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International Symposium on Visual Computing - Tutorial on Computer Vision in 3D

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Analysis and visualization of 3D data in Python - ISVC '19

Binder

  1. Follow the preparation instructions
  2. Start the notebook server from the same directory as this README with jupyter notebook

Objectives:

a) a brief overview of scikit-image and related packages in the scientific Python ecosystem, including how to create your environment;

b) filtering, segmentation and data extraction of large 2D and 3D images;

c) exploration and visualization of large 2D and 3D images;

d) inspection, counting, and measuring attributes of objects; routines that extract shape, color and texture features; how to use topological description to calculate equidistant boundaries;

e) data reduction algorithms using priors from image acquisition instruments and/or sample architecture;

f) parallel data processing pipelines for accelerating image analysis.

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