SAM 3 Interactive¶
Class: SegmentAnything3InteractiveBlockV1
Run the interactive (promptable visual segmentation) head of Segment Anything 3 (SAM3) on an image.
Unlike the SAM 3 concept segmentation block (which takes text or exemplar prompts and returns ALL instances of a concept), this block performs SAM2-style interactive segmentation: each prompt targets ONE object and the model returns a single mask for it.
Two prompt inputs are supported (at least one must be provided): - points: a list of labeled 2D points defining a single object. Positive points mark the object to segment, negative points mark regions to exclude (useful to refine the mask). - boxes: detections from another model. Each bounding box becomes a separate prompt and the model segments the object inside it. Class names of the boxes are forwarded to the predicted masks.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/sam3_interactive@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
points |
List[Any] |
Labeled points defining a single object to segment. Each point is {'x': ..., 'y': ..., 'positive': ...} in absolute pixel coordinates - positive points mark the object, negative points mark regions to exclude. Plain (x, y) or (x, y, positive) sequences are also accepted.. | ✅ |
threshold |
float |
Minimum confidence threshold for predicted masks. | ✅ |
multimask_output |
bool |
Flag to determine whether to use SAM3 internal multimask or single mask mode. For ambiguous prompts (like a single point) setting to True is recommended.. | ✅ |
The Refs column marks possibility to parametrise the property with dynamic values available
in workflow runtime. See Bindings for more info.
Runtime compatibility¶
-
hard— runtimeself_hosted_cpu; executionlocal - Requires a GPU; run_locally() loads a model that needs CUDA.
Available Connections¶
Compatible Blocks
Check what blocks you can connect to SAM 3 Interactive in version v1.
- inputs:
VLM As Classifier,Line Counter,Stability AI Image Generation,Trace Visualization,Path Deviation,Per-Class Confidence Filter,Icon Visualization,SIFT Comparison,Morphological Transformation,Color Visualization,Perspective Correction,Corner Visualization,Roboflow Custom Metadata,Detections Merge,Halo Visualization,Dynamic Zone,Keypoint Detection Model,JSON Parser,Email Notification,Halo Visualization,Object Detection Model,Background Color Visualization,Ellipse Visualization,Email Notification,Twilio SMS/MMS Notification,Text Display,Polygon Visualization,Crop Visualization,Absolute Static Crop,Image Preprocessing,Template Matching,Model Monitoring Inference Aggregator,Relative Static Crop,VLM As Detector,OCR Model,Heatmap Visualization,Motion Detection,Detections Filter,Blur Visualization,Depth Estimation,Instance Segmentation Model,Stability AI Outpainting,YOLO-World Model,Background Subtraction,Keypoint Visualization,Webhook Sink,Byte Tracker,Stitch Images,Detections List Roll-Up,Contrast Equalization,Mask Edge Snap,Moondream2,VLM As Detector,Triangle Visualization,Slack Notification,Overlap Filter,Time in Zone,Detections Stabilizer,SIFT,Local File Sink,Cosine Similarity,Image Contours,Keypoint Detection Model,VLM As Classifier,Roboflow Asset Library Attributes,Image Slicer,Polygon Zone Visualization,Contrast Enhancement,Time in Zone,Image Threshold,Line Counter Visualization,Camera Calibration,QR Code Generator,Detection Offset,ByteTrack Tracker,Detection Event Log,Detections Transformation,S3 Sink,Microsoft SQL Server Sink,Mask Area Measurement,Google Vision OCR,Twilio SMS Notification,Image Blur,Detections Combine,Morphological Transformation,Camera Focus,Roboflow Vision Events,Stability AI Inpainting,PTZ Tracking (ONVIF),Classification Label Visualization,Bounding Rectangle,SAM2 Video