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, th

Answer 1

I don't know much about this package Motmot or how it compares to OpenCV, but I have imported and used a class or two from it. Much of the image processing is done via numpy arrays and might be similar enough to how you've used Matlab to meet your needs.

Answer 2

I've started a website on this subject: pythonvision.org. It has some tutorials, &c and some links to software. There are more links and tutorials there.

Answer 3

Foreword: This book is more for people who want a good hands on introduction into computer or machine vision, even though it covers what the original question asked.

[BOOK]: Programming Computer Vision with Python

At the moment you can download the final draft from the book's website for free as pdf:

http://programmingcomputervision.com/

From the introduction:

The idea behind this book is to give an easily accessible entry point to hands-on computer vision with enough understanding of the underlying theory and algorithms to be a foundation for students, researchers and enthusiasts.

What you need to know

• Basic programming experience. You need to know how to use an editor and run scripts, how to structure code as well as basic data types. Familiarity with Python or other scripting style languages like Ruby or Matlab will help.
• Basic mathematics. To make full use of the examples it helps if you know about matrices, vectors, matrix multiplication, the standard mathematical functions and concepts like derivatives and gradients. Some of the more advanced mathe- matical examples can be easily skipped.

What you will learn

• Hands-on programming with images using Python.
• Computer vision techniques behind a wide variety of real-world applications.
• Many of the fundamental algorithms and how to implement and apply them your- self.

Answer 4

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.

Answer 5

You probably would be well served by SciPy. Here is the introductory tutorial for SciPy. It has a lot of similarities to Matlab. Especially the included matplotlib package, which is explicitly made to emulate the Matlab plotting functions. I don't believe SciPy has equivalents for the functions you mentioned. There are some things which are similar. For example, threshold is a very simple version of graythresh. It doesn't implement "Otsu's" method, it just does a simple threshold, but that might be close enough.

I'm sorry that I don't know of any tutorials which are closer to the task you described. But if you are accustomed to Matlab, and you want to do this in Python, SciPy is a good starting point.

Answer 6

I've acquired image from FW camera using .NET and IronPython. On CPython I would checkout ctypes library, unless you find any library support for grabbing.