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

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
}