Optical-Text-AI-Extractor

This Python Script is a RESTful API built using Flask. It provides Optical Character Recognition (OCR) services, allowing users to extract text from PDF files and images. The OCR functionality is implemented using the pytesseract library, which is a Python wrapper for Google's Tesseract-OCR Engine, and OpenCV (cv2) for image processing.

OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products. It has C++, Python, Java and MATLAB interfaces and supports Windows, Linux, Android and Mac OS.

Tesseract is an open-source OCR engine that uses machine learning to recognize and read text in various languages from images and PDF files. It was initially developed by HP and then open-sourced in 2005. Google has been sponsoring the project since 2006, and it's currently considered one of the most accurate open-source OCR engines available. Tesseract supports a wide variety of image formats and can recognize more than 100 languages out of the box.

The pdf2image library is used to convert PDF files into images for OCR processing.

Getting Started

Prerequisites

Windows

Create a virtual environment:

python -m venv myenv

Activate the virtual environment:

myenv\Scripts\activate

Linux

Install venv

sudo apt install python3.10-venv

Create a virtual environment:

python3 -m venv myenv

Activate the virtual environment:

source myenv\bin\activate

To run this application, you will need to have the following installed:

• Python 3
• Flask
• Flask-CORS
• OpenCV (cv2)
• pytesseract
• pdf2image
• Gunicorn (Linux)
• Werkzeug (Windows) and others

You can install these using pip:

pip install -r requirements.txt

Running the Application

To run the application in production, use the following command:

For Windows:

cd src
waitress-serve --listen=*:8000 main:app

Using Gunicorn (Does not work in Windows):

gunicorn -w 4 src.main:app

The application will start and listen for HTTP requests on http://localhost:8000

Key Functions

• check_api(): This function is mapped to the root URL ("/") and returns a message indicating that the API is running.

• require_api_key(view_function): This function is a decorator that checks if the API key in the request header matches the one stored in the environment variables. If not, it aborts the request with a 401 error.

• pdf_to_img_base64(pdf_file): This function takes a path to a PDF file in base64 as input and returns a list of images extracted from the PDF file.

• ocr_core(file): This function takes an image as input and uses the Tesseract-OCR Engine to extract and return the text from the image.

• ocr_pdf_base64(): This function is mapped to the "/pdf" URL and handles POST requests. It receives a PDF file, saves it to a local path, converts the PDF into a list of images, performs OCR on each image using the Tesseract-OCR Engine, and returns the extracted text as a JSON response.

• ocr_image(): This function is mapped to the "/image" URL and handles POST requests. It receives an image file, saves it to a local path, performs OCR on the image using the Tesseract-OCR Engine, and returns the extracted text.

Example Usage

To extract text from a PDF file, send a POST request to the "/pdf-base64" URL with the PDF file attached. The response will be a JSON object containing the extracted text from each page of the PDF.

To extract text from an image, send a POST request to the "/image" URL with the image file attached. The response will be the extracted text from the image.

Security

The application uses an API key for authentication. The API key is stored in an environment variable and is required in the header of every request. Unauthorized requests will be rejected with a 401 error.