Hi Michael,
I suppose I'm a bit confused -- I thought that jpeglib, part of which
is implemented by PIL (??) could process compressed images without
representing decompressing them to a dense raster-image matrix
(http://en.wikipedia.org/wiki/Jpeglib).
That said, I tried to do some PIL things,
Leo Trottier wrote:
Hi Michael,
I suppose I'm a bit confused -- I thought that jpeglib, part of which
is implemented by PIL (??)
Other way around. PIL uses jpeglib to read JPEG files.
could process compressed images without
representing decompressing them to a dense raster-image matrix
Hi,
I think I've figured out what's going on. It's a combination of things:
1) iPython is ignorant of the problems associated with caching massive data
output
2) iPython doesn't seem to have a good way to clear data from memory
reliably (https://bugs.launchpad.net/ipython/+bug/412350)
3)
If you assign each figure to a new number, it will keep all of those
figures around in memory (because pyplot thinks you may want to use it
again.) The best route is to call close('all') or fig.close() with each
loop iteration.
40MB per image doesn't sound way out of reason to me. How big
I have a friend who's having strange memory issues when opening and
displaying images (using Matplotlib).
Here's what he says:
###
pylab seems really inefficient: Opening a few images and displaying them
eats up tons of memory, and the memory doesn't get
