Question

I’ve been working on a PyOpenCL program that will take in an OpenCL kernel (representing an image filter) and an image and apply said filter to generate an output image. The issue is that I need to make this program run on an image of any size.

I’ve written a similar program before with C# and OpenCL using the Cloo (http://sourceforge.net/projects/cloo/) framework, but I wanted to make something more portable (since the Cloo framework fails to run properly on Linux).

Now, in my C# implementation, I simply split the image up into chunks and ran the kernel on each chunk. I did this by handling the images as plain byte arrays in my kernel. However, the issue I’m having now is that I’m attempting to use the image2d_t datatype in my PyOpenCL implementation, and I’m not sure how to go about breaking the image into chunks and passing them to the kernel.

Does the image2d_t class add padding to the returned images (that I would need to post-process), or perhaps it supports some sort of automated methodology that would handle this for me?

Any resources that would point me in the right direction are greatly appreciated!

Edit: I figured I should mention that the reason why I want to do this is because I run into memory allocation exceptions with my current build (because the images are too large).

Answer 1

I managed to work around it by splitting the image up using the Python Imaging Library’s crop and paste functionality to process subimages and replace them into the output image after processing.