Search⌘ K
AI Features
Home
Courses
Getting Started with Image Classification with PyTorch

HTTP Methods

Explore how to deploy image classification models using FastAPI by implementing HTTP GET and POST methods. Understand safe and idempotent GET requests, configure CORS, and handle image uploads through POST to build effective REST APIs.

We'll cover the following...

HTTP GET is a request method to retrieve data from the server. An HTTP GET method should have the following characteristics:

  • Safe: It doesn’t change or modify the state of the server.
  • Idempotent: It doesn’t result in any side effects for the server.
  • Cacheable: It allows caching of the HTTP response.

Note: All safe methods are also idempotent.

We can easily build a simple HTTP GET API with the FastAPI framework.

Import

Start by adding the following import statements:

Python
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
app = FastAPI(
    title="Image Classification API",
    description="Working demo for building HTTP GET API server.",
    version="0.0.1"
)
print('The title of the application is:', app.title)

Cross-origin resource sharing (CORS)

CORS allows a frontend to load resources from a backend with a different origin. The implementation for CORS in FastAPI is as follows:

  1. Import the
...