Speaker
Description
The Segment Anything Model (SAM) by Meta is a transformer model trained on 11 million images and 1.1 billion masks, known for its exceptional generalization and zero-shot segmentation capabilities. In under a year, SAM has been cited in over 2,500 papers and has been widely adopted for specialized tasks like medical imaging and microscopy. This proposed course will provide hands-on guidance for installing and running SAM on Google Colab, exploring its model parameters, and learning to interpret and utilize its output effectively. While various plugins exist, Python remains a powerful tool, providing users with greater control over the entire segmentation process. The course will primarily focus on Python but will also introduce some published plugins to participants, ensuring a comprehensive understanding of SAM's application and versatility.
| Target audience | Beginner users, Intermediate users, Advanced users, Beginner developers, Intermediate developers |
|---|---|
| Keywords | Image segmentation, Zero-shot segmentation, Transformer model, Microscopy images, Python, Google Colab |
