Skip to content

TemporalFix

TemporalFix stabilizes and repairs frame-level detections without coupling an application to a detector or full tracking framework. It accepts validated NumPy data and returns boxes with track IDs, lifecycle state, provenance, and bounded heuristic uncertainty.

detector -> Detections -> global association -> temporal stabilization
                                             -> provenance-labelled output

Install the dependency-light core:

pip install temporalfix

Start with the five-minute quick start, then review the configuration, public API, and limitations. The release candidate has no published performance or accuracy claim; its benchmark tools record evidence for the machine and data on which they run.

What it does

  • deterministic global IoU association with optional class gating;
  • none, EMA, or constant-velocity Kalman box smoothing;
  • confidence smoothing and decay through short gaps;
  • class evidence voting and switch diagnostics;
  • false-positive confirmation and bounded gap recovery;
  • independent state for multiple streams;
  • safe YAML configuration and inspectable presets.

What it does not do

TemporalFix is not appearance-based tracking or long-term re-identification. Its uncertainty is an interpretable lifecycle heuristic, not a calibrated error probability. Detector execution remains outside the package.