Run Vision AI on Live Video Feeds via WebRTC
In this video, we introduce the Roboflow Serverless Streaming API, the simplest and easiest way to run computer vision on live cameras.
Traditionally, processing live video meant choosing between managing edge hardware (low latency but high maintenance) or scaling dedicated cloud servers (hard to manage for burst traffic). The new Serverless Streaming API solves this by using WebRTC to let you stream video directly to the cloud, where it is processed by your custom models and workflows in real-time.
What you’ll see in this video:
Reviewing deployment options: Edge vs. Dedicated Cloud vs. Serverless.
Serverless Streaming: How the new API facilitates auto-scaling video inference.
Python & JS SDKs: How to integrate live vision into web and mobile apps with just a few lines of code.
Live Demos: See it working on a webcam, RTSP stream, and even a mobile iOS app for exercise tracking.
Chapters
00:00 - Intro: Computer Vision on Live Video
01:29 - Choosing Infrastructure: Edge vs. Cloud
03:10 - Roboflow Cloud Options (Serverless vs. Dedicated vs. Batch)
05:13 - Introducing the Serverless Streaming API
07:30 - How it Works: WebRTC & Architecture
09:50 - Demo 1: JavaScript SDK & Webcam (Object Counting)
12:40 - Demo 2: Python SDK with RTSP Streams
14:43 - Demo 3: Mobile App (iOS Squat Counter)