Python Face Shape Detection and Landmark Analysis

Facial analysis is at the heart of modern computer vision applications, from virtual try-ons to personalized styling. This text-based course guides you through building a face shape detection system from scratch using Python. You will transition from a beginner to a confident developer capable of processing facial images, extracting key coordinates, and applying geometric algorithms to classify face shapes. You will learn how to structure your computer vision code using modern Python practices, ensuring your projects are clean, readable, and maintainable. What you'll learn: - Understand the foundational concepts of facial landmarks and coordinate mapping - Extract precise face landmarks using MediaPipe and OpenCV - Calculate facial distances, ratios, and angles using geometric formulas - Classify face shapes such as oval, round, square, and heart-shaped - Apply modern Python features like type hinting and dataclasses to structure landmark data - Set up a clean local development environment using modern virtual environments The course begins with core definitions and environment setup, guiding you through landmark extraction before moving on to geometric calculations and final classification logic. You will practice through structured written explanations, step-by-step code walkthroughs, and conceptual exercises. This course is designed for beginner Python developers, aspiring computer vision enthusiasts, and creative technologists, with no prior experience in image processing required. Start reading today to build your own facial analysis programs from scratch.