FastAPI OCR Application

This project is a FastAPI application that provides OCR (Optical Character Recognition) capabilities for both images and PDFs. It uses Tesseract OCR to extract text and can handle tables in images and PDFs.

Usage

This application features a user interface that allows you to upload images or PDF files and receive the extracted text in JSON format.

1. main.py

This file contains the FastAPI application and defines the routes for handling image and PDF uploads.

Routes

• /ocr-image/

  • Method: POST
  • Description: Accepts an image file and returns the extracted text and tables.
  • Request Body: Image file (form-data).
  • Response: JSON containing the extracted text and tables.

• /ocr-pdf/

  • Method: POST
  • Description: Accepts a PDF file and returns the extracted text and tables.
  • Request Body: PDF file (form-data).
  • Response: JSON containing the extracted text and tables.

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2. image_processing.py

This module provides functions for OCR and table extraction from images.

Functions

• ocr_image(image_data: bytes) -> str

  • Takes image data as input and returns the extracted text as a string.

• extract_table_from_img(image_data: bytes) -> list

  • Takes image data as input and returns a list of extracted table data.

---

3. pdf_processing.py

This module provides functions for OCR and table extraction from PDF files.

Functions

• ocr_pdf(pdf_data: bytes) -> str

  • Takes PDF data as input and returns the extracted text as a string.

• extract_table_from_pdf(pdf_data: bytes) -> list

  • Takes PDF data as input and returns a list of extracted table data.

Features

• OCR for Images: Extract text from standard images and images containing tables.
• OCR for PDFs: Extract text and tables from PDF files.
• UI Design: Separate files for handling image and PDF processing.

Directory Structure

OCR/
├── main.py
├── image_processing.py
├── pdf_processing.py
└── index.html
└── asset/
    ├── img.png
    ├── lorem.pdf
    ├── table_img.jpg
    ├── table_pdf.pdf
└── static/
    └── style.css
└── README. md

Installation Guide

Follow these steps to set up the FastAPI OCR application:

Prerequisites

Ensure you have the following installed on your system:

• Python 3.7 or higher
• Tesseract OCR (Make sure to note the installation path)

Steps to Install

1. Clone the Repository: Open your terminal and run the following command to clone the repository

   git clone https://github.com/dagimgetaw/OCR.git
   cd OCR
   

2. Set Up a Virtual Environment (Optional but Recommended): Create a virtual environment to manage dependencies

   python -m venv venv

Activate the virtual environment:

• For Windows: venv\Scripts\activate
• For macOS/Linux: source venv/bin/activate

3. Install Requirements: Install the necessary dependencies using pip

    pip install -r requirements.txt
   

4. Tesseract Installation: Make sure Tesseract OCR is installed on your system. You can download it from: Tesseract OCR

After installation, set the tesseract_cmd path in your code: python

For Windows

pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe'

For macOS

pytesseract.pytesseract.tesseract_cmd = '/usr/local/bin/tesseract'

Linux

pytesseract.pytesseract.tesseract_cmd = '/usr/bin/tesseract'

3. Run the Application: Start the FastAPI application using the following command Inside the directory: uvicorn main:app --host 0.0.0.0 --port 8000

4. Access the Application: Access the application at http://localhost:8000.

Requirements

Make sure you have the following installed:

• Docker
• Tesseract OCR (included in the Dockerfile)
• FastAPI
• OpenCV
• pdfplumber
• pdf2image

License

This project is licensed under the MIT License. See the LICENSE file for details.