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:
Stability AI Outpainting,SAM 3,Motion Detection,Contrast Enhancement,Camera Focus,Image Preprocessing,Corner Visualization,Ellipse Visualization,Seg Preview,Object Detection Model,Roboflow Vision Events,Cosine Similarity,Heatmap Visualization,Trace Visualization,OC-SORT Tracker,VLM As Classifier,Time in Zone,OpenAI,Email Notification,Byte Tracker,Keypoint Visualization,Detections Consensus,Model Comparison Visualization,YOLO-World Model,JSON Parser,Polygon Zone Visualization,Byte Tracker,Dynamic Crop,Polygon Visualization,QR Code Generator,GLM-OCR,Stitch Images,OpenRouter,Image Blur,Dynamic Zone,Model Monitoring Inference Aggregator,Clip Comparison,Detections Stitch,Time in Zone,Detections List Roll-Up,Segment Anything 2 Model,Instance Segmentation Model,Google Gemini,Pixelate Visualization,EasyOCR,SIFT,Contrast Equalization,Image Threshold,Instance Segmentation Model,Polygon Visualization,Anthropic Claude,Halo Visualization,Roboflow Custom Metadata,Keypoint Detection Model,Florence-2 Model,Local File Sink,Icon Visualization,Detection Offset,Image Contours,SAM2 Video Tracker,Single-Label Classification Model,OpenAI,Detections Filter,SAM 3,Grid Visualization,ByteTrack Tracker,VLM As Detector,Object Detection Model,Detections Transformation,LMM,Image Convert Grayscale,Reference Path Visualization,Stitch OCR Detections,Keypoint Detection Model,SIFT Comparison,Identify Changes,Roboflow Dataset Upload,CSV Formatter,S3 Sink,BoT-SORT Tracker,SIFT Comparison,OpenAI-Compatible LLM,Morphological Transformation,Object Detection Model,Identify Outliers,Crop Visualization,Blur Visualization,Mask Visualization,Stability AI Image Generation,Qwen-VL,Stitch OCR Detections,Velocity,Google Gemma API,Image Slicer,Qwen 3.5 API,Path Deviation,Background Color Visualization,Slack Notification,Anthropic Claude,Qwen 3.6 API,Webhook Sink,Color Visualization,Bounding Box Visualization,Google Gemma,Relative Static Crop,Bounding Rectangle,Detection Event Log,Path Deviation,CogVLM,Llama 3.2 Vision,Instance Segmentation Model,Qwen3.5-VL,Camera Focus,Instance Segmentation Model,Google Vision OCR,Google Gemini,SAM 3,Llama 3.2 Vision,SORT Tracker,Twilio SMS Notification,Detections Stabilizer,Moondream2,Anthropic Claude,Image Slicer,Depth Estimation,OpenAI,Multi-Label Classification Model,Gaze Detection,Template Matching,Classification Label Visualization,PTZ Tracking (ONVIF),Florence-2 Model,MoonshotAI Kimi,Time in Zone,MoonshotAI Kimi,Line Counter,Dot Visualization,Background Subtraction,Keypoint Detection Model,Roboflow Dataset Upload,Stability AI Inpainting,Per-Class Confidence Filter,Detections Classes Replacement,Label Visualization,Overlap Filter,Detections Merge,Absolute Static Crop,Google Gemini,VLM As Classifier,Camera Calibration,Halo Visualization,Email Notification,OpenAI,LMM For Classification,Text Display,Mask Area Measurement,Circle Visualization,Line Counter Visualization,Byte Tracker,OCR Model,Detections Combine,VLM As Detector,Morphological Transformation,Twilio SMS/MMS Notification,Mask Edge Snap,Triangle Visualization,Perspective Correction - outputs:
BoT-SORT Tracker,Crop Visualization,Mask Visualization,Camera Focus,Blur Visualization,Corner Visualization,Ellipse Visualization,Roboflow Vision Events,Velocity,Heatmap Visualization,Trace Visualization,Path Deviation,OC-SORT Tracker,Background Color Visualization,Time in Zone,Color Visualization,Byte Tracker,Bounding Box Visualization,Detections Consensus,Model Comparison Visualization,Detection Event Log,Bounding Rectangle,Path Deviation,Byte Tracker,Dynamic Crop,Polygon Visualization,Distance Measurement,SORT Tracker,Detections Stabilizer,Dynamic Zone,Model Monitoring Inference Aggregator,Detections Stitch,Time in Zone,Detections List Roll-Up,Segment Anything 2 Model,Pixelate Visualization,PTZ Tracking (ONVIF),Florence-2 Model,Time in Zone,Line Counter,Dot Visualization,Polygon Visualization,Roboflow Dataset Upload,Halo Visualization,Per-Class Confidence Filter,Stability AI Inpainting,Roboflow Custom Metadata,Line Counter,Detections Classes Replacement,Florence-2 Model,Label Visualization,Icon Visualization,Detection Offset,Overlap Filter,Detections Merge,SAM2 Video Tracker,Detections Filter,ByteTrack Tracker,Halo Visualization,Size Measurement,Detections Transformation,Mask Area Measurement,Circle Visualization,Byte Tracker,Detections Combine,Overlap Analysis,Roboflow Dataset Upload,Mask Edge Snap,Triangle Visualization,Perspective Correction
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[keypoint_detection_prediction,instance_segmentation_prediction,object_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
}