> ## Documentation Index
> Fetch the complete documentation index at: https://docs.biom.science/llms.txt
> Use this file to discover all available pages before exploring further.

# SAM3 — Segment Anything

> Universal segmentation for images and videos.

# SAM3 — Segment Anything Model 3

SAM3 (Meta's Segment Anything Model 3) provides universal segmentation for images and videos. It supports point prompts, bounding box prompts, text prompts, and video tracking.

## Input formats

`.png`, `.jpg`, `.jpeg`, `.tiff`, `.bmp`, `.webp`, `.mp4`, `.avi`, `.mov`

## Modes

### Visual prompt segmentation (PVS)

Click on your image to provide prompts:

* **Point prompts** — click foreground points (label=1) or background points (label=0) to guide segmentation
* **Box prompts** — draw a bounding box around the object to segment

Best for: segmenting specific objects you can see and point to.

### Text concept segmentation (PCS)

Describe what you want to segment in natural language:

* *"red neurons"*
* *"cell nuclei"*
* *"mitochondria"*

Set a confidence threshold (0–1) to filter results by match quality.

Best for: segmenting objects by semantic description without clicking.

### Video tracking

Track objects across video frames:

* Select an object in one frame using point or box prompts
* Propagate the mask forward or backward through the video
* Specify a start frame for tracking

Best for: following cells, animals, or structures through time-lapse or video data.

### Z-stack propagation

For multi-plane images, propagate a segmentation mask across Z-slices automatically.

## Parameters

| Parameter                | Range   | Default | Description                                      |
| ------------------------ | ------- | ------- | ------------------------------------------------ |
| **IoU Threshold**        | 0.5–1.0 | 0.7     | Minimum intersection-over-union for mask quality |
| **Multi-mask output**    | Toggle  | Off     | Return multiple candidate masks                  |
| **Return polygons**      | Toggle  | Off     | Return GeoJSON polygon outlines                  |
| **Return instance IDs**  | Toggle  | Off     | Label each segment with a unique ID              |
| **Start frame**          | Integer | 0       | Starting frame for video tracking                |
| **Confidence threshold** | 0–1     | 0.5     | Minimum confidence for text prompts              |

## Outputs

| Output            | Format  | Description                            |
| ----------------- | ------- | -------------------------------------- |
| Segmentation mask | PNG     | Binary or labeled mask image           |
| Polygon outlines  | GeoJSON | Vector boundaries of segmented objects |

## Compute requirements

| Resource | Requirement                                         |
| -------- | --------------------------------------------------- |
| GPU      | T4 minimum (16 GB VRAM), A100 recommended for video |
| Duration | \~20 seconds for images, \~60 seconds for video     |

## Presets

| Preset             | Description                                     |
| ------------------ | ----------------------------------------------- |
| **Visual Prompt**  | Point/box-based segmentation for images         |
| **Text Prompt**    | Natural language description-based segmentation |
| **Video Tracking** | Object tracking through video frames            |