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// summary
Supervision is a model-agnostic computer vision toolkit designed to simplify dataset processing, visualization of model inference results, and detection tasks. It provides rich connectors to support mainstream deep learning frameworks and includes highly customizable annotators. Additionally, the library contains powerful dataset management tools that support loading, splitting, merging, and converting between various formats.
// use cases
01
Supports the integration and processing of inference results from multiple mainstream models (such as Ultralytics and Transformers)
02
Provides highly customizable annotators for drawing detection results on images or videos
03
Supports the loading, splitting, merging, and conversion of computer vision datasets between different formats (COCO, YOLO, Pascal VOC)