Validate Actions with Vision AI | Building a Web App for Real-Time Drinking Detection
Join Roboflow Engineer Riaz Virani as he shares a fun and practical computer vision application, Hydrovisor, which validates the simple human action of drinking water for real-time, automated hydration tracking. We use this as an example to illustrate how computer vision applications can run in edge devices and assist with real-time action validation.
Chapters:
00:00 Introduction: AI-Powered Hydration Reminders
01:58 Demonstration: Hydrovisor - RF-DETR in a Web Browser
05:48 Background: Why Build the Hydrovisor App & Reviewing Open Source Tools
09:10 Parsing Actions for a Computer to Underst…
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Chapters (11)
Introduction: AI-Powered Hydration Reminders
1:58
Demonstration: Hydrovisor - RF-DETR in a Web Browser
5:48
Background: Why Build the Hydrovisor App & Reviewing Open Source Tools
9:10
Parsing Actions for a Computer to Understand Them
17:37
Data Collection and Training a Custom Model to Recognize Cups
23:42
Validating Actions with AI in Industrial Settings - How Would You Start?
24:53
Deploying with Inference.js and Considerations for Edge Devices
28:34
Designing Computer Vision Solutions for Industrial Applications
36:30
Handling Latency and Re-Training the Model
40:49
Dataset Preparation Tips for Reducing False Positives
45:49
Conclusion
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