🧐 A Researcher’s Deep Dive: Comparing Top OCR Frameworks

“From pixel to word, from silence to script — OCR is the whisperer of text in the visual void.”

Optical Character Recognition (OCR) has been the unsung hero behind countless applications — invoice scanning, identity verification, prescription digitization, and more. But as AI evolves, the humble OCR engine has donned new robes — from basic template-based models to sophisticated deep learning and transformer-powered systems.

In this blog, we will meticulously compare 8 prominent OCR libraries — Tesseract, EasyOCR, DocTR, PaddleOCR, MMOCR, Keras-OCR, TrOCR, and SmolDocling — evaluating them across various dimensions:

📋 Comparison Summary Table

🏛️ 1. Tesseract OCR — The Old Monk of OCR

Origin: Developed by HP in the ’80s, now maintained by Google.
Type: LSTM-based OCR engine
Languages: 100+
Strengths: