Image Text Annotation with OpenCV and Python

Adding text overlays to images is a foundational skill for computer vision tasks, from labeling detected objects to adding watermarks and dynamic data readouts. This text-based course guides you through the process of programmatically writing text onto images with precision. You will transition from understanding how digital images are represented as matrices to writing clean, production-ready Python code that overlays highly customized text. You will master control over positioning, fonts, colors, line types, and scaling using modern Python practices. What you'll learn: - Understand how images are represented as NumPy arrays and how coordinate systems work in computer vision. - Apply the OpenCV putText function to draw clear, customizable text on any image. - Configure text properties including font faces, scaling, colors, thickness, and anti-aliasing for professional results. - Calculate text bounding boxes dynamically to perfectly center or align overlays on varying image sizes. - Implement modern Python conventions, including type hints and safe path handling with pathlib. - Explore alternative workflows using Pillow for advanced rendering of non-standard fonts and Unicode characters. The course begins with foundational concepts of image coordinate systems and color spaces before moving into hands-on code examples. You will read detailed explanations, analyze structured code snippets, and complete written exercises to solidify your skills. Designed for beginner Python developers, aspiring data scientists, and computer vision enthusiasts, this course requires no prior image processing experience. Start writing clean image annotation scripts today.