Advanced OCR with Tesseract

Abstract

Advanced OCR with Tesseract is a Python project that leverages the Tesseract OCR engine for high-accuracy Optical Character Recognition. The application performs image preprocessing, text extraction, and post-processing, demonstrating the use of open-source OCR for document analysis.

Prerequisites

Python 3.8 or above
A code editor or IDE
Basic understanding of image processing
Required libraries: pytesseract, opencv-python, Pillow
Tesseract OCR installed (installation guide)

Before you Start

Install Python, Tesseract, and the required libraries:

Install dependencies

pip install pytesseract opencv-python pillow

Getting Started

Create a Project

Create a folder named advanced-ocr-tesseract.
Open the folder in your code editor or IDE.
Create a file named advanced_ocr_with_tesseract.py.
Copy the code below into your file.

diagram how the pieces call each other mermaid

  flowchart TD
  n0(["script start"])
  n1["batch_ocr()"]
  n2["main()"]
  n3["ocr_image()"]
  n4["preprocess_image()"]
  n0 --> n2
  n1 --> n3
  n2 --> n1
  n2 --> n3
  n3 --> n4

Derived from projects/advance/advanced_ocr_with_tesseract.py by parsing it, not by hand. Arrows are calls between the file's own functions and methods; library calls are left out, and only calls the parser could resolve with certainty are shown.

Write the Code

Advanced OCR with Tesseract

pch.viewSource

Advanced OCR with Tesseract

"""
Advanced OCR with Tesseract

This project demonstrates advanced Optical Character Recognition (OCR) using Tesseract and Python. It supports multi-language recognition, image preprocessing, batch processing, and saving results to text files. Includes CLI for batch and single image OCR.

Requirements:
pip install pytesseract pillow
Make sure Tesseract is installed and in your PATH

Example usage:
python advanced_ocr_with_tesseract.py --image sample.png --lang eng --out result.txt
python advanced_ocr_with_tesseract.py --folder images/ --lang eng --out results/
"""
import pytesseract
from PIL import Image, ImageFilter, ImageEnhance
import os
import argparse

def preprocess_image(image_path):
    try:
        img = Image.open(image_path)
        img = img.convert('L')
        img = img.filter(ImageFilter.MedianFilter())
        enhancer = ImageEnhance.Contrast(img)
        img = enhancer.enhance(2)
        return img
    except Exception as e:
        print(f"Error processing {image_path}: {e}")
        return None

def ocr_image(image_path, lang='eng', out_path=None):
    img = preprocess_image(image_path)
    if img is None:
        return ""
    text = pytesseract.image_to_string(img, lang=lang)
    if out_path:
        with open(out_path, 'w', encoding='utf-8') as f:
            f.write(text)
    return text

def batch_ocr(folder, lang='eng', out_folder=None):
    results = {}
    for filename in os.listdir(folder):
        if filename.lower().endswith(('.png', '.jpg', '.jpeg', '.tiff')):
            path = os.path.join(folder, filename)
            out_path = None
            if out_folder:
                os.makedirs(out_folder, exist_ok=True)
                out_path = os.path.join(out_folder, filename + '.txt')
            results[filename] = ocr_image(path, lang, out_path)
    return results

def main():
    parser = argparse.ArgumentParser(description="Advanced OCR with Tesseract")
    parser.add_argument('--image', type=str, help='Path to image file for OCR')
    parser.add_argument('--folder', type=str, help='Path to folder for batch OCR')
    parser.add_argument('--lang', type=str, default='eng', help='Language for OCR')
    parser.add_argument('--out', type=str, help='Output file or folder')
    args = parser.parse_args()

    if args.image:
        text = ocr_image(args.image, args.lang, args.out)
        print(text)
    elif args.folder:
        batch_ocr(args.folder, args.lang, args.out)
        print(f"Batch OCR completed. Results saved to {args.out}")
    else:
        parser.print_help()

if __name__ == "__main__":
    main()

Example Usage

Run the OCR

python advanced_ocr_with_tesseract.py

Explanation