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Building Data Science Applications with FastAPI - Second Edition

You're reading from  Building Data Science Applications with FastAPI - Second Edition

Product type Book
Published in Jul 2023
Publisher Packt
ISBN-13 9781837632749
Pages 422 pages
Edition 2nd Edition
Languages
Author (1):
François Voron François Voron
Profile icon François Voron

Table of Contents (21) Chapters

Preface 1. Part 1: Introduction to Python and FastAPI
2. Chapter 1: Python Development Environment Setup 3. Chapter 2: Python Programming Specificities 4. Chapter 3: Developing a RESTful API with FastAPI 5. Chapter 4: Managing Pydantic Data Models in FastAPI 6. Chapter 5: Dependency Injection in FastAPI 7. Part 2: Building and Deploying a Complete Web Backend with FastAPI
8. Chapter 6: Databases and Asynchronous ORMs 9. Chapter 7: Managing Authentication and Security in FastAPI 10. Chapter 8: Defining WebSockets for Two-Way Interactive Communication in FastAPI 11. Chapter 9: Testing an API Asynchronously with pytest and HTTPX 12. Chapter 10: Deploying a FastAPI Project 13. Part 3: Building Resilient and Distributed Data Science Systems with FastAPI
14. Chapter 11: Introduction to Data Science in Python 15. Chapter 12: Creating an Efficient Prediction API Endpoint with FastAPI 16. Chapter 13: Implementing a Real-Time Object Detection System Using WebSockets with FastAPI 17. Chapter 14: Creating a Distributed Text-to-Image AI System Using the Stable Diffusion Model 18. Chapter 15: Monitoring the Health and Performance of a Data Science System 19. Index 20. Other Books You May Enjoy

Sending a stream of images from the browser in 
a WebSocket

In this section, we’ll see how you can capture images from the webcam in the browser and send them through a WebSocket. Since it mainly involves JavaScript code, it’s admittedly a bit beyond the scope of this book, but it’s necessary to make the application work fully.

The first step is to enable a camera input in the browser, open the WebSocket connection, pick a camera image, and send it through the WebSocket. Basically, it’ll work like this: thanks to the MediaDevices browser API, we’ll be able to list all the camera inputs available on the device. With this, we’ll build a selection form so the user can select the camera they want to use. You can see the concrete JavaScript implementation in the following code:

script.js

window.addEventListener('DOMContentLoaded', (event) => {  const video = document.getElementById('video');
 ...
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