sam3-segmentation — скилл

---
name: sam3-segmentation
description: >-
  Outline, mask, cut out or count objects in images with Meta's SAM 3 (Segment
  Anything Model 3), run locally on an NVIDIA GPU. Use when the user wants pixel
  masks or outlines of things in a photo, even without saying "segmentation" or
  "SAM": every instance of a phrase ("all the dogs"), one object from a click or
  box, automatic "segment everything", or careful, auditable annotation of many
  small objects or parts, such as corn kernels, seeds, cells, insects or leaves,
  with COCO RLE / PNG masks, review and a zoomable viewer. Prefer it to judging
  outlines, counts or object positions by eye. Includes first-time setup and a
  demo that needs no GPU. Outputs are model proposals, not verified
  ground truth. Not for classifying, captioning or editing images, video,
  medical scans, or customer and network segmentation.
license: MIT
compatibility: >-
  Model inference needs Linux (or Windows WSL2), an NVIDIA GPU with drivers for
  CUDA 12.8 (12-24 GB memory suggested), uv, Python 3.12, about 11 GB of
  downloads plus room for run records, and the user's own approved Hugging Face
  access to facebook/sam3. No CPU or Apple
  GPU inference. The demo, review and export tools run anywhere uv runs.
metadata:
  version: "0.1.0"
  author: Aurélie Guisnet
  repository: https://github.com/lillyguisnet/sam3-segmentation
---

# SAM 3 segmentation

## Choose a mode

**Direct SAM calls** (`scripts/sam.py`): the model and nothing else. Use them
for a quick outline, a few objects, a "segment everything" pass, exploring a
photo before a full run, or your own procedure. Read