Image Blur

Class: ImageBlurBlockV1

Source: inference.core.workflows.core_steps.classical_cv.image_blur.v1.ImageBlurBlockV1

Apply a blur to an image. The blur type and kernel size can be specified.

Type identifier

Use the following identifier in step "type" field: roboflow_core/image_blur@v1to add the block as as step in your workflow.

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
blur_type	str	Type of Blur to