mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-28 18:45:14 +08:00
Adam Wisniewski
129 lines
3.4 KiB
Python
129 lines
3.4 KiB
Python
__all__ = ['imread']
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import numpy as np
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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("The Python Image Library could not be found. "
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"Please refer to http://pypi.python.org/pypi/PIL/ "
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"for further instructions.")
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from skimage.util import img_as_ubyte
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def imread(fname, dtype=None):
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"""Load an image from file.
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"""
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im = Image.open(fname)
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if im.mode == 'P':
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if _palette_is_grayscale(im):
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im = im.convert('L')
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else:
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im = im.convert('RGB')
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elif im.mode == '1':
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im = im.convert('L')
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elif 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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im = np.fromstring(im.tostring(), dtype)
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im.shape = shape[::-1]
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elif 'A' in im.mode:
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im = im.convert('RGBA')
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return np.array(im, dtype=dtype)
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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 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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Currently, only 8-bit precision is supported.
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"""
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arr = np.asarray(arr).squeeze()
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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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# Image is floating point, assume in [0, 1]
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if np.issubdtype(arr.dtype, float):
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arr = arr * 255
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arr = arr.astype(np.uint8)
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if arr.ndim == 2:
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mode = 'L'
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elif arr.shape[2] in (3, 4):
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mode = {3: 'RGB', 4: 'RGBA'}[arr.shape[2]]
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# Force all integers to bytes
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arr = arr.astype(np.uint8)
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# default to PNG if file-like object
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if not isinstance(fname, basestring) and format_str is None:
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format_str = "PNG"
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img = Image.fromstring(mode, (arr.shape[1], arr.shape[0]), arr.tostring())
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img.save(fname, format=format_str)
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def imshow(arr):
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"""Display an image, using PIL's default display command.
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Parameters
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----------
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arr : ndarray
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Image to display. Images of dtype float are assumed to be in
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[0, 1]. Images of dtype uint8 are in [0, 255].
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"""
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Image.fromarray(img_as_ubyte(arr)).show()
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def _app_show():
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pass
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