Merge branch 'io_cleanup'

doc/source/api_changes.txt

@@ -1,4 +1,5 @@
 Version 0.3
 -----------
-- Remove ``as_grey``, ``dtype`` keywords from imread and ImageCollection
+- Remove ``as_grey``, ``dtype`` keyword from ImageCollection
+- Remove ``dtype`` from imread
 - Generalise ImageCollection to accept a load_func

scikits/image/color/colorconv.py

@@ -44,7 +44,7 @@ References
 from __future__ import division
 
 __all__ = ['convert_colorspace', 'rgb2hsv', 'hsv2rgb', 'rgb2xyz', 'xyz2rgb',
-           'rgb2rgbcie', 'rgbcie2rgb']
+           'rgb2rgbcie', 'rgbcie2rgb', 'rgb2grey', 'rgb2gray']
 
 __docformat__ = "restructuredtext en"
 
@@ -264,7 +264,7 @@ xyz_from_rgb =  np.array([[0.412453, 0.357580, 0.180423],
 rgb_from_xyz = linalg.inv(xyz_from_rgb)
 
 # From http://en.wikipedia.org/wiki/CIE_1931_color_space
-# Note: Travis' code did not have the divide by 0.17697
+# Note: Travis's code did not have the divide by 0.17697
 xyz_from_rgbcie = np.array([[0.49, 0.31, 0.20],
                             [0.17697, 0.81240, 0.01063],
                             [0.00, 0.01, 0.99]]) / 0.17697
@@ -276,6 +276,10 @@ rgbcie_from_rgb = np.dot(rgbcie_from_xyz, xyz_from_rgb)
 rgb_from_rgbcie = np.dot(rgb_from_xyz, xyz_from_rgbcie)
 
 
+grey_from_rgb = np.array([[0.2125, 0.7154, 0.0721],
+                          [0, 0, 0],
+                          [0, 0, 0]])
+
 #-------------------------------------------------------------
 # The conversion functions that make use of the matrices above
 #-------------------------------------------------------------
@@ -338,6 +342,7 @@ def xyz2rgb(xyz):
     >>> import os
     >>> from scikits.image import data_dir
     >>> from scikits.image.io import imread
+    >>> from scikits.image.color import rgb2xyz, xyz2rgb
 
     >>> lena = imread(os.path.join(data_dir, 'lena.png'))
     >>> lena_xyz = rgb2xyz(lena)
@@ -410,6 +415,7 @@ def rgb2rgbcie(rgb):
     >>> import os
     >>> from scikits.image import data_dir
     >>> from scikits.image.io import imread
+    >>> from scikits.image.color import rgb2rgbcie
 
     >>> lena = imread(os.path.join(data_dir, 'lena.png'))
     >>> lena_rgbcie = rgb2rgbcie(lena)
@@ -443,9 +449,54 @@ def rgbcie2rgb(rgbcie):
     >>> import os
     >>> from scikits.image import data_dir
     >>> from scikits.image.io import imread
+    >>> from scikits.image.color import rgb2rgbcie, rgbcie2rgb
 
     >>> lena = imread(os.path.join(data_dir, 'lena.png'))
     >>> lena_rgbcie = rgb2rgbcie(lena)
     >>> lena_rgb = rgbcie2rgb(lena_hsv)
     """
     return _convert(rgb_from_rgbcie, rgbcie)
+
+def rgb2grey(rgb):
+    """Compute luminance of an RGB image.
+
+    Parameters
+    ----------
+    rgb : array_like
+        The image in RGB format, in a 3-D array of shape (.., .., 3).
+
+    Returns
+    -------
+    out : ndarray
+        The luminance image, a 2-D array.
+
+    Raises
+    ------
+    ValueError
+        If `rgb2grey` is not a 3-D array of shape (.., .., 3).
+
+    References
+    ----------
+    .. [1] http://www.poynton.com/PDFs/ColorFAQ.pdf
+
+    Notes
+    -----
+    The weights used in this conversion are calibrated for contemporary
+    CRT phosphors::
+
+        Y = 0.2125 R + 0.7154 G + 0.0721 B
+
+    Examples
+    --------
+    >>> import os
+    >>> from scikits.image import data_dir
+    >>> from scikits.image.io import imread
+    >>> from scikits.image.color import rgb2grey
+
+    >>> lena = imread(os.path.join(data_dir, 'lena.png'))
+    >>> lena_grey = rgb2grey(lena)
+    """
+    return _convert(grey_from_rgb, rgb)[..., 0]
+
+rgb2gray = rgb2grey
+

scikits/image/color/tests/test_colorconv.py

@@ -21,7 +21,8 @@ from scikits.image.color import (
     rgb2hsv, hsv2rgb,
     rgb2xyz, xyz2rgb,
     rgb2rgbcie, rgbcie2rgb,
-    convert_colorspace
+    convert_colorspace,
+    rgb2grey
     )
 
 from scikits.image import data_dir
@@ -142,6 +143,13 @@ class TestColorconv(TestCase):
         self.assertRaises(ValueError, convert_colorspace, self.colbars_array,
                                                            'RGB', 'nokey')
 
