At WIDE IO, we are specialists in image processing and video analytics; we have individual experience using Python, Numpy and Scipy for Computer Vision applications since 2007. Now, the environment has become much mature. Our goal with this talk is to share our enthusiasm and to present the basic steps required to perform image and video pattern analysis with Python. In our tutorial, we’ll investigate how to build an action recognition framework and how to do video-tracking with traditional vision models based on a bag-of- keypoints. By going through examples, we’ll discuss how in practice computer vision for real-applications involve a trade-off between esthetical theories and utilitarianism. We will explore the various tricks that allow engineers to boost global performances, methods for running experiments and a mechanism for how to prepare the data... All these points are just a nice pretext to discuss our favorite tools: Numpy and Scipy of course, but also more exotic ones such as MediaLovinToolkit, PyCUDA, Bob and PyCVF... At the end of the talk, we’ll conclude by briefly discussing future imperatives, especially with respect to mobility and cloud computing.