The text discusses the role of Optical Character Recognition (OCR) in digitizing and extracting text from natural scene images, highlighting its significance in the era of increasing digitization. It explores the challenges associated with OCR, particularly in unstructured environments, and describes various machine learning and deep learning approaches for overcoming these challenges. Techniques such as the EAST model for text detection and Tesseract for text recognition are explored, with emphasis on their application and limitations in handling complex backgrounds and non-standard fonts. The text also introduces Nanonets, a platform that offers an API for building OCR models, and provides a step-by-step guide for using it to train custom models. The document underscores the importance of preprocessing images for effective text recognition and suggests that while OCR technology has advanced significantly, it still faces challenges, especially with non-uniform and stylized text.