diff --git a/CHANGELOG.rst b/CHANGELOG.rst
index e074d702b6c87ab9dae882cdd6a42e9eac12c669..2790ec5d8549a8ae2352c5aef6cf6c8d862d0842 100644
--- a/CHANGELOG.rst
+++ b/CHANGELOG.rst
@@ -2,6 +2,17 @@ This document contains the ``fslpy`` release history in reverse chronological
order.
+2.3.1 (Friday July 5th 2019)
+----------------------------
+
+
+Fixed
+^^^^^
+
+
+* The :class:`.Bitmap` class now supports greyscale images and palette images.
+
+
2.3.0 (Tuesday June 25th 2019)
------------------------------
diff --git a/fsl/data/bitmap.py b/fsl/data/bitmap.py
index ec7b6b1fe1c9e12c5fa8e52c6e52589f1be3281c..51b354f7ddfcef93cb44a2d2a83231b518d89fe2 100644
--- a/fsl/data/bitmap.py
+++ b/fsl/data/bitmap.py
@@ -51,30 +51,48 @@ class Bitmap(object):
data.
"""
- try:
- import PIL.Image as Image
- except ImportError:
- raise RuntimeError('Install Pillow to use the Bitmap class')
-
if isinstance(bmp, six.string_types):
- source = bmp
- data = np.array(Image.open(source))
+
+ try:
+ # Allow big images
+ import PIL.Image as Image
+ Image.MAX_IMAGE_PIXELS = 1e9
+
+ except ImportError:
+ raise RuntimeError('Install Pillow to use the Bitmap class')
+
+ src = bmp
+ img = Image.open(src)
+
+ # If this is a palette/LUT
+ # image, convert it into a
+ # regular rgb(a) image.
+ if img.mode == 'P':
+ img = img.convert()
+
+ data = np.array(img)
elif isinstance(bmp, np.ndarray):
- source = 'array'
- data = np.copy(bmp)
+ src = 'array'
+ data = np.copy(bmp)
else:
raise ValueError('unknown bitmap: {}'.format(bmp))
- # Make the array (w, h, c)
+ # Make the array (w, h, c). Single channel
+ # (e.g. greyscale) images are returned as
+ # 2D arrays, whereas multi-channel images
+ # are returned as 3D. In either case, the
+ # first two dimensions are (height, width),
+ # but we watn them the other way aruond.
+ data = np.atleast_3d(data)
data = np.fliplr(data.transpose((1, 0, 2)))
data = np.array(data, dtype=np.uint8, order='C')
w, h = data.shape[:2]
self.__data = data
- self.__dataSource = source
- self.__name = op.basename(source)
+ self.__dataSource = src
+ self.__name = op.basename(src)
def __hash__(self):
@@ -132,7 +150,6 @@ class Bitmap(object):
if nchannels == 1:
dtype = np.uint8
-
elif nchannels == 3:
dtype = np.dtype([('R', 'uint8'),
('G', 'uint8'),
@@ -158,4 +175,6 @@ class Bitmap(object):
data = np.array(data, order='F', copy=False)
- return fslimage.Image(data, name=self.name)
+ return fslimage.Image(data,
+ name=self.name,
+ dataSource=self.dataSource)
diff --git a/fsl/data/image.py b/fsl/data/image.py
index 417a0445ceccd64f6bcc28d7abc1d2214c2de32d..1bf901c287d5c2ba3ea033e11f08fdb79cc55e3d 100644
--- a/fsl/data/image.py
+++ b/fsl/data/image.py
@@ -809,6 +809,7 @@ class Image(Nifti):
"""
nibImage = None
+ saved = False
if indexed is not False:
warnings.warn('The indexed argument is deprecated '
@@ -841,10 +842,10 @@ class Image(Nifti):
# The image parameter may be the name of an image file
if isinstance(image, six.string_types):
-
image = op.abspath(addExt(image))
nibImage = nib.load(image, **kwargs)
dataSource = image
+ saved = True
# Or a numpy array - we wrap it in a nibabel image,
# with an identity transformation (each voxel maps
@@ -906,7 +907,7 @@ class Image(Nifti):
self.__dataSource = dataSource
self.__threaded = threaded
self.__nibImage = nibImage
- self.__saveState = dataSource is not None
+ self.__saveState = saved
self.__imageWrapper = imagewrapper.ImageWrapper(self.nibImage,
self.name,
loadData=loadData,
diff --git a/tests/test_bitmap.py b/tests/test_bitmap.py
index b59c4083e2e822400f19ccc6895d500179fb4149..20b369e75775e52b2acd5e83397aa980bb437f93 100644
--- a/tests/test_bitmap.py
+++ b/tests/test_bitmap.py
@@ -19,22 +19,30 @@ def test_bitmap():
from PIL import Image
+ nchannels = (1, 3, 4)
+
with tempdir.tempdir():
- data = np.random.randint(0, 255, (100, 200, 4), dtype=np.uint8)
- img = Image.fromarray(data, mode='RGBA')
- img.save('image.png')
+ for nch in nchannels:
+ data = np.random.randint(0, 255, (100, 200, nch), dtype=np.uint8)
+ img = Image.fromarray(data.squeeze())
+
+ fname = 'image.png'
+ img.save(fname)
- bmp = fslbmp.Bitmap('image.png')
+ bmp1 = fslbmp.Bitmap(fname)
+ bmp2 = fslbmp.Bitmap(data)
- assert bmp.name == 'image.png'
- assert bmp.dataSource == 'image.png'
- assert bmp.shape == (200, 100, 4)
+ assert bmp1.name == fname
+ assert bmp1.dataSource == fname
+ assert bmp1.shape == (200, 100, nch)
+ assert bmp2.shape == (200, 100, nch)
- repr(bmp)
- hash(bmp)
+ repr(bmp1)
+ hash(bmp1)
- assert np.all(bmp.data == np.fliplr(data.transpose(1, 0, 2)))
+ assert np.all(bmp1.data == np.fliplr(data.transpose(1, 0, 2)))
+ assert np.all(bmp2.data == np.fliplr(data.transpose(1, 0, 2)))
@pytest.mark.piltest
@@ -47,17 +55,23 @@ def test_bitmap_asImage():
img3 = Image.fromarray(d3, mode='RGB')
img4 = Image.fromarray(d4, mode='RGBA')
+ img1 = img3.convert(mode='P')
img3.save('rgb.png')
img4.save('rgba.png')
+ img1.save('p.png')
- bmp3 = fslbmp.Bitmap('rgb.png')
- bmp4 = fslbmp.Bitmap('rgba.png')
+ bmp3 = fslbmp.Bitmap('rgb.png')
+ bmp4 = fslbmp.Bitmap('rgba.png')
+ bmp1 = fslbmp.Bitmap('p.png')
- i3 = bmp3.asImage()
- i4 = bmp4.asImage()
+ i3 = bmp3.asImage()
+ i4 = bmp4.asImage()
+ i1 = bmp1.asImage()
assert i3.shape == (200, 100, 1)
assert i4.shape == (200, 100, 1)
+ assert i1.shape == (200, 100, 1)
assert i3.nvals == 3
assert i4.nvals == 4
+ assert i1.nvals == 3