Seg Preview

Class: SegPreviewBlockV1

Source: inference.core.workflows.core_steps.models.foundation.seg_preview.v1.SegPreviewBlockV1

Seg Preview

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
class_names	Union[List[str], str]	List of classes to recognise.	✅
threshold	float	Threshold for predicted mask scores.	✅

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 Seg Preview in version v1.

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

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Seg Preview in version v1 has.

Bindings

• input

  • images (image): The image to infer on..
  • class_names (Union[list_of_values, string]): List of classes to recognise.
  • threshold (float): Threshold for predicted mask scores.

• output

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

Example JSON definition of step Seg Preview in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/seg-preview@v1",
    "images": "$inputs.image",
    "class_names": [
        "car",
        "person"
    ],
    "threshold": 0.3
}