Tracker,Event Writer,Grid Visualization,Mask Visualization,Byte Tracker,Reference Path Visualization,Image Slicer,Label Visualization,Velocity,Identify Outliers,Byte Tracker,SIFT Comparison,OPC UA Writer Sink,Dot Visualization,Identify Changes,Dynamic Crop,Detections Stitch,Circle Visualization,Path Deviation,BoT-SORT Tracker,SAM3 Video Tracker,Camera Focus,Gaze Detection,Segment Anything 2 Model,Object Detection Model,SAM 3 Interactive,Detections Consensus,Bounding Box Visualization,SAM 3,PLC Reader,Image Convert Grayscale,Instance Segmentation Model,Roboflow Visual Search,EasyOCR,Roboflow Dataset Upload,SAM 3,Detections Classes Replacement,Instance Segmentation Model,Pixelate Visualization,Keypoint Detection Model,Instance Segmentation Model,SORT Tracker,Roboflow Dataset Upload,PLC Writer,Track Class Lock,Object Detection Model,Time in Zone,MQTT Writer,Polygon Visualization,OC-SORT Tracker,SAM 3,Model Comparison Visualization,Seg Preview - outputs:
Line Counter,Time in Zone,Path Deviation,Trace Visualization,Distance Measurement,Detection Offset,ByteTrack Tracker,Detection Event Log,Per-Class Confidence Filter,Icon Visualization,Detections Transformation,Color Visualization,Perspective Correction,Corner Visualization,Mask Area Measurement,Roboflow Custom Metadata,Detections Merge,Halo Visualization,Dynamic Zone,Detections Combine,Roboflow Vision Events,Size Measurement,Halo Visualization,Stability AI Inpainting,PTZ Tracking (ONVIF),Bounding Rectangle,SAM2 Video Tracker,Event Writer,Mask Visualization,Byte Tracker,Background Color Visualization,Ellipse Visualization,Velocity,Label Visualization,Byte Tracker,Dot Visualization,Polygon Visualization,Crop Visualization,Dynamic Crop,Path Deviation,Circle Visualization,Detections Stitch,BoT-SORT Tracker,Model Monitoring Inference Aggregator,Camera Focus,Segment Anything 2 Model,Florence-2 Model,Heatmap Visualization,Detections Filter,Overlap Analysis,Blur Visualization,SAM 3 Interactive,Detections Consensus,Byte Tracker,Bounding Box Visualization,Florence-2 Model,Detections List Roll-Up,Mask Edge Snap,Line Counter,Triangle Visualization,Overlap Filter,Roboflow Dataset Upload,Time in Zone,Detections Classes Replacement,Pixelate Visualization,Roboflow Dataset Upload,Detections Stabilizer,SORT Tracker,Track Class Lock,Time in Zone,Polygon Visualization,OC-SORT Tracker,Model Comparison Visualization
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
SAM 3 Interactive in version v1 has.
Bindings
-
input
images(image): The image to infer on..points(labeled_points): Labeled points defining a single object to segment. Each point is {'x': ..., 'y': ..., 'positive': ...} in absolute pixel coordinates - positive points mark the object, negative points mark regions to exclude. Plain (x, y) or (x, y, positive) sequences are also accepted..boxes(Union[keypoint_detection_prediction,object_detection_prediction,instance_segmentation_prediction]): Bounding boxes (from another model) to use as prompts - the model segments the object inside each box.threshold(float): Minimum confidence threshold for predicted masks.multimask_output(boolean): Flag to determine whether to use SAM3 internal multimask or single mask mode. For ambiguous prompts (like a single point) setting to True is recommended..
-
output
predictions(instance_segmentation_prediction): Prediction with detected bounding boxes and segmentation masks in form of sv.Detections(...) object.
Example JSON definition of step SAM 3 Interactive in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/sam3_interactive@v1",
"images": "$inputs.image",
"points": [
{
"positive": true,
"x": 320,
"y": 240
}
],
"boxes": "$steps.object_detection_model.predictions",
"threshold": 0.3,
"multimask_output": true
}