These labs using python are based on scikit-image tutorials.
Modified and extended for the class CCOM4995 Topics in Computer Science: Computer Vision at University of Puerto Rico, Río Piedras campus, by Rémi Mégret, 2017.
Other materials will be shared on Moodle.
A collection of tutorials for the scikit-image package.
Installation instructions can be found in lectures/0_preparation.md
Start the notebook server from the same directory as this README with:
jupyter notebook
Then select the jupyter notebook that you are interested in from the lectures directory.
See the viewer_examples directory for GUI demos.
Refer to the gallery as well as scikit-image demos for more examples.
These usage guidelines are based on goodwill. They are not a legal contract.
The scikit-image team requests that you follow these guidelines if you use these materials in downstream projects.
All materials in this repository are available free of restriction under the Creative Commons CC0 1.0 Universal Public Domain Dedication (see LICENSE.txt).
However, we request that you actively acknowledge and give attribution to this repo and to the authors if you reproduce them or create any derivative works.
For more information on these guidelines, which are sometimes known as CC0 (+BY), see this blog post by Dan Cohen.
Note that some images in the image/ directory may have their own
sharing rules, as described in the associated *_credits.txt file
located beside them.