Segment Anything 2 Model

Class: SegmentAnything2BlockV1

Source: inference.core.workflows.core_steps.models.foundation.segment_anything2.v1.SegmentAnything2BlockV1

Run Segment Anything 2, a zero-shot instance segmentation model, on an image.

** Dedicated inference server required (GPU recomended) **

You can use pass in boxes/predictions from other models to Segment Anything 2 to use as prompts for the model. If you pass in box detections from another model, the class names of the boxes will be forwarded to the predicted masks. If using the model unprompted, the model will assign integers as class names / ids.

Type identifier

Use the following identifier in step "type" field: roboflow_core/segment_anything@v1to add the block as as step in your workflow.

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
version	str	Model to be used. One of hiera_large, hiera_small, hiera_tiny, hiera_b_plus.	✅
threshold	float	Threshold for predicted masks scores.	✅
multimask_output	bool	Flag to determine whether to use sam2 internal multimask or single mask mode. For ambiguous prompts setting to True is recomended..	✅

The Refs column marks possibility to parametrise the property with dynamic values available in workflow runtime. See Bindings for more info.

Available Connections

Compatible Blocks

Check what blocks you can connect to Segment Anything 2 Model in version v1.

• inputs: Keypoint Detection Model, CogVLM, Image Convert Grayscale, Anthropic Claude, Gaze Detection, Google Vision OCR, OpenAI, Detections Classes Replacement, Florence-2 Model, Detection Offset, Pixelate Visualization, Single-Label Classification Model, SIFT, VLM as Detector, OpenAI, Moondream2, Stability AI Image Generation, YOLO-World Model, SIFT Comparison, Mask Visualization, Object Detection Model, Image Slicer, Overlap Filter, Triangle Visualization, Cosine Similarity, Path Deviation, VLM as Detector, CSV Formatter, Polygon Zone Visualization, Model Comparison Visualization, Crop Visualization, Classification Label Visualization, LMM, Segment Anything 2 Model, Keypoint Detection Model, Reference Path Visualization, Multi-Label Classification Model, Twilio SMS Notification, Google Gemini, Bounding Box Visualization, Image Contours, Byte Tracker, Roboflow Custom Metadata, Circle Visualization, Perspective Correction, Slack Notification, Polygon Visualization, Detections Transformation, Instance Segmentation Model, VLM as Classifier, Trace Visualization, Detections Merge, Webhook Sink, Color Visualization, Identify Changes, Detections Consensus, LMM For Classification, Image Threshold, Detections Stitch, SIFT Comparison, JSON Parser, Absolute Static Crop, Line Counter Visualization, Stitch Images, Line Counter, Dot Visualization, Detections Filter, Identify Outliers, Dynamic Zone, Instance Segmentation Model, Background Color Visualization, Florence-2 Model, Detections Stabilizer, Model Monitoring Inference Aggregator, Stitch OCR Detections, Image Slicer, Template Matching, Bounding Rectangle, Roboflow Dataset Upload, Roboflow Dataset Upload, Image Blur, Time in Zone, Email Notification, Camera Focus, Grid Visualization, Path Deviation, Object Detection Model, Blur Visualization, Label Visualization, Stability AI Inpainting, Depth Estimation, Image Preprocessing, Llama 3.2 Vision, Byte Tracker, Ellipse Visualization, ONVIF Control, VLM as Classifier, Byte Tracker, Halo Visualization, Corner Visualization, Camera Calibration, Clip Comparison, Time in Zone, Dynamic Crop, Relative Static Crop, OpenAI, Keypoint Visualization, Velocity, OCR Model, Local File Sink
• outputs: Detections Stitch, Detections Classes Replacement, Florence-2 Model, Detection Offset, Distance Measurement, Pixelate Visualization, Line Counter, Mask Visualization, Detections Filter, Overlap Filter, Dot Visualization, Dynamic Zone, Background Color Visualization, Florence-2 Model, Model Monitoring Inference Aggregator, Detections Stabilizer, Triangle Visualization, Bounding Rectangle, Path Deviation, Roboflow Dataset Upload, Roboflow Dataset Upload, Time in Zone, Path Deviation, Model Comparison Visualization, Crop Visualization, Stability AI Inpainting, Blur Visualization, Segment Anything 2 Model, Label Visualization, Byte Tracker, Ellipse Visualization, ONVIF Control, Byte Tracker, Line Counter, Bounding Box Visualization, Halo Visualization, Roboflow Custom Metadata, Byte Tracker, Size Measurement, Corner Visualization, Time in Zone, Circle Visualization, Perspective Correction, Dynamic Crop, Polygon Visualization, Detections Transformation, Detections Merge, Trace Visualization, Velocity, Color Visualization, Detections Consensus

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Segment Anything 2 Model in version v1 has.

Bindings

• input

  • images (image): The image to infer on..
  • boxes (Union[instance_segmentation_prediction, object_detection_prediction, keypoint_detection_prediction]): Bounding boxes (from another model) to convert to polygons.
  • version (string): Model to be used. One of hiera_large, hiera_small, hiera_tiny, hiera_b_plus.
  • threshold (float): Threshold for predicted masks scores.
  • multimask_output (boolean): Flag to determine whether to use sam2 internal multimask or single mask mode. For ambiguous prompts setting to True is recomended..

• output

  • predictions (instance_segmentation_prediction): Prediction with detected bounding boxes and segmentation masks in form of sv.Detections(...) object.

Example JSON definition of step Segment Anything 2 Model in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/segment_anything@v1",
    "images": "$inputs.image",
    "boxes": "$steps.object_detection_model.predictions",
    "version": "hiera_large",
    "threshold": 0.3,
    "multimask_output": true
}