Some hints: - pad image with skimage.util.pad, which allows a large number of padding methods - spawn a pool of processes using Python's multiprocessing package in the standard library - use shared memory to provide read access to complete image - define slices of image blocks and add them to a processing queue Am 31.08.2013 um 20:05 schrieb Riaan van den Dool :

The blockproc function's signature provides a useful starting point, thanks. http://www.mathworks.com/help/images/ref/blockproc.html

I will have to think about how to do the parallel execution from the function.

Blockproc provides two 'padding' methods: replicate and symmetric. I guess what I need could be called margin, or overlap perhaps.

For the margin case it might make sense that such a function merely returns an array of block definitions, rather than blocks of pixel data. But this would not be so applicable for the replicate and symmetric cases I think.

R

On Saturday, August 31, 2013 6:49:31 PM UTC+2, Johannes Schönberger wrote: Hi Riaan,

Unfortunately we do not have (at least I do not know of) a function similar to Matlab's `blockproc`. Such feature would be a great addition to skimage!

Regards, Johannes

Am 31.08.2013 um 16:04 schrieb Riaan van den Dool :

...

Hi guys

I would like to use scikit-image to process large images, for example (5696, 13500).

In the interest of speed I need to divide the image into smaller sub-images with the possibility of processing these in parallel.

If I define the sub-images so that neighbouring sub-images overlap then edge effects should not be a problem for the algorithm operating on each sub-image.

This is probably a specific case of the more general border/edge-effect handling issue as addressed by the mode parameter here: http://docs.scipy.org/doc/scipy/reference/generated/scipy.ndimage.filters.co...

My questions: • Is there already a image-division function/strategy implemented in scikit-image? • Is this something that might be included in future if an implementation is available? • Please share any references to articles or code that deals with this. Riaan

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You also might want to look into joblib which makes it very easy to do parallel computations. This is used frequently in sklearn to speedup code. http://pythonhosted.org/joblib/ On Saturday, August 31, 2013 3:26:51 PM UTC-4, Riaan van den Dool wrote:

Thanks

On Saturday, August 31, 2013 8:17:25 PM UTC+2, Johannes Schönberger wrote:

...

Some hints:

- pad image with skimage.util.pad, which allows a large number of padding methods - spawn a pool of processes using Python's multiprocessing package in the standard library - use shared memory to provide read access to complete image - define slices of image blocks and add them to a processing queue

Am 31.08.2013 um 20:05 schrieb Riaan van den Dool :

...

The blockproc function's signature provides a useful starting point, thanks. http://www.mathworks.com/help/images/ref/blockproc.html

I will have to think about how to do the parallel execution from the function.

Blockproc provides two 'padding' methods: replicate and symmetric. I guess what I need could be called margin, or overlap perhaps.

For the margin case it might make sense that such a function merely returns an array of block definitions, rather than blocks of pixel data. But this would not be so applicable for the replicate and symmetric cases I think.

R

On Saturday, August 31, 2013 6:49:31 PM UTC+2, Johannes Schönberger wrote: Hi Riaan,

Unfortunately we do not have (at least I do not know of) a function similar to Matlab's `blockproc`. Such feature would be a great addition to skimage!

Regards, Johannes

Am 31.08.2013 um 16:04 schrieb Riaan van den Dool :

...

...

Hi guys

I would like to use scikit-image to process large images, for example

...

...

In the interest of speed I need to divide the image into smaller

sub-images with the possibility of processing these in parallel.

...

If I define the sub-images so that neighbouring sub-images overlap

(5696, 13500). then edge effects should not be a problem for the algorithm operating on each sub-image.

...

...

This is probably a specific case of the more general

border/edge-effect handling issue as addressed by the mode parameter here:

...

http://docs.scipy.org/doc/scipy/reference/generated/scipy.ndimage.filters.co...

...

My questions: • Is there already a image-division function/strategy

implemented in scikit-image?

...

• Is this something that might be included in future if an

implementation is available?

...

• Please share any references to articles or code that deals

with this.

...

Riaan

-- You received this message because you are subscribed to the Google Groups "scikit-image" group. To unsubscribe from this group and stop receiving emails from it, send an email to scikit-image...@googlegroups.com. For more options, visit https://groups.google.com/groups/opt_out.

-- You received this message because you are subscribed to the Google Groups "scikit-image" group. To unsubscribe from this group and stop receiving emails from it, send an email to scikit-image...@googlegroups.com. For more options, visit https://groups.google.com/groups/opt_out.