Phase 3: Generative Vision Models · ~45 minutes · Python

OCR & Document Understanding

OCR is a three-stage pipeline — detect text boxes, recognise the characters, then lay them out. Every modern OCR system reorders these stages or merges them.

What you will learn

Trace the classical OCR pipeline (detect -> recognise -> layout) and the modern end-to-end alternatives (Donut, Qwen-VL-OCR)
Implement CTC (Connectionist Temporal Classification) loss for sequence-to-sequence OCR training
Use PaddleOCR or EasyOCR for production document parsing without training
Distinguish OCR, layout parsing, and document understanding — and pick the right tool per task

Introduction

Type: Learn + Use
Languages: Python
Prerequisites: the Transformers & LLMs from Scratch course
Time: ~45 minutes

Objective

Learning objectives

Trace the classical OCR pipeline (detect -> recognise -> layout) and the modern end-to-end alternatives (Donut, Qwen-VL-OCR)
Implement CTC (Connectionist Temporal Classification) loss for sequence-to-sequence OCR training
Use PaddleOCR or EasyOCR for production document parsing without training
Distinguish OCR, layout parsing, and document understanding — and pick the right tool per task

Unlock the full lesson

You've read the first 2 sections. The rest of this lesson covers The Problem, The Concept, Build, Check Yourself, Key Terms & Next — plus a hands-on lab, quiz, and project artifact.

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