TL;DR
Supervision is a reusable collection of tools for processing, visualizing, and analyzing inference results from computer vision models.
Key features
Model connection: Supports integration with various libraries such as Ultralytics, Transformers, and MMDetection, unifying results into sv.Detections objects.
Annotators: Provides various visualization tools for bounding boxes, masks, keypoints, labels, etc., with customization options.
Data processing: Offers filtering, merging, zone counting (aggregation by region), and other functions for detection results.
Dataset tools: Supports conversion between formats such as COCO, YOLO, Pascal VOC, and dataset loading.
When to use it
When you need to visualize or analyze inference results from computer vision models.
When using multiple model libraries and want to process results with a consistent interface.
When you need to quickly implement zone statistics or tracking features based on object detection results.