In research and development (R&D), interactive computing environments are a frequently employed alternative for data exploration, algorithm development and prototyping. In the last twelve years, a popular scientific computing environment flourished around the Python programming language. Most of this environment is part of (or built over) a software stack named the SciPy Stack. Combined to the OpenCV’s Python interface, this environment becomes an alternative for current computer vision R&D. This tutorial introduces such an environment and shows how it can address different steps on computer vision research, from initial data exploration to parallel computing implementations. Several code examples are presented, addressing problems from simple image processing to inference by machine learning.
This tutorial was presented for the first time at SIBGRAPI 2014 in Rio de Janeiro.
IPython Notebooks on GitHub for download
IPython Notebooks on Nbviewer for visualization