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scikit-image/scikits/image/io/_plugins/pil_plugin.py
T
2010-06-08 21:25:14 -06:00

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3.0 KiB
Python

__all__ = ['imread']
import numpy as np
try:
from PIL import Image
except ImportError:
raise ImportError("The Python Image Library could not be found. "
"Please refer to http://pypi.python.org/pypi/PIL/ "
"for further instructions.")
def imread(fname, as_grey=False, dtype=None):
"""Load an image from file.
"""
im = Image.open(fname)
if im.mode == 'P':
if _palette_is_grayscale(im):
im = im.convert('L')
else:
im = im.convert('RGB')
if as_grey and not \
im.mode in ('1', 'L', 'I', 'F', 'I;16', 'I;16L', 'I;16B', 'LA'):
im = im.convert('F')
if 'A' in im.mode:
im = im.convert('RGBA')
return np.array(im, dtype=dtype)
def _palette_is_grayscale(pil_image):
"""Return True if PIL image in palette mode is grayscale.
Parameters
----------
pil_image : PIL image
PIL Image that is in Palette mode.
Returns
-------
is_grayscale : bool
True if all colors in image palette are gray.
"""
assert pil_image.mode == 'P'
# get palette as an array with R, G, B columns
palette = np.asarray(pil_image.getpalette()).reshape((256, 3))
# Not all palette colors are used; unused colors have junk values.
start, stop = pil_image.getextrema()
valid_palette = palette[start:stop]
# Image is grayscale if channel differences (R - G and G - B)
# are all zero.
return np.allclose(np.diff(valid_palette), 0)
def imsave(fname, arr):
"""Save an image to disk.
Parameters
----------
fname : str
Name of destination file.
arr : ndarray of uint8 or float
Array (image) to save. Arrays of data-type uint8 should have
values in [0, 255], whereas floating-point arrays must be
in [0, 1].
Notes
-----
Currently, only 8-bit precision is supported.
"""
arr = np.asarray(arr).squeeze()
if arr.ndim not in (2, 3):
raise ValueError("Invalid shape for image array: %s" % arr.shape)
if arr.ndim == 3:
if arr.shape[2] not in (3, 4):
raise ValueError("Invalid number of channels in image array.")
# Image is floating point, assume in [0, 1]
if np.issubdtype(arr.dtype, float):
arr = arr * 255
arr = arr.astype(np.uint8)
if arr.ndim == 2:
mode = 'L'
elif arr.shape[2] in (3, 4):
mode = {3: 'RGB', 4: 'RGBA'}[arr.shape[2]]
# Force all integers to bytes
arr = arr.astype(np.uint8)
img = Image.fromstring(mode, (arr.shape[1], arr.shape[0]), arr.tostring())
img.save(fname)
def imshow(arr):
"""Display an image, using PIL's default display command.
Parameters
----------
arr : ndarray
Image to display. Images of dtype float are assumed to be in
[0, 1]. Images of dtype uint8 are in [0, 255].
"""
if np.issubdtype(arr.dtype, float):
arr = (arr * 255).astype(np.uint8)
Image.fromarray(arr).show()