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.

Hiring signal: Understanding of ocr & document understanding internals

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: Phase 4 Lesson 06 (Detection), Phase 7 Lesson 02 (Self-Attention) Time: ~45 minutes

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 It, Use It, Ship It, Exercises, Key Terms, Further Reading — plus a hands-on lab, quiz, and project artifact.

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