Dynamic Zone¶
Class: DynamicZonesBlockV1
Source: inference.core.workflows.core_steps.transformations.dynamic_zones.v1.DynamicZonesBlockV1
The DynamicZoneBlock is a transformer block designed to simplify polygon
so it's geometrically convex and then reduce number of vertices to requested amount.
This block is best suited when Zone needs to be created based on shape of detected object
(i.e. basketball field, road segment, zebra crossing etc.)
Input detections should be filtered and contain only desired classes of interest.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/dynamic_zone@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
required_number_of_vertices |
int |
Keep simplifying polygon until number of vertices matches this number. | ✅ |
scale_ratio |
float |
Expand resulting polygon along imaginary line from centroid to edge by this ratio. | ✅ |
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 Dynamic Zone in version v1.
- inputs:
Distance Measurement,Gaze Detection,Time in Zone,Detections Filter,Time in Zone,Dynamic Crop,Template Matching,Detections Classes Replacement,Instance Segmentation Model,Image Contours,Dynamic Zone,Instance Segmentation Model,Camera Focus,SIFT Comparison,Detections Transformation,Segment Anything 2 Model,Bounding Rectangle,Cosine Similarity,Velocity,Line Counter,SIFT Comparison,Detections Stitch,Path Deviation,Detection Offset,Identify Changes,Line Counter,Perspective Correction,Detections Stabilizer,Path Deviation,Pixel Color Count - outputs:
Circle Visualization,Background Color Visualization,Corner Visualization,VLM as Detector,VLM as Classifier,Polygon Zone Visualization,Cache Set,Path Deviation,Dot Visualization,Google Gemini,Detections Merge,Detection Offset,Roboflow Dataset Upload,Stability AI Inpainting,Pixelate Visualization,Line Counter,Detections Consensus,Distance Measurement,Webhook Sink,Color Visualization,Halo Visualization,Polygon Visualization,Grid Visualization,VLM as Classifier,Detections Classes Replacement,Dynamic Zone,Instance Segmentation Model,Email Notification,Object Detection Model,Classification Label Visualization,Llama 3.2 Vision,Roboflow Dataset Upload,Byte Tracker,Ellipse Visualization,Size Measurement,Bounding Box Visualization,Object Detection Model,Line Counter Visualization,Keypoint Detection Model,Trace Visualization,Label Visualization,Clip Comparison,Detections Transformation,Anthropic Claude,Crop Visualization,Detections Stitch,YOLO-World Model,Model Comparison Visualization,Perspective Correction,OpenAI,Byte Tracker,Path Deviation,Mask Visualization,Time in Zone,Detections Filter,Clip Comparison,Time in Zone,Dynamic Crop,Florence-2 Model,Byte Tracker,Instance Segmentation Model,Keypoint Detection Model,Buffer,Florence-2 Model,Reference Path Visualization,Triangle Visualization,Model Monitoring Inference Aggregator,Bounding Rectangle,Velocity,VLM as Detector,LMM For Classification,Roboflow Custom Metadata,Line Counter,Segment Anything 2 Model,Detections Stabilizer,Blur Visualization
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Dynamic Zone in version v1 has.
Bindings
-
input
predictions(instance_segmentation_prediction): .required_number_of_vertices(integer): Keep simplifying polygon until number of vertices matches this number.scale_ratio(float): Expand resulting polygon along imaginary line from centroid to edge by this ratio.
-
output
zones(list_of_values): List of values of any type.predictions(instance_segmentation_prediction): Prediction with detected bounding boxes and segmentation masks in form of sv.Detections(...) object.
Example JSON definition of step Dynamic Zone in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/dynamic_zone@v1",
"predictions": "$segmentation.predictions",
"required_number_of_vertices": 4,
"scale_ratio": 1.05
}