roboflow/supervision is a Python library that provides reusable building blocks to reduce repetitive code in computer vision workflows. Developers can connect classification, detection, or segmentation models and use utilities for data loading, zone counting, and visualization.
Project overview
It addresses repetitive, custom computer vision code by providing model-agnostic connectors and visualization annotators, letting developers focus on application logic.
Project type
Workflow
Deployment
Refer to project documentation
License
MIT
Best for
Developers and AI engineers who need to process image or video streams and want to use model-agnostic connectors to avoid writing repetitive visualization and data loading code.
Key capabilities
Provides connectors to plug in and use results from various classification, detection, or segmentation models, supporting libraries such as Ultralytics, Transformers, MMDetection, and Roboflow Inference.
Offers a range of customizable annotators to compose visualizations for bounding boxes and other detections.
Limitations and risks
Requires a Python environment (>=3.10).
Using the Roboflow Inference integration requires a Roboflow API KEY.
Getting started
Install the library in a Python environment (>=3.10) using the standard pip command without requiring complex system dependencies.