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

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, instance_segmentation_prediction, keypoint_detection_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
}