Blur Visualization

Class: BlurVisualizationBlockV1

Source: inference.core.workflows.core_steps.visualizations.blur.v1.BlurVisualizationBlockV1

The BlurVisualization block blurs detected objects in an image using Supervision's sv.BlurAnnotator.

Type identifier

Use the following identifier in step "type" field: roboflow_core/blur_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..	✅
kernel_size	int	Size of the average pooling kernel used for blurring..	✅

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 Blur Visualization in version v1.

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

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Blur 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..
  • predictions (Union[object_detection_prediction, keypoint_detection_prediction, instance_segmentation_prediction]): Model predictions to visualize..
  • kernel_size (integer): Size of the average pooling kernel used for blurring..

• output

  • image (image): Image in workflows.

Example JSON definition of step Blur Visualization in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/blur_visualization@v1",
    "image": "$inputs.image",
    "copy_image": true,
    "predictions": "$steps.object_detection_model.predictions",
    "kernel_size": 15
}