Polygon Zone Visualization

Class: PolygonZoneVisualizationBlockV1

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

Draw polygon zones on an image to visualize monitoring areas, displaying colored polygon overlays for zone-based detection and counting workflows that track objects within irregular, custom-defined regions.

How This Block Works

This block takes an image and polygon zone coordinates (a list of points defining a polygon shape) and draws a filled polygon overlay to visualize the monitoring zone. The block:

1. Takes an image and polygon zone coordinates (a list of points: [(x1, y1), (x2, y2), (x3, y3), ...]) as input
2. Creates a filled polygon mask from the zone coordinates using the specified color
3. Overlays the filled polygon onto the image with the specified opacity, creating a semi-transparent zone visualization
4. Returns an annotated image with the polygon zone overlay on the original image

The block visualizes polygon zones used to define irregular monitoring areas for detection, counting, or tracking workflows. The polygon is drawn as a filled shape between the specified points, creating a closed region that can represent any custom area shape (unlike rectangular bounding boxes). This allows for flexible zone definitions that match real-world boundaries, such as specific floor areas, irregular regions of interest, or complex monitoring zones. The zone overlay is semi-transparent, allowing the underlying image details to remain visible while clearly indicating the monitoring area. Note: This block should typically be placed before other visualization blocks in the workflow, as the polygon zone provides a background reference layer for object detection visualizations.

Common Use Cases

• Zone Detection Visualization: Visualize polygon zones for object detection or counting workflows where objects are tracked within irregular, custom-defined areas, displaying the monitoring boundaries clearly
• Area-Based Monitoring: Display polygon zones for area-based monitoring applications such as occupancy tracking, people counting in specific regions, or object presence detection within defined spaces
• Custom Region Visualization: Visualize custom monitoring regions that don't fit rectangular boundaries, such as irregular floor areas, complex room layouts, or specific zones within larger spaces
• Security and Surveillance: Display polygon zones for security monitoring, access control, or surveillance workflows where specific areas need to be visually marked and monitored
• Retail and Business Analytics: Visualize polygon zones for foot traffic analysis, customer movement tracking, or space utilization monitoring in retail, hospitality, or business intelligence applications
• Real-Time Zone Monitoring: Create visual overlays for real-time monitoring dashboards, live video feeds, or monitoring interfaces where polygon zones need to be clearly visible to indicate monitored areas

Connecting to Other Blocks

The annotated image from this block can be connected to:

• Zone detection or counting blocks to receive polygon zone coordinates that are visualized
• Other visualization blocks (e.g., Bounding Box Visualization, Label Visualization, Polygon Visualization) to add object detection annotations on top of the polygon zone visualization
• Data storage blocks (e.g., Local File Sink, CSV Formatter, Roboflow Dataset Upload) to save images with polygon zone visualizations for documentation, reporting, or analysis
• Webhook blocks to send visualized results with polygon zones to external systems, APIs, or web applications for display in dashboards or monitoring tools
• Notification blocks (e.g., Email Notification, Slack Notification) to send annotated images with polygon zones as visual evidence in alerts or reports
• Video output blocks to create annotated video streams or recordings with polygon zone visualizations for live monitoring, zone visualization, or post-processing analysis

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 zone coordinates in the format [[(x1, y1), (x2, y2), (x3, y3), ...], ...] defining one or more polygon shapes. Each zone must consist of more than 2 points to form a valid polygon. The polygon is drawn as a filled shape connecting these points in order, creating a closed region. Typically connected from zone detection or counting blocks that define monitoring areas..	✅
color	str	Color of the polygon zone overlay. Can be specified as a color name (e.g., 'WHITE', 'RED'), hex color code (e.g., '#5bb573', '#FFFFFF'), or RGB format (e.g., 'rgb(255, 255, 255)'). The polygon is filled with this color and overlaid with the specified opacity..	✅
opacity	float	Opacity of the polygon zone overlay, ranging from 0.0 (fully transparent) to 1.0 (fully opaque). Controls how transparent the polygon zone appears over the image. Lower values create more transparent zones that blend with the background, while higher values create more opaque, visible zones. Typical values range from 0.2 to 0.5 for balanced visibility where both the zone and underlying image are visible..	✅

