Hi all, I'm using SciPy to process some sparse binary images with a resolution of about 5000x5000 pixels. I try to load images like this: im = Image.open('/tmp/foo.pbm') print "Image loaded, size is %s and mode is %s." % (im.size, im.mode) arr = fromimage(im) or arr = imread('/tmp/foo.pbm') In either case, I get a segfault. The segfault is definitely in the SciPy code, rather than the PIL code, since PIL's Image.open runs fine. I ran strace, and there's an attempt to mmap() a region as large as the image, one byte per pixel, immediately before the segfault: mmap(NULL, 21463040, PROT_READ|PROT_WRITE, MAP_PRIVATE|MAP_ANONYMOUS, -1, 0) = 0x7f278b5be000 The funny thing is... the imread() implementation in pylab *does* work, but it converts all images to RGB mode and reverses them vertically for no apparent reason. So I'd rather not use it. Is this a known bug in SciPy? Any workarounds/fixes? I don't know any other good, reliable way to get a big image into an array :-( Dan