The Data Carpentry: Image Processing with Python workshop will teach the fundamental concepts and skills needed to load, edit, and analyse image data with the Python programming language.
The workshop uses the scikit-image library to teach these skills, and is taught within a Jupyter environment. The material includes many different example images, including plants, bacterial colonies, and household objects, which are intended to be accessible to learners from a diverse range of backgrounds.
In addition to the standard Carpentries curriculum we will cover an additional non-official episode focussing on multidimensional data visualisation and analysis with Napari - a fast interactive image viewer for Python.
Difficulty rating: ★★★☆ Intermediate
Who is it for?
- Both research staff and research students
- Users who are already familiar with the basics of Python
Summary of the topics covered
- How images are stored digitally,
- How these files can be loaded and represented in Python,
- How to select and edit regions in an image,
- How to handle noise in image data,
- How to select pixels in an image based on their properties, and
- How to automatically identify and analyse objects within an image.
Prerequisites
Either attendance at Software Carpentry - Python or previous experience in using Python is required.
Frequency
2 times a year
Duration
8 hours
Next course
TBC.
Can't attend?
We don’t have online materials for this session, but the course will run again — so you’ll be very welcome to join next time.