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 are your
images?
Mike
On 10/01/2009 10:25 PM, Leo Trottier wrote:
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 freed.
Starting python, and run
In [5]: from glob import *;
In [6]: from pylab import *
python has 33MB of memory.
Run
In [7]: i = 1
In [8]: for imname in glob("*.JPG"):
...: im = imread(imname)
...: figure(i); i = i+1
...: imshow(im)
...:
This opens 10 figures and displays them. Python takes 480MB of memory.
This is crazy, for 10 images -- 40+MB of memory for each!
In [14]: close("all")
In [15]: i = 1
In [16]: for imname in glob("*.JPG"):
im = imread(imname)
figure(i); i = i+1
imshow(im)
....:
....:
This closes all figures and opens them again. Python takes up 837MB of
memory.
and so on... Something is really wrong with memory management.
##### System info: ##############
(using macosx backend)
2.4GHz MacBook Pro Intel Core 2 Duo
4GB 667MHz DDR2 SDRAM
In [5]: sys.version
Out[5]: '2.6.2 (r262:71600, Oct 1 2009, 16:44:23) \n[GCC 4.2.1 (Apple
Inc. build 5646)]'
In [6]: numpy.__version__
Out[6]: '1.3.0'
In [7]: matplotlib.__version__
Out[7]: '0.99.1.1'
In [8]: scipy.__version__
Out[8]: '0.7.1'
In [9]:
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