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Building Data Science Applications with FastAPI

You're reading from   Building Data Science Applications with FastAPI Develop, manage, and deploy efficient machine learning applications with Python

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Product type Paperback
Published in Oct 2021
Publisher Packt
ISBN-13 9781801079211
Length 426 pages
Edition 1st Edition
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Author (1):
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François Voron François Voron
Author Profile Icon François Voron
François Voron
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Table of Contents (19) Chapters Close

Preface 1. Section 1: Introduction to Python and FastAPI
2. Chapter 1: Python Development Environment Setup FREE CHAPTER 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 Injections in FastAPI 7. Section 2: Build and Deploy 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. Section 3: Build a Data Science API with Python and FastAPI
14. Chapter 11: Introduction to NumPy and pandas 15. Chapter 12: Training Machine Learning Models with scikit-learn 16. Chapter 13: Creating an Efficient Prediction API Endpoint with FastAPI 17. Chapter 14: Implement a Real-Time Face Detection System Using WebSockets with FastAPI and OpenCV 18. 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 it 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:

  1. 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 using which 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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