FastAI Image Segmentation
source link: https://www.tuicool.com/articles/hit/uEFZJrQ
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Image segmentation is the process of taking a digital image and segmenting it into multiple segments of pixels. The goal of image segmentation is to simplify and/or change the representation of an image into something more meaningful and easier to understand.
The FastAI library allows us to build image segmentation models using only a few lines of code by providing us with classes and methods for both loading in the data and creating a model to perform the segmentation( UNET ).
If you are unfamiliar with the FastAI library I would highly recommend that you check out the Practical Deep Learning for Coders course which is really awesome and not only teaches you about the library but also about the technologies and practices used to make the library great.
In this article, we will go over where we can get image segmentation data, how we could create our own data as well as what a U-NET is and how we can use for image segmentation.
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