Intro to Computer Vision: Building Object Detection Models and Datasets
Build your own object detection model from start to finish. Includes step-by-step instructions on data annotation and model training.
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 workshop we’ll cover:
High level computer vision applications & concepts
How to label your own dataset for object detection & computer vision
How to train your model using a Faster R-CNN in python & detectron2 (A PyTorch based modular object detection library)
Run the model for object detection on images & video
What you’ll need:
A modern web browser
A Google account (Colab is a tool made by Google)
Sign up free for Sense Data Annotation (https://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’s not required. We encourage anyone who is curious to attend and ask questions!
About the instructor:
Sage Elliott will be leading this workshop. He’s passionate about making AI approachable for everyone and loves building things with technology. Connect with Sage on LinkedIn: https://www.linkedin.com/in/sageelliott/
Sixgill makes AI easy and accessible for all, so all can benefit. We provide an industry-first AI platform for end-to-end computer vision and machine learning lifecycle management. All in one powerful yet simplified interface, users of the Sixgill Sense platform get integrated tools for camera/device management, data annotation, model creation, and flexible edge, cloud, on-premise, or hybrid deployment. Sixgill accelerates and streamlines the success of AI-powered computer vision applications at any scale. Read more at https://sixgill.com/ or contact Sixgill for any questions at https://sixgill.com/contact/