Detect Objects in a Serverless Twilio Video App with TensorFlow.js

This article provides a step-by-step guide on how to detect objects in a Twilio Programmable Video application using TensorFlow.js, a popular open-source machine learning library. The setup includes creating an account with Twilio and generating API Key SID and API Key Secret. The process involves importing TensorFlow.js and the coco-ssd model into the video.html file to detect objects defined in the COCO dataset. An estimate function is then created to load the model, get predictions, and pass those predictions to a renderPredictions function that displays the predictions along with a bounding box on the video canvas. The final code is provided for both assets/video.html and assets/index.js files. The author suggests potential applications of this technique such as building collaborative games or detecting mask-usage in videos.