---
license: apache-2.0
base_model:
- facebook/sam3
tags:
- mlx
---
# SAM3 MLX Examples

Example scripts demonstrating how to use SAM3 MLX for segmentation tasks.

## Click-Based Segmentation

Segment objects by clicking on them with positive/negative points.

### Basic Usage

```bash
# Segment with a single positive click
python click_segment.py --image photo.jpg --point 512,384

# Segment with multiple points
python click_segment.py --image photo.jpg --point 512,384 --point 600,400

# Use positive (+) and negative (-) points for refinement
python click_segment.py --image photo.jpg --point +512,384 --point -100,100

# Save visualization
python click_segment.py --image photo.jpg --point 512,384 --output result.png

# Get single best mask instead of 3 masks
python click_segment.py --image photo.jpg --point 512,384 --single-mask
```

### Requirements

```bash
pip install pillow matplotlib mlx
```

### Performance

On Apple Silicon with MLX:
- Model initialization: ~2-3s
- Single inference: **<200ms** (target performance)
- Multiple masks: 3 predictions per inference

## Box-Based Segmentation

Coming soon: Segment using bounding box prompts.

## Mask-Based Refinement

Coming soon: Refine existing masks with additional mask prompts.

## Batch Processing

Coming soon: Process multiple images efficiently.