[virtuald]

We did our image processing in python using OpenCV in a single thread, and didn't have any lag problems. Here are some thoughts that may help:

• Memory allocation of large images can get expensive. Don't allocate new images each time you read something in. Instead, find the size of the image, allocate a numpy array to store the image, and process it. Reuse the same array each time you grab a new image. Similarly, when doing processing steps that return a new image (like splitting, or colorspace transforms, or whatever), allocate your buffers once, and reuse the same buffers over and over again by using the 'dst' parameter.
• Be wary of accessing too many non-local variables in python. In our robot code (which is running python), we found that accessing a lot of things at module level instead of local level caused noticeable slowness. Presumably this is because each time python needs to do multiple lookups in each scope to find things.
• Keep in mind that in python 2.7, because of the GIL multithreading doesn't buy you a lot unless you are I/O bound