+    def test_rgb2grey(self):
+        x = np.array([1, 1, 1]).reshape((1, 1, 3))
+        g = rgb2grey(x)
+        assert_array_almost_equal(g, 1)
+
+        assert_equal(g.shape, (1, 1))
+
 if __name__ == "__main__":
     run_module_suite()
 

scikits/image/io/_plugins/freeimage_plugin.py

@@ -319,11 +319,11 @@ def _array_from_bitmap(bitmap):
     def n(arr):
         return arr[..., ::-1].T
     if len(shape) == 3 and _FI.FreeImage_IsLittleEndian() and \
-       dtype.type == np.uint8:
+       dtype.type == numpy.uint8:
         b = array[0]
         g = array[1]
         r = array[2]
-        return np.dstack( (n(r), n(g), n(b)) )
+        return numpy.dstack( (n(r), n(g), n(b)) )
     # We need to copy because array does *not* own its memory
     # after bitmap is freed.
     return n(array).copy()
@@ -460,8 +460,8 @@ def imread(filename, as_grey=False):
     img = read(filename)
     if as_grey and len(img) == 3:
         # these are the values that wikipedia says are typical
-        transform = np.array([ 0.30,  0.59,  0.11])
-        return np.dot(img, transform)
+        transform = numpy.array([ 0.30,  0.59,  0.11])
+        return numpy.dot(img, transform)
     return img
 
 def imsave(filename, img):

scikits/image/io/_plugins/test_freeimage.py

@@ -0,0 +1,13 @@
+import os
+
+import scikits.image as si
+import scikits.image.io as sio
+
+sio.use_plugin('matplotlib', 'imshow')
+sio.use_plugin('freeimage', 'imread')
+
+img = sio.imread(os.path.join(si.data_dir, 'color.png'))
+
+sio.imshow(img)
+sio.show()
+

scikits/image/io/_plugins/test_plugin.py

@@ -1,6 +1,5 @@
 def imread(fname, as_grey=False, dtype=None):
     assert fname == 'test.png'
-    assert as_grey == True
     assert dtype == 'i4'
 
 def imsave(fname, arr):

scikits/image/io/collection.py

@@ -23,9 +23,6 @@ class MultiImage(object):
     conserve_memory : bool, optional
         Whether to conserve memory by only caching a single frame. Default is
         True.
-    dtype : dtype, optional
-        NumPy data-type specifier. If given, the returned image has this type.
-        If None (default), the data-type is determined automatically.
 
     Attributes
     ----------

scikits/image/io/io.py

@@ -1,6 +1,7 @@
 __all__ = ['imread', 'imsave', 'imshow', 'show', 'push', 'pop']
 
 from scikits.image.io._plugins import call as call_plugin
+from scikits.image.color import rgb2grey
 import numpy as np
 
 # Shared image queue
@@ -31,7 +32,7 @@ def pop():
     """
     return _image_stack.pop()
 
-def imread(fname, as_grey=False, dtype=None, plugin=None, flatten=None,
+def imread(fname, as_grey=False, plugin=None, flatten=None,
            **plugin_args):
     """Load an image from file.
 
@@ -40,12 +41,8 @@ def imread(fname, as_grey=False, dtype=None, plugin=None, flatten=None,
     fname : string
         Image file name, e.g. ``test.jpg``.
     as_grey : bool
-        If True, convert color images to grey-scale. If `dtype` is not given,
-        converted color images are returned as 32-bit float images.
+        If True, convert color images to grey-scale (32-bit floats).
         Images that are already in grey-scale format are not converted.
-    dtype : dtype, optional
-        NumPy data-type specifier. If given, the returned image has this type.
-        If None (default), the data-type is determined automatically.
     plugin : str
         Name of plugin to use (Python Imaging Library by default).
 
@@ -71,8 +68,12 @@ def imread(fname, as_grey=False, dtype=None, plugin=None, flatten=None,
     if flatten is not None:
         as_grey = flatten
 
-    return call_plugin('imread', fname, as_grey=as_grey, dtype=dtype,
-                       plugin=plugin, **plugin_args)
+    img = call_plugin('imread', fname, plugin=plugin, **plugin_args)
+
+    if as_grey and getattr(img, 'ndim', 0) >= 3:
+        img = rgb2grey(img)
+
+    return img
 
 def imsave(fname, arr, plugin=None, **plugin_args):
     """Save an image to file.

scikits/image/io/tests/test_pil.py

@@ -9,17 +9,14 @@ from scikits.image.io import imread, imsave
 from scikits.image.io._plugins.pil_plugin import _palette_is_grayscale
 
 def test_imread_flatten():
-    # a color image is flattened and returned as float32
+    # a color image is flattened
     img = imread(os.path.join(data_dir, 'color.png'), flatten=True)
-    assert img.dtype == np.float32
+    assert img.ndim == 2
+    assert img.dtype == np.float64
     img = imread(os.path.join(data_dir, 'camera.png'), flatten=True)
     # check that flattening does not occur for an image that is grey already.
     assert np.sctype2char(img.dtype) in np.typecodes['AllInteger']
 
-def test_imread_dtype():
-    img = imread(os.path.join(data_dir, 'camera.png'), dtype=np.float64)
-    assert img.dtype == np.float64
-
 def test_imread_palette():
     img = imread(os.path.join(data_dir, 'palette_gray.png'))
     assert img.ndim == 2