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

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
}