Chicago Computer Vision Meetup

https://voxel51.com/computer-vision-events/getting-started-with-fiftyone-workshop-dec-4-2024/

About the workshop

Want greater visibility into the quality of your computer vision datasets and models? Then join Harpreet Sahota, Hacker in Residence and Machine Learning Engineer at Voxel51, for this free 90-minute, hands-on workshop to learn how to leverage the open source FiftyOne computer vision toolset.

In the first part of the workshop we’ll cover:

• FiftyOne Basics (terms, architecture, installation, and general usage)
• An overview of useful workflows to explore, understand, and curate your data
• How FiftyOne represents and semantically slices unstructured computer vision data

The second half will be a hands-on introduction to FiftyOne, where you will learn how to:

• Load datasets from the FiftyOne Dataset Zoo
• Navigate the FiftyOne App
• Programmatically inspect attributes of a dataset
• Add new sample and custom attributes to a dataset
• Generate and evaluate model predictions
• Save insightful views into the data

Prerequisites are a working knowledge of Python and basic computer vision. All attendees will get access to the tutorials, videos, and code examples used in the workshop.

About the Instructor

Harpreet Sahota is a hacker-in-residence and machine learning engineer with a passion for deep learning and generative AI. He’s got a deep interest in RAG, Agents, and Multimodal AI.

https://voxel51.com/computer-vision-events/ai-machine-learning-computer-vision-meetup-dec-12-2024/

How We Built CoTracker3: Simpler and Better Point Tracking by Pseudo-Labeling Real Videos

CoTracker3 is a state-of-the-art point tracking model that introduces significant improvements in tracking objects through video sequences. Its key innovations include:

• Uses semi-supervised training with real videos, reducing reliance on synthetic data1
• Generates pseudo-labels using existing tracking models as teachers1
• Features a simplified architecture compared to previous trackers

About the Speaker

Nikita Karaev is currently doing a PhD at Meta AI and Oxford, where he’s working on dynamic reconstruction and motion estimation (CoTracker) with Andrea Vedaldi and Christian Rupprecht. Before that, he did his master’s at École Polytechnique (Paris), and undergrad in cold Siberia (Novosibirsk). He was also an early employee at two startups that got acquired by Snapchat and Farfetch.

Hands-On with Meta AI's CoTracker3: Parsing and Visualizing Point Tracking Output

In this presentation, Harpreet Sahota explores CoTracker3, a state-of-the-art point tracking model that effectively leverages real-world videos during training. He dives into the practical aspects of running inference with CoTracker3 and parsing its output into FiftyOne, a powerful open-source tool for dataset curation, analysis, and visualization. Through a hands-on demonstration, Harpreet shows how to prepare a video for inference, run the model, examine its output, and parse the model’s output into FiftyOne’s keypoint format for seamless integration and visualization within the FiftyOne app.

About the Speaker

Harpreet Sahota is a hacker-in-residence and machine learning engineer with a passion for deep learning and generative AI. He’s got a deep interest in RAG, Agents, and Multimodal AI.

Streamlined Retail Product Detection with YOLOv8 and FiftyOne

In the fast-paced retail environment, automation at checkout is increasingly essential to enhance operational efficiency and improve the customer experience.

This talk will demonstrate a streamlined approach to retail product detection using the Retail Product Checkout (RPC) dataset, which includes 200 SKUs across 17 meta-categories such as puffed food, dried food, and drinks.

By leveraging YOLOv8, renowned for its speed and accuracy in real-time object detection, and FiftyOne, an open-source toolset for computer vision, we can simplify data loading, training, evaluation, and visualization for effective product detection and classification. Attendees will gain insights into how these tools can be applied to optimize checkout automation.

About the Speaker

Vanshika Jain is a Data Engineer Intern at UNAR Labs, a startup focused on making information accessible for the blind. She holds a Master’s degree in Machine Learning and Computer Vision from Northeastern University and is passionate about applying AI and computer vision to real-world problems, with a focus on automation and accessibility.

Register for the Zoom

Date and Time

Jan 29, 2025 at 9 AM Pacific / Noon Eastern

Is AI Creating a Whole New Earth-Aware Geospatial Stack? Promises and Challenges

The latest wave of AI innovation is profoundly changing many domains. In remote sensing, despite efforts like ours at Clay and others, it is been less so. In this talk we will share our experience as we realize, and explore, if geoAI represents a whole new stack to work with Earth data.

About the Speaker

Dr. Bruno Sanchez-Andrade Nuno is the executive director of the non-profit project Clay, an AI model for remote sensing. Previously, Bruno has had more than a decace of operational geosptatial system like director of the Planetary Computer at Microsoft, Big Data innovations at the World Bank, and Chief Scientist at Mapbox.

Evaluating the Satlas and Clay Remote Sensing Foundational Models

Geospatial and Earth Observation have benefited from the new advances in computer vision. In this talk we are going to evaluate the accuracy and ease of use for two of these great new models – the Satlas and Clay foundational models. The evaluation will look at distinct different areas on the globe. Come see how this gift of foundational models improves your work in geospatial or Earth observation analysis.

About the Speaker

Steve Pousty is a dad, partner, son, a founder, and a principal developer advocate at Voxel51. He can teach you about Computer Vision, Data Analysis, Java, Python, PostgreSQL, Microservices, and Kubernetes. He has deep expertise in GIS/Spatial, Remote Sensing, Statistics, and Ecology. Steve has a Ph.D. in Ecology and can be bribed with offers of bird watching or fly fishing.

Earth Monitoring for Everyone with Earth Index

Earth Index is a end user focused application that preprocesses global imagery through AI foundation models to enable rapid in-browser search and monitoring. Earth Genome builds Earth Index for critical applications in the environment, and is being used today to report on illegal airstrips built in the Peruvian Amazon, track cattle factory farms across the planet for emissions modeling, and expose illegal gold mining in the Yanomami Indigenous Territory

About the Speaker

Mikel Maron works on open technology for the earth. He leads product development and sets organizational pace at Earth Genome. Previously, Mikel led corporate social responsibility at Mapbox, elevated open mapping in the federal government as a Presidential Innovation Fellow, and founded community mapping initiatives notably Map Kibera through Ground Truth Initiative. He has a long association with the OpenStreetMap project, founding Humanitarian OpenStreetMap Team in 2005 and serving many years on the OSM Foundation Board.