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@v1
to 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:
Identify Changes
,Relative Static Crop
,Background Color Visualization
,Line Counter Visualization
,OpenAI
,Roboflow Dataset Upload
,Grid Visualization
,LMM For Classification
,Object Detection Model
,Llama 3.2 Vision
,Camera Focus
,Color Visualization
,Roboflow Dataset Upload
,Label Visualization
,CSV Formatter
,Dot Visualization
,Bounding Box Visualization
,Detections Consensus
,Single-Label Classification Model
,OCR Model
,Google Vision OCR
,JSON Parser
,Dynamic Crop
,Clip Comparison
,Identify Outliers
,Model Comparison Visualization
,Anthropic Claude
,Depth Estimation
,Corner Visualization
,SIFT Comparison
,SIFT Comparison
,Camera Calibration
,Keypoint Visualization
,Mask Visualization
,Image Threshold
,VLM as Detector
,Halo Visualization
,Florence-2 Model
,Polygon Zone Visualization
,Clip Comparison
,Google Gemini
,Polygon Visualization
,Image Preprocessing
,Instance Segmentation Model
,SIFT
,Twilio SMS Notification
,Dynamic Zone
,Reference Path Visualization
,Roboflow Custom Metadata
,Blur Visualization
,Image Contours
,VLM as Detector
,Pixelate Visualization
,Keypoint Detection Model
,OpenAI
,Ellipse Visualization
,Crop Visualization
,Stitch Images
,Florence-2 Model
,Stitch OCR Detections
,CogVLM
,Image Slicer
,LMM
,Webhook Sink
,Perspective Correction
,Email Notification
,Size Measurement
,Dimension Collapse
,Multi-Label Classification Model
,Image Blur
,Stability AI Image Generation
,Image Convert Grayscale
,Stability AI Inpainting
,Model Monitoring Inference Aggregator
,Triangle Visualization
,Classification Label Visualization
,Trace Visualization
,Buffer
,VLM as Classifier
,Absolute Static Crop
,VLM as Classifier
,Circle Visualization
,Slack Notification
,Local File Sink
,Image Slicer
- outputs:
Relative Static Crop
,Background Color Visualization
,Line Counter Visualization
,OpenAI
,Roboflow Dataset Upload
,Gaze Detection
,Barcode Detection
,Detections Stabilizer
,LMM For Classification
,Object Detection Model
,Llama 3.2 Vision
,Camera Focus
,Color Visualization
,Roboflow Dataset Upload
,Instance Segmentation Model
,Pixel Color Count
,Label Visualization
,YOLO-World Model
,Moondream2
,SmolVLM2
,Dot Visualization
,Object Detection Model
,Bounding Box Visualization
,Template Matching
,Single-Label Classification Model
,OCR Model
,Google Vision OCR
,Dynamic Crop
,Clip Comparison
,Model Comparison Visualization
,Anthropic Claude
,Depth Estimation
,Corner Visualization
,Byte Tracker
,Qwen2.5-VL
,Multi-Label Classification Model
,SIFT Comparison
,Camera Calibration
,QR Code Detection
,Keypoint Visualization
,VLM as Detector
,Image Threshold
,Florence-2 Model
,Mask Visualization
,Halo Visualization
,Polygon Zone Visualization
,Google Gemini
,Clip Comparison
,Polygon Visualization
,Image Preprocessing
,Instance Segmentation Model
,SIFT
,Reference Path Visualization
,CLIP Embedding Model
,Blur Visualization
,Image Contours
,VLM as Detector
,Pixelate Visualization
,Dominant Color
,Keypoint Detection Model
,Detections Stitch
,OpenAI
,Ellipse Visualization
,Crop Visualization
,Stitch Images
,Florence-2 Model
,CogVLM
,LMM
,Image Slicer
,Perspective Correction
,Multi-Label Classification Model
,Image Blur
,Stability AI Image Generation
,Time in Zone
,Image Convert Grayscale
,Stability AI Inpainting
,Triangle Visualization
,Classification Label Visualization
,Keypoint Detection Model
,Trace Visualization
,Single-Label Classification Model
,Buffer
,VLM as Classifier
,Segment Anything 2 Model
,Absolute Static Crop
,VLM as Classifier
,Circle Visualization
,Image Slicer
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
}