This repository demonstrates stereo matching for depth estimation in computer vision using Python. It calculates disparity maps from stereo images via Sum of Absolute Differences (SAD), Sum of Squared Differences (SSD), and dynamic programming, producing visualized results for different window sizes.

A repository to keep track of my efforts to learn how various stereo matching algorithms work. Note that the algorithms appearing in here probably won't be particularly optimised versions, but they might just be reasonably illustrative/demonstrative.