Implement OCR API Using FastAPI - 1
Learn how to create a REST API that performs OCR on multiple images concurrently using FastAPI.
We'll cover the following
Create a virtual environment for our API
It is a best practice to create a virtual environment whenever you create a new project. You can follow one of the two options below:
-
Using the Anaconda Prompt:
-
Start the Anaconda Prompt.
-
Run the following command:
conda create -n env_name python=3.7
You can specify any
env_name
you like and the desiredPython
version. -
Activate your virtual environment by running the following command:
conda activate env_name
-
Your environment is now activated and you can install whichever packages you need in this virtual environment.
-
-
Using venv package:
-
Start the Command Prompt.
-
If you do not have
venv
installed, you need to first install it by running the command shown below:pip install venv
-
Then, run the following command to create the virtual environment:
python3 -m venv path\env_name
You can specify any
env_name
you like. You need to specify the path where you want to store the files for your environment. By default, it will take the current directory. -
Activate your virtual environment by running the following command:
path\env_name\Scripts\activate
-
Your environment is now activated and you can install whichever packages you need in this virtual environment.
-
Create the default GET
route
The first step in creating our REST API
is to define a default (home) route that performs a GET
operation. Whenever anyone tries to go the URL:
http://localhost:8000/
we will just give a JSON response as shown below:
{
"message" : "Visit the endpoint: /api/v1/extract_text to perform OCR."
}
This means that the actual OCR
operation is going to perform at the URL:
http://localhost:8000/api/v1/extract_text
with a request body containing the multipart/form-data
, i.e., the images.
Note that we are going to pass multiple images in a single call, and our
API
should give the response in the form shown below:
{
"image_name": "extracted_text"
}
Let’s first create the default GET
route.
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