Polygon Zone Visualization

Class: PolygonZoneVisualizationBlockV1

Source: inference.core.workflows.core_steps.visualizations.polygon_zone.v1.PolygonZoneVisualizationBlockV1

The PolygonZoneVisualization block draws polygon zone in an image with a specified color and opacity. Please note: zones will be drawn on top of image passed to this block, this block should be placed before other visualization blocks in the workflow.

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
copy_image	bool	Enable this option to create a copy of the input image for visualization, preserving the original. Use this when stacking multiple visualizations..	✅
zone	List[Any]	Polygon zones (one for each batch) in a format [[(x1, y1), (x2, y2), (x3, y3), ...], ...]; each zone must consist of more than 2 points.	✅
color	str	Color of the zone..	✅
opacity	float	Transparency of the Mask overlay..	✅

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 Polygon Zone Visualization in version v1.

• inputs: VLM as Detector, OpenAI, Keypoint Detection Model, Circle Visualization, Roboflow Dataset Upload, PTZ Tracking (ONVIF).md), Multi-Label Classification Model, Roboflow Custom Metadata, Depth Estimation, SIFT, Florence-2 Model, Buffer, Dimension Collapse, Grid Visualization, Dynamic Zone, Instance Segmentation Model, Color Visualization, CSV Formatter, Detections Consensus, Identify Outliers, Perspective Correction, Model Monitoring Inference Aggregator, Image Slicer, OpenAI, Model Comparison Visualization, Clip Comparison, Stitch Images, Dynamic Crop, Image Contours, Webhook Sink, Pixelate Visualization, Llama 3.2 Vision, SIFT Comparison, Camera Calibration, Reference Path Visualization, Image Blur, Local File Sink, Blur Visualization, OCR Model, Ellipse Visualization, Trace Visualization, Corner Visualization, Camera Focus, Polygon Zone Visualization, Google Gemini, OpenAI, Triangle Visualization, Stability AI Inpainting, Classification Label Visualization, Single-Label Classification Model, Bounding Box Visualization, CogVLM, Image Convert Grayscale, Halo Visualization, LMM, Email Notification, Polygon Visualization, Absolute Static Crop, Slack Notification, Object Detection Model, Dot Visualization, Label Visualization, Stability AI Outpainting, Crop Visualization, Google Vision OCR, Stability AI Image Generation, Image Threshold, Stitch OCR Detections, Image Preprocessing, VLM as Classifier, Identify Changes, SIFT Comparison, JSON Parser, Mask Visualization, Twilio SMS Notification, Florence-2 Model, Clip Comparison, Roboflow Dataset Upload, Line Counter Visualization, VLM as Classifier, Anthropic Claude, Background Color Visualization, LMM For Classification, Image Slicer, Keypoint Visualization, Size Measurement, VLM as Detector, Relative Static Crop
• outputs: YOLO-World Model, OpenAI, VLM as Detector, Keypoint Detection Model, Circle Visualization, Gaze Detection, Roboflow Dataset Upload, Perception Encoder Embedding Model, Depth Estimation, SIFT, Florence-2 Model, Buffer, Single-Label Classification Model, Template Matching, Detections Stitch, Instance Segmentation Model, Color Visualization, Object Detection Model, Perspective Correction, Image Slicer, OpenAI, Keypoint Detection Model, Model Comparison Visualization, Clip Comparison, Stitch Images, Dynamic Crop, Moondream2, Image Contours, Pixelate Visualization, Llama 3.2 Vision, Byte Tracker, Camera Calibration, Reference Path Visualization, Time in Zone, Image Blur, CLIP Embedding Model, Blur Visualization, OCR Model, Ellipse Visualization, Trace Visualization, SmolVLM2, Polygon Zone Visualization, Corner Visualization, Google Gemini, Camera Focus, OpenAI, Triangle Visualization, Stability AI Inpainting, Classification Label Visualization, Single-Label Classification Model, Barcode Detection, Bounding Box Visualization, Detections Stabilizer, CogVLM, Image Convert Grayscale, Halo Visualization, LMM, Polygon Visualization, Absolute Static Crop, Object Detection Model, Dot Visualization, Label Visualization, Stability AI Outpainting, Crop Visualization, Google Vision OCR, Stability AI Image Generation, Pixel Color Count, Image Threshold, Image Preprocessing, VLM as Classifier, SIFT Comparison, Mask Visualization, Dominant Color, Florence-2 Model, Segment Anything 2 Model, Clip Comparison, Roboflow Dataset Upload, QR Code Detection, Line Counter Visualization, VLM as Classifier, Instance Segmentation Model, Background Color Visualization, Anthropic Claude, LMM For Classification, Multi-Label Classification Model, Image Slicer, Keypoint Visualization, Qwen2.5-VL, Multi-Label Classification Model, VLM as Detector, Relative Static Crop

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Polygon Zone Visualization in version v1 has.

Bindings

• input

  • image (image): The image to visualize on..
  • copy_image (boolean): Enable this option to create a copy of the input image for visualization, preserving the original. Use this when stacking multiple visualizations..
  • zone (list_of_values): Polygon zones (one for each batch) in a format [[(x1, y1), (x2, y2), (x3, y3), ...], ...]; each zone must consist of more than 2 points.
  • color (string): Color of the zone..
  • opacity (float_zero_to_one): Transparency of the Mask overlay..

• output

  • image (image): Image in workflows.

Example JSON definition of step Polygon Zone Visualization in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/polygon_zone_visualization@v1",
    "image": "$inputs.image",
    "copy_image": true,
    "zone": "$inputs.zones",
    "color": "WHITE",
    "opacity": 0.3
}