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Supervision

Roboflow's reusable computer vision utilities for annotation, tracking, and visualising detection model outputs.

@ai-supply
Installations175k
Note★ 4.8
Avis58
↗ Dépôt source

Supervision

Supervision by Roboflow is a library of reusable computer-vision utilities that sits on top of any detection or segmentation model. It provides annotators, trackers, zone counting, and dataset tools that eliminate boilerplate when building vision pipelines.

Key Features

  • Model-agnostic Detections dataclass compatible with YOLO, SAM, Detectron2, and more
  • Rich annotation suite: BoundingBox, Mask, Label, Halo, Ellipse, Corner, Trace annotators
  • Object tracking with ByteTrack, SORT, and BotSort with one-line integration
  • Zone counting, line crossing counters, and polygon zones
  • Dataset tools: load COCO/YOLO/Pascal VOC, split, merge, and export

Quick Start

pip install supervision
import supervision as sv
from ultralytics import YOLO  # or any detector

model = YOLO("yolov8n.pt")
image = sv.load_image("image.jpg")
results = model(image)[0]
detections = sv.Detections.from_ultralytics(results)

annotator = sv.BoxAnnotator()
annotated = annotator.annotate(scene=image.copy(), detections=detections)
sv.plot_image(annotated)
npx ai-supply add supervision-vision-toolkit

Curated mirror of the open-source Supervision (MIT). Get it from the source.

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