Open Source · Observability
segment-anything (SAM)
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to
Our verdict
We have not reviewed segment-anything (SAM) yet
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From the listing
About segment-anything (SAM)
Segment Anything Model (SAM) is a foundation model for image segmentation that identifies and isolates objects in images with a single prompt. The repository provides inference code, pre-trained model checkpoints, and example notebooks for integration into applications.
Best for
Developers building image annotation tools, content moderation systems, or computer vision applications needing zero-shot segmentation.
Use cases
- Automated object detection and masking in images
- Building interactive segmentation interfaces
- Preprocessing images for computer vision pipelines
Notes
54,274 stars on GitHub. Last updated 2024-09-18. Licensed Apache-2.0.
Pros
- Foundation model trained on diverse data, generalizes across object types without retraining
- Prompt-based interface supports flexible input (points, boxes, text descriptions)
- Well-documented with example notebooks and multiple model size options
Cons
- Requires GPU for practical inference speed
- Model checkpoints are large (100MB to 2.5GB depending on variant)
- Performance degrades on small objects or images with complex occlusion
Key facts
What we have checked
- GitHub stars
- 54,941
Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.
Stars and usage
How segment-anything (SAM) is growing
54,274 to 54,941
Sources
Where this comes from
- github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438Registry
A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.
Changelog
What changed
No changes recorded yet. Releases, price changes and deprecations appear here, with their dates, once we track them for this record.
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