Meta’s Segment Anything Model (SAM) is a new and open-source computer vision model for image segmentation. It is as revolutionary to images as ChatGPT is to conversational text! It was trained on a large data set including 11 million images licensed from “a large photo company” and 1.1 billion segmentation masks produced by its segmentation model.

It’s amazing to see how easy it is to pick it up and build something quickly around it! The article below provides a brilliant tutorial for setting up and trying this model very quickly (15 mins or less)!

The steps are outlined below:

  1. I used Google Colab notebook with a Free GPU.
  2. I used Metaseg (MetaSeg is a post-processing tool for quantifying the reliability of semantic segmentation neural networks).
  3. I picked a .png image and had SAM segment it.
  4. The article below shows you how to display the final result!

ByteXD