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Most computer-vision tutorials hand you a demo: a box drawn around a face, a label slapped on a cat, and then nothing. The moment you ask a second question - Is that car moving? What is it near? Where is it in 3D? - the demo falls silent.
This book builds a system instead of a demo. From a single camera frame, you'll produce a structured, queryable description of the entire scene - a world model you can interrogate like a small database: the same object keeps its identity across frames, its parts, its properties, its place on the ground, and its relationships to everything else.
Working in Python with today's open-source stack, you'll wire together more than a dozen capabilities into one coherent pipeline:
Every chapter is grounded in real, runnable open-source code, not pseudocode - with a companion repository, original diagrams, and an architecture designed so you can add a new capability or teach a new class after deployment, without forgetting what the system already knew.
Who it's for: developers, ML engineers, robotics and AR builders, and serious learners who are done running other people's demos and want to construct a perception system of their own - one frame, one world model, fully under your control.
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