This seminar is hosted by SF Bay ACM Chapter and Silicon Valley ACM SIGGRAPH
Join this hands-on workshop to get started with computer vision and object detection.
Build your own object detection model from start to finish. Includes step-by-step instructions on data annotation and model training with your own dataset.
Object classification and localization within an image is foundational to many computer vision applications.
In this 2-hour hands-on, interactive workshop, We will cover:
High level computer vision applications & concepts
How to label your own dataset for object detection & computer vision
How to train your model using python & detectron2 (A PyTorch based modular object detection library)
Run the model for object detection on images & video
What you will need:
A modern web browser (like Chrome)
A Google account (Colab is a tool made by Google)
Sign up free for Sense Data Annotation (http://sixgill.tech/ai-powered-labeling)
Who should attend:
Anyone interested in computer vision! This workshop is designed to be approachable for most skill levels. Knowing some python programming will help, but it is not required.
We encourage anyone who is curious to attend and ask questions!
Sage Elliott (Sixgill)
Sage Elliott is a Machine Learning Developer for Sixgill (https://sixgill.com/) with over 10 years of experience in the engineering space. He has passion for exploring new technologies and building communities.