Sam3 Image

Sam3 Image

Playground

SAM 3 is a unified foundation model for promptable image segmentation using text, points, or boxes to detect and segment objects. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

SAM3 Image Segmentation

SAM3 Image Segmentation is an advanced image segmentation model based on Meta’s Segment Anything Model 3. It identifies and segments objects in images using flexible prompt types — text descriptions, point coordinates, or bounding boxes — delivering precise masks for any target object.

Why Choose This?

• Multiple prompt types Segment objects using text prompts, point prompts, box prompts, or any combination.

• Text-based segmentation Simply describe what to segment (e.g., “the man”, “the car”, “background”).

• Point and box prompts Precise control with coordinate-based prompts for exact object targeting.

• Mask overlay option Optionally overlay the segmentation mask directly on the original image.

• Prompt Enhancer Built-in tool to automatically improve your text prompts for better results.

• Ultra-affordable Just $0.005 per image for professional-quality segmentation.

Parameters

*At least one prompt type (text, boxes, or points) must be provided.

How to Use

1. Upload your image — drag and drop or paste a URL.
2. Add prompts — provide at least one of the following:
   • Text prompt — describe the object to segment (e.g., “the man”, “the dog”).
   • Point prompts — click ”+ Add Item” to add point coordinates.
   • Box prompts — click ”+ Add Item” to add bounding box coordinates.
3. Enable apply_mask (optional) — check to overlay the mask on the original image.
4. Choose output format — select jpeg, png, or webp.
5. Run — submit and download the segmented result.

Pricing

Simple flat-rate pricing regardless of image size or prompt complexity.

Best Use Cases

• Background Removal — Segment subjects for clean background removal.
• Object Isolation — Extract specific objects for compositing or editing.
• Image Editing — Create precise masks for targeted edits.
• Data Annotation — Generate segmentation masks for training datasets.
• E-commerce — Isolate products for catalog images.

Pro Tips

• Text prompts work best for common objects with clear descriptions.
• Use point prompts for precise targeting when text is ambiguous.
• Use box prompts to constrain the segmentation to a specific region.
• Combine multiple prompt types for more accurate results.
• Enable apply_mask to visualize the segmentation directly on the image.
• PNG format preserves transparency for mask outputs.

Notes

• At least one prompt type must be provided (text, points, or boxes).
• Text prompts support natural language descriptions.
• Point and box prompts use image coordinate systems.
• PNG format is recommended for mask outputs to preserve transparency.

Related Models

• Bria RMBG — Background removal model.
• Qwen Image Edit 2511 — Image editing with text instructions.

# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/sam3-image" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "point_prompts": [],
    "box_prompts": [],
    "apply_mask": true,
    "output_format": "png"
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"