Evaluate

Use eval to score tracking runs on MOT-style datasets with TrackEval-backed metrics.

Examples

Example

CLIPython

boxmot eval --benchmark mot17-ablation --tracker boosttrack --verbose

from boxmot import Boxmot

boxmot = Boxmot(detector="yolov8n", reid="lmbn_n_duke", tracker="boosttrack")
metrics = boxmot.val(benchmark="mot17-ablation")
print(metrics)

Typical workflow

Example

CLIPython

For repeated experiments:

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

This lets eval reuse precomputed detections and embeddings.

from boxmot import Boxmot

boxmot = Boxmot(detector="yolov8n", reid="lmbn_n_duke", tracker="boosttrack")
metrics = boxmot.val(benchmark="mot17-ablation")
print(metrics)

Postprocessing

Example

CLIPython

eval can apply optional postprocessing before scoring:

boxmot eval --benchmark mot17-ablation --tracker boosttrack --postprocessing gsi
boxmot eval --benchmark mot17-ablation --tracker boosttrack --postprocessing gbrc

Boxmot.val(...) is the Python-facing validation entry point. Postprocessing details and metric interpretation are the same as in the CLI evaluation pipeline.

See Evaluation and Postprocessing.

Main outputs

• combined benchmark metrics such as HOTA, MOTA, and IDF1
• per-sequence summaries
• optional runtime timing summary with --show-timing
• MOT-style tracker outputs
• reused cache paths and evaluation artifacts in the run directory

See Evaluation and Postprocessing and Results and Artifacts.

CLI Arguments

boxmot eval

Evaluate tracking performance

Usage:

boxmot eval [OPTIONS]

Options:

Name	Type	Description	Default
--benchmark	text	benchmark config name or YAML file, e.g. mot17-ablation or boxmot/configs/benchmarks/mot17-ablation.yaml	None
--imgsz	text	Image size for model input as H,W (e.g. 800,1440) or single int for square. Default: read from the selected detector config, otherwise use detector-specific defaults.	None
--fps	integer	video frame-rate	None
--conf	float	Min confidence threshold. Default: read from the selected detector config, fallback 0.01.	None
--iou	float	IoU threshold for NMS	0.7
--device	text	cuda device(s), e.g. 0 or 0,1,2,3 or cpu	cpu
--batch-size	integer	micro-batch size for batched detection/embedding	16
--auto-batch / --no-auto-batch	boolean	probe GPU memory with a dummy pass to pick a safe batch size	True
--resume / --no-resume	boolean	resume detection/embedding generation from progress checkpoints	True
--n-threads	integer	CPU threads for image decoding; defaults to min(8, cpu_count)	4
--project	Path	save results to project/name	runs
--name	text	save results to project/name	exp
--exist-ok	boolean	existing project/name ok, do not increment	False
--half	boolean	use FP16 half-precision inference	False
--vid-stride	integer	video frame-rate stride	1
--ci	boolean	reuse existing runs in CI (no UI)	False
--tracker	text	deepocsort, botsort, strongsort, ...	bytetrack
--verbose	boolean	print detailed logs	False
--show-timing / --hide-timing	boolean	print runtime timing summary after evaluation	False
--agnostic-nms	boolean	class-agnostic NMS	False
--postprocessing	choice (none | gsi | gbrc)	Postprocess tracker output: none	gsi (Gaussian smoothed interpolation)
--show	boolean	display tracking in a window	False
--show-labels / --hide-labels	boolean	show or hide detection labels	True
--show-conf / --hide-conf	boolean	show or hide detection confidences	True
--show-trajectories	boolean	overlay past trajectories	False
--show-kf-preds	boolean	show Kalman-filter predictions	False
--save-txt	boolean	save results to a .txt file	False
--save-crop	boolean	save cropped detections	False
--save	boolean	save annotated video	False
--line-width	integer	bounding box line width	None
--per-class	boolean	track each class separately	False
--target-id	integer	ID to highlight in green	None
--detector	Path	one or more YOLO weights for detection	[PosixPath('/home/runner/work/boxmot/boxmot/models/yolov8n.pt')]
--reid	Path	one or more ReID model weights	[PosixPath('/home/runner/work/boxmot/boxmot/models/osnet_x0_25_msmt17.pt')]
--classes	text	filter by class indices, e.g. 0 or "0,1"	None
--help	boolean	Show this message and exit.	False