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: Triangle Visualization, Morphological Transformation, Roboflow Dataset Upload, Ellipse Visualization, LMM, Florence-2 Model, Blur Visualization, Halo Visualization, Anthropic Claude, Google Gemini, Camera Focus, Llama 3.2 Vision, Motion Detection, Model Comparison Visualization, VLM As Detector, Keypoint Visualization, Pixelate Visualization, Size Measurement, Image Slicer, SIFT Comparison, Roboflow Dataset Upload, Line Counter Visualization, Stitch OCR Detections, Label Visualization, SIFT Comparison, QR Code Generator, Dynamic Zone, Email Notification, Clip Comparison, Buffer, Slack Notification, Corner Visualization, Image Slicer, Florence-2 Model, CSV Formatter, EasyOCR, Object Detection Model, Anthropic Claude, OpenAI, Google Gemini, Bounding Box Visualization, Keypoint Detection Model, Anthropic Claude, Background Subtraction, Background Color Visualization, Image Convert Grayscale, Camera Calibration, Polygon Visualization, Image Blur, VLM As Classifier, Relative Static Crop, Clip Comparison, Heatmap Visualization, CogVLM, Mask Visualization, Image Preprocessing, Twilio SMS Notification, VLM As Detector, PTZ Tracking (ONVIF).md), OpenAI, OCR Model, SIFT, Stitch Images, Stability AI Outpainting, Stitch OCR Detections, Dynamic Crop, Model Monitoring Inference Aggregator, Circle Visualization, Color Visualization, Trace Visualization, OpenAI, Dimension Collapse, Icon Visualization, Dot Visualization, Email Notification, Instance Segmentation Model, Camera Focus, Twilio SMS/MMS Notification, Depth Estimation, Contrast Equalization, Roboflow Custom Metadata, LMM For Classification, Grid Visualization, Text Display, Reference Path Visualization, Image Threshold, Perspective Correction, Image Contours, Polygon Zone Visualization, Multi-Label Classification Model, Polygon Visualization, Local File Sink, Identify Changes, Halo Visualization, JSON Parser, Google Vision OCR, Stability AI Inpainting, Identify Outliers, Crop Visualization, Detections Consensus, Detections List Roll-Up, Google Gemini, Webhook Sink, Absolute Static Crop, Classification Label Visualization, VLM As Classifier, OpenAI, Single-Label Classification Model, Stability AI Image Generation
• outputs: Triangle Visualization, Detections Stitch, Roboflow Dataset Upload, Ellipse Visualization, Morphological Transformation, LMM, Florence-2 Model, Blur Visualization, CLIP Embedding Model, Anthropic Claude, Halo Visualization, Google Gemini, Camera Focus, Llama 3.2 Vision, Motion Detection, Model Comparison Visualization, VLM As Detector, Keypoint Visualization, Qwen3-VL, Pixelate Visualization, Image Slicer, Roboflow Dataset Upload, Line Counter Visualization, Keypoint Detection Model, SmolVLM2, Label Visualization, SIFT Comparison, Clip Comparison, Buffer, SAM 3, Detections Stabilizer, Object Detection Model, EasyOCR, Image Slicer, Corner Visualization, Florence-2 Model, Object Detection Model, SAM 3, QR Code Detection, Anthropic Claude, OpenAI, Google Gemini, Perception Encoder Embedding Model, Bounding Box Visualization, Keypoint Detection Model, Anthropic Claude, Pixel Color Count, Background Subtraction, Background Color Visualization, Image Convert Grayscale, Camera Calibration, Polygon Visualization, Image Blur, VLM As Classifier, Relative Static Crop, Clip Comparison, Heatmap Visualization, CogVLM, Mask Visualization, Image Preprocessing, VLM As Detector, Instance Segmentation Model, OpenAI, OCR Model, SIFT, Stitch Images, Single-Label Classification Model, Moondream2, Stability AI Outpainting, Dynamic Crop, Circle Visualization, Byte Tracker, OpenAI, Trace Visualization, Color Visualization, Qwen2.5-VL, Icon Visualization, YOLO-World Model, Dot Visualization, Time in Zone, Email Notification, Instance Segmentation Model, Camera Focus, Twilio SMS/MMS Notification, Contrast Equalization, Depth Estimation, Segment Anything 2 Model, LMM For Classification, Text Display, Dominant Color, Reference Path Visualization, Image Threshold, Perspective Correction, Multi-Label Classification Model, Image Contours, Polygon Zone Visualization, Polygon Visualization, Halo Visualization, Google Vision OCR, SAM 3, Stability AI Inpainting, Crop Visualization, Template Matching, Google Gemini, Barcode Detection, VLM As Classifier, Classification Label Visualization, Seg Preview, OpenAI, Absolute Static Crop, Multi-Label Classification Model, Single-Label Classification Model, Gaze Detection, Stability AI Image Generation

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 zone coordinates in the format [[(x1, y1), (x2, y2), (x3, y3), ...], ...] defining one or more polygon shapes. Each zone must consist of more than 2 points to form a valid polygon. The polygon is drawn as a filled shape connecting these points in order, creating a closed region. Typically connected from zone detection or counting blocks that define monitoring areas..
  • color (string): Color of the polygon zone overlay. Can be specified as a color name (e.g., 'WHITE', 'RED'), hex color code (e.g., '#5bb573', '#FFFFFF'), or RGB format (e.g., 'rgb(255, 255, 255)'). The polygon is filled with this color and overlaid with the specified opacity..
  • opacity (float_zero_to_one): Opacity of the polygon zone overlay, ranging from 0.0 (fully transparent) to 1.0 (fully opaque). Controls how transparent the polygon zone appears over the image. Lower values create more transparent zones that blend with the background, while higher values create more opaque, visible zones. Typical values range from 0.2 to 0.5 for balanced visibility where both the zone and underlying image are visible..

• 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
}