Welcome

Welcome to the Yet Another Limelight Library (YALL) documentation!

YALL is a WPILib vendordep that wraps Limelight's NetworkTables API and JSON results output in a typed, chainable Java (and Python) API for FRC robots. It replaces the raw LimelightHelpers script with real objects: a Limelight per camera, chainable settings, MegaTag1/MegaTag2 pose estimation, and typed results for every pipeline type, including AprilTag, retroreflective, neural classifier/detector, and barcode.

Jump right in

Basic setup

Create your first Limelight object and configure it.

AprilTag pose estimation

Fuse MegaTag2 vision measurements into your pose estimator.

Object detection

Read neural classifier and detector results.

Simulation

Exercise vision code in desktop simulation without hardware.

Where to go next

• Tutorials: step-by-step walkthroughs for common setups.
• How-to guides: focused answers to specific "how do I…" questions.
• Tuning: the tuning steps from Limelight's own documentation, reorganized into the order you'd actually apply them (sensor settings, crosshair/camera calibration, pipeline-specific tuning, then PID).
• Understanding: explanations of how YALL's settings, pose estimation, and results model work.
• API Reference (YALL-Gitbook-API space): every class, field, and method.
• Javadocs: generated API docs.
• GitHub: source, issues, and releases.