On Mon, 08 Mar 2010 11:58:08 -0800, Christopher Barker wrote:
Daniel Lenski wrote:
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')
where do fromimage and imread come from? "namespaces are one honking great idea".
Sorry! That'd be from scipy.misc import fromimage, imread
don't be so sure -- I think PIL used lazy loading, so it doesn't actually read all the data with the open call, but rather when you try to do something with it.
I'd try making a few calls on the PIl image, and make sure it is what you expect. If it is, the easiest way to get it into a numpy array is:
True, PIL lazy-loads the image. However, I've checked this, and I'm able to manipulate the image via PIL with no problems.
np.asarray(pil_image)
Yeah, I looked at the scipy.misc.fromimage code and this is all it does, basically.
do you have a smaller image in the same format you can experiment with? That might make it easier to figure out.
Yes, smaller images in the same format work fine!
I don't know any other good, reliable way to get a big image into an array :-(
if you really can't get PIL to work, pbm looks really simple:
http://netpbm.sourceforge.net/doc/pbm.html
read the header, then read the data with np.fromfile(), then convert to a uint8 array with np.unpackbits().
That's what I've ended up doing...
You could also take a look at MPL's imread() and see what it does -- I don't think MPL requires PIL, though I could be wrong.
MPL does require PIL for formats other than PNG. Dan