Machine vision in Python

Question

I would like to perform a few basic machine vision tasks using Python and I'd like to know where I could find tutorials to help me get started.

As far as I know, the only free library for Python that does machine vision is PyCV (which is a wrapper for OpenCV apparently), but I can't find any appropriate tutorials.

My main tasks are to acquire an image from FireWire. Segment the image in different regions. And then perform statistics on each regions to determine pixel area and center of mass.

Previously, I've used Matlab's Image Processing Tootlbox without any problems. The functions I would like to find an equivalent in Python are graythresh, regionprops and gray2ind.

Thanks!

Answer 1

OpenCV is probably your best bet for a library; you have your choice of wrappers for them. I looked at the SWIG wrapper that comes with the standard OpenCV install, but ended up using ctypes-opencv because the memory management seemed cleaner.

They are both very thin wrappers around the C code, so any C references you can find will be applicable to the Python.

OpenCV is huge and not especially well documented, but there are some decent samples included in the samples directory that you can use to get started. A searchable OpenCV API reference is here.

You didn't mention if you were looking for online or print sources, but I have the O'Reilly book and it's quite good (examples in C, but easily translatable).

The FindContours function is a bit similar to regionprops; it will get you a list of the connected components, which you can then inspect to get their info.

For thresholding you can try Threshold. I was sure you could pass a flag to it to use Otsu's method, but it doesn't seem to be listed in the docs there.

I haven't come across specific functions corresponding to gray2ind, but they may be in there.