wkentaro/osam

Get up and running with SAM1-3, EfficientSAM, YOLO-World, and other promptable vision models locally.

61
/ 100
Established

This tool helps developers and machine learning engineers easily integrate advanced image segmentation and object detection capabilities into their applications. You input an image and a specific prompt (like a point, bounding box, or text), and it outputs a segmented mask or detected objects. This is ideal for those who need to quickly experiment with or deploy powerful vision models locally.

Available on PyPI.

Use this if you need to run and experiment with state-of-the-art promptable vision models like SAM or YOLO-World directly on your local machine or server.

Not ideal if you are a non-technical end-user looking for a graphical user interface to perform image editing or analysis.

computer-vision image-segmentation object-detection machine-learning-ops model-deployment
Maintenance 10 / 25
Adoption 9 / 25
Maturity 25 / 25
Community 17 / 25

How are scores calculated?

Stars

81

Forks

14

Language

Python

License

MIT

Last pushed

Jan 28, 2026

Commits (30d)

0

Dependencies

7

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/wkentaro/osam"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.