Calibra v0.11 makes robotics dataset analysis more accurate and reliable. This release adds dataset profiles, so Calibra can adapt its analysis and pruning logic to how a dataset was actually collected instead of applying one global threshold everywhere. It also fixes and verifies key workflows across LeRobot, Isaac Lab, GR00T, HDF5, dataset export, calibration baselines, duplicate-frame detection, and deterministic pruning. The result: cleaner dataset decisions and training-ready exports.

Calibra helps robotics teams audit dataset integrity, measure quality and coverage, and build smaller training sets. v0.8 adds measured training experiments: record real GPU-hours, wall-clock time, energy, and policy performance, then compare Full vs Random vs Calibra across retention levels.

Calibra helps robotics teams trust, understand, and optimize their datasets before training. Audit integrity, measure quality and coverage, and build smaller, high-quality training sets to reduce unnecessary GPU computation.