Hello PIL experts,
I am writing a Python script to analyse a multipage TIFF image stacks
coming from a microscope. The average file size is around several
gigabytes with few thousand grayscale frames and the resolution is
around 640x480 or thereabouts.
For this I need to apply some temporal filtering to individual pixels
(temporal means that I need to construct a "line" from the values of
this pixel along the pages).
Currently I am using Image.getpixel() in cycle, but it turns out that
it's prohibitively slow (much slower than the filtering that I am
applying). I estimated that on my 2 Ghz laptop it will take around 400
hours to analyse one pack (all the pixels).
Therefore I'd like to inquire whether this is an issue with PIL, or
underlying TIFF reader, or maybe there's a built-in method to quickly
read Z-axis cut that I didn't consider (I'm a total PIL n00b).
Also I was considering that maybe reading the whole page with some
built-in method, such as Image.getdata() and switching through the pages
may be faster, but I can't store the whole stack in memory (the stacks
that we have now will take around ~4 Gb, but this will quickly grow...).
Fortunately I can apply filters to a window, but this will introduce a
lot of complication in the algorithm, so I'm really looking forward to
hearing from you whether it is possible to speed up my code as is.
Many thanks!
P.S. Snippet attached:
import numpy as np
def getvalue(im, position):
pixel = im.getpixel( position )
if isinstance(pixel, int):
return pixel
else:
return np.sqrt( np.sum( np.array(pixel) ** 2 ) )
im_name = 'bleaching.tiff'
im = Image.open(im_name)
page = 0
line = []
try:
while True:
im.seek(page)
line.append(getvalue(im, (x, y) ))
page += 1
except EOFError:
pass
<do something with line and take another pixel>
--
Sincerely yours,
Yury V. Zaytsev
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