Computer vision is a complex field that spans industries with varying needs and implementations. Scikit-Image is a library that provides tools and techniques for people working in the sciences to process the visual data that is critical to their research. This week Stefan Van der Walt and Juan Nunez-Iglesias, co-authors of Elegant SciPy, talk about how the project got started, how it works, and how they are using it to power their experiments.
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- Your host as usual is Tobias Macey and today I am interviewing Stefan van der Walt and Juan Nunez-Iglesias, co-authors of Elegant SciPy, about scikit-image
- How did you get introduced to Python?
- What is scikit-image and how did the project get started?
- How does its focus differ from projects like SimpleCV/OpenCV or Pillow?
- What are some of the common use cases for which the scikit-image package is typically employed?
- What are some of the ways in which images can exhibit higher dimensionality and what are some of the kinds of operations that scikit-image can perform in those situations?
- How is scikit designed and what are some of the biggest challenges associated with its development, whether in the past, present, or future?
- What are some of the most interesting use cases for scikit-image that you have seen?
- What do you have planned for the future of scikit-image?
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- SciPy Conference
- Minimum Cost Paths
- Image Stitching Tutorial
- Elegant SciPy