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:
Dynamic Crop,OCR Model,Image Blur,Background Subtraction,Google Vision OCR,Google Gemini,Image Preprocessing,Object Detection Model,Local File Sink,Single-Label Classification Model,Bounding Box Visualization,Model Monitoring Inference Aggregator,Keypoint Detection Model,Camera Focus,Identify Outliers,Dot Visualization,Gaze Detection,Florence-2 Model,Roboflow Dataset Upload,CSV Formatter,Depth Estimation,Polygon Visualization,OpenAI,Line Counter,Image Slicer,Detections List Roll-Up,Line Counter Visualization,Heatmap Visualization,Morphological Transformation,Stability AI Image Generation,Google Gemini,Keypoint Visualization,Keypoint Detection Model,Background Color Visualization,Label Visualization,Polygon Visualization,LMM,CogVLM,Time in Zone,Triangle Visualization,Stability AI Outpainting,Mask Visualization,Color Visualization,Detections Combine,Text Display,Bounding Rectangle,Reference Path Visualization,Llama 3.2 Vision,OpenAI,Image Threshold,Clip Comparison,Classification Label Visualization,Polygon Zone Visualization,Image Contours,VLM As Classifier,Roboflow Custom Metadata,Dynamic Zone,LMM For Classification,Velocity,Halo Visualization,Blur Visualization,Path Deviation,Absolute Static Crop,Anthropic Claude,SAM 3,Cosine Similarity,Detections Transformation,Ellipse Visualization,Identify Changes,Crop Visualization,Path Deviation,SIFT Comparison,Trace Visualization,Twilio SMS Notification,Stitch Images,Detections Stabilizer,Detections Merge,Time in Zone,Motion Detection,Email Notification,SIFT Comparison,OpenAI,Seg Preview,Time in Zone,Instance Segmentation Model,Anthropic Claude,Multi-Label Classification Model,Detections Stitch,Email Notification,Slack Notification,Twilio SMS/MMS Notification,VLM As Detector,Camera Focus,SAM 3,Stitch OCR Detections,Perspective Correction,Moondream2,PTZ Tracking (ONVIF),Camera Calibration,Corner Visualization,Icon Visualization,Overlap Filter,Qwen3.5-VL,Byte Tracker,VLM As Detector,Halo Visualization,Detection Event Log,JSON Parser,Pixelate Visualization,Contrast Equalization,VLM As Classifier,Instance Segmentation Model,Detections Classes Replacement,Relative Static Crop,Stitch OCR Detections,Webhook Sink,Circle Visualization,Image Convert Grayscale,Grid Visualization,Mask Area Measurement,Byte Tracker,Florence-2 Model,SAM 3,SIFT,YOLO-World Model,Object Detection Model,Byte Tracker,Detections Consensus,Template Matching,Anthropic Claude,Google Gemini,Model Comparison Visualization,Detection Offset,QR Code Generator,EasyOCR,Image Slicer,S3 Sink,Stability AI Inpainting,Segment Anything 2 Model,Detections Filter,OpenAI,Roboflow Dataset Upload - outputs:
Dynamic Crop,Time in Zone,Circle Visualization,Time in Zone,Mask Area Measurement,Byte Tracker,Model Monitoring Inference Aggregator,Bounding Box Visualization,Florence-2 Model,Detections Stitch,Roboflow Custom Metadata,Dot Visualization,Florence-2 Model,Dynamic Zone,Roboflow Dataset Upload,Camera Focus,Velocity,Polygon Visualization,Halo Visualization,PTZ Tracking (ONVIF),Perspective Correction,Line Counter,Icon Visualization,Corner Visualization,Overlap Filter,Byte Tracker,Detections Consensus,Detections List Roll-Up,Heatmap Visualization,Distance Measurement,Byte Tracker,Model Comparison Visualization,Blur Visualization,Detection Offset,Halo Visualization,Background Color Visualization,Path Deviation,Label Visualization,Detection Event Log,Polygon Visualization,Pixelate Visualization,Time in Zone,Triangle Visualization,Detections Transformation,Mask Visualization,Ellipse Visualization,Path Deviation,Crop Visualization,Stability AI Inpainting,Trace Visualization,Color Visualization,Segment Anything 2 Model,Detections Combine,Size Measurement,Detections Stabilizer,Detections Filter,Bounding Rectangle,Detections Classes Replacement,Detections Merge,Roboflow Dataset Upload,Line Counter
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[object_detection_prediction,instance_segmentation_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
}