From 1a811c11466ae4d2e8743272b4dbe8fa3643563f Mon Sep 17 00:00:00 2001
From: Paul McCarthy <pauldmccarthy@gmail.com>
Date: Wed, 3 Jul 2019 15:29:40 +0930
Subject: [PATCH] BF: Tell Pillow to allow bigger images. Make sure
single-chanel images are still shaped (w, h, c), where c == 1
---
fsl/data/bitmap.py | 23 ++++++++++++++++-------
1 file changed, 16 insertions(+), 7 deletions(-)
diff --git a/fsl/data/bitmap.py b/fsl/data/bitmap.py
index ec7b6b1fe..0e5c9b413 100644
--- a/fsl/data/bitmap.py
+++ b/fsl/data/bitmap.py
@@ -51,12 +51,16 @@ 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):
+
+ 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')
+
source = bmp
data = np.array(Image.open(source))
@@ -67,7 +71,13 @@ class Bitmap(object):
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]
@@ -132,7 +142,6 @@ class Bitmap(object):
if nchannels == 1:
dtype = np.uint8
-
elif nchannels == 3:
dtype = np.dtype([('R', 'uint8'),
('G', 'uint8'),
--
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