Modes Overview

BoxMOT organizes its main workflows into six modes exposed through one CLI and one high-level Python facade.

Mode	Use it when	Start here
track	You want detector + tracker output on a live or saved source	Track
generate	You want reusable detections and embeddings	Generate
eval	You want benchmark metrics on MOT-style datasets	Evaluate
tune	You want to optimize tracker hyperparameters	Tune
research	You want GEPA to propose and score tracker code changes	Research
export	You want to convert a ReID model to deployment formats	Export

Two workflow families

Direct-source execution

Use track when you already have a webcam, video, image folder, or stream and want annotated output immediately.

boxmot track --detector yolov8n --reid osnet_x0_25_msmt17 --tracker botsort --source video.mp4 --save

Benchmark-driven execution

Use generate, eval, tune, and research when you want repeatable experiments backed by YAML configs in boxmot/configs.

boxmot generate --benchmark mot17-ablation
boxmot eval --benchmark mot17-ablation --tracker boosttrack
boxmot tune --benchmark mot17-ablation --tracker bytetrack

Shared CLI shape

All BoxMOT modes start from the same command group:

boxmot MODE [OPTIONS] [DETECTOR] [REID] [TRACKER]

Use CLI for the high-level syntax. Each mode page includes its own examples and generated CLI argument table.