_num=None):
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"""Import a PIL Image object to an ndarray, in memory.
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Parameters
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----------
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Refer to ``imread``.
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"""
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frames = []
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grayscale = None
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i = 0
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while 1:
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try:
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im.seek(i)
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except EOFError:
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break
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frame = im
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if img_num is not None and img_num != i:
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im.getdata()[0]
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i += 1
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continue
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if im.mode == 'P':
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if grayscale is None:
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grayscale = _palette_is_grayscale(im)
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if grayscale:
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frame = im.convert('L')
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else:
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frame = im.convert('RGB')
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elif im.mode == '1':
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frame = im.convert('L')
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elif 'A' in im.mode:
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frame = im.convert('RGBA')
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elif im.mode == 'CMYK':
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frame = im.convert('RGB')
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if im.mode.startswith('I;16'):
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shape = im.size
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dtype = '>u2' if im.mode.endswith('B') else '<u2'
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if 'S' in im.mode:
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dtype = dtype.replace('u', 'i')
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frame = np.fromstring(frame.tobytes(), dtype)
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frame.shape = shape[::-1]
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else:
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frame = np.array(frame, dtype=dtype)
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frames.append(frame)
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i += 1
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if hasattr(im, 'fp') and im.fp:
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im.fp.close()
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if img_num is None and len(frames) > 1:
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return np.array(frames)
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elif frames:
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return frames[0]
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elif img_num:
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raise IndexError('Could not find image #%s' % img_num)
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def _palette_is_grayscale(pil_image):
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"""Return True if PIL image in palette mode is grayscale.
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Parameters
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----------
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pil_image : PIL image
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PIL Image that is in Palette mode.
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Returns
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-------
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is_grayscale : bool
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True if all colors in image palette are gray.
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"""
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assert pil_image.mode == 'P'
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# get palette as an array with R, G, B columns
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palette = np.asarray(pil_image.getpalette()).reshape((256, 3))
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# Not all palette colors are used; unused colors have junk values.
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start, stop = pil_image.getextrema()
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valid_palette = palette[start:stop]
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# Image is grayscale if channel differences (R - G and G - B)
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# are all zero.
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return np.allclose(np.diff(valid_palette), 0)
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def ndarray_to_pil(arr, format_str=None):
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"""Export an ndarray to a PIL object.
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Parameters
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----------
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Refer to ``imsave``.
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"""
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if arr.ndim == 3:
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arr = img_as_ubyte(arr)
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mode = {3: 'RGB', 4: 'RGBA'}[arr.shape[2]]
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elif format_str in ['png', 'PNG']:
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mode = 'I;16'
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mode_base = 'I'
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if arr.dtype.kind == 'f':
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arr = img_as_uint(arr)
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elif arr.max() < 256 and arr.min() >= 0:
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arr = arr.astype(np.uint8)
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mode = mode_base = 'L'
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else:
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arr = img_as_uint(arr)
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else:
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arr = img_as_ubyte(arr)
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mode = 'L'
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mode_base = 'L'
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try:
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array_buffer = arr.tobytes()
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except AttributeError:
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array_buffer = arr.tostring() # Numpy < 1.9
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if arr.ndim == 2:
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im = Image.new(mode_base, arr.T.shape)
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try:
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im.frombytes(array_buffer, 'raw', mode)
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except AttributeError:
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im.fromstring(array_buffer, 'raw', mode) # PIL 1.1.7
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else:
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image_shape = (arr.shape[1], arr.shape[0])
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try:
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im = Image.frombytes(mode, image_shape, array_buffer)
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except AttributeError:
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im = Image.fromstring(mode, image_shape, array_buffer) # PIL 1.1.7
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return im
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def imsave(fname, arr, format_str=None):
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"""Save an image to disk.
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Parameters
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----------
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fname : str or file-like object
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Name of destination file.
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arr : ndarray of uint8 or float
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Array (image) to save. Arrays of data-type uint8 should have
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values in [0, 255], whereas floating-point arrays must be
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in [0, 1].
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format_str: str
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Format to save as, this is defaulted to PNG if using a file-like
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object; this will be derived from the extension if fname is a string
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Notes
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-----
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Tiff files are handled by Christophe Golhke's tifffile.py [1]_,
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and support many advanced image types including multi-page and
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floating point.
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All other image formats use the Python Imaging Libary.
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See PIL docs [2]_ for a list of other supported formats.
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All images besides single channel PNGs are converted using `img_as_uint8`.
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Single Channel PNGs have the following behavior:
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- Integer values in [0, 255] and Boolean types -> img_as_uint8
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- Floating point and other integers -> img_as_uint16
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References
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----------
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.. [1] http://www.lfd.uci.edu/~gohlke/code/tifffile.py.html
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.. [2] http://pillow.readthedocs.org/en/latest/handbook/image-file-formats.html
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"""
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# default to PNG if file-like object
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if not isinstance(fname, string_types) and format_str is None:
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format_str = "PNG"
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# Check for png in filename
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if (isinstance(fname, string_types)
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and fname.lower().endswith(".png")):
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format_str = "PNG"
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arr = np.asanyarray(arr).squeeze()
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if arr.dtype.kind == 'b':
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arr = arr.astype(np.uint8)
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use_tif = False
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if hasattr(fname, 'lower'):
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if fname.lower().endswith(('.tiff', '.tif')):
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use_tif = True
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if not format_str is None:
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if format_str.lower() in ['tiff', 'tif']:
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use_tif = True
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if use_tif:
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tif_imsave(fname, arr)
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return
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if arr.ndim not in (2, 3):
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raise ValueError("Invalid shape for image array: %s" % arr.shape)
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if arr.ndim == 3:
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if arr.shape[2] not in (3, 4):
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raise ValueError("Invalid number of channels in image array.")
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img = ndarray_to_pil(arr, format_str=format_str)
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img.save(fname, format=format_str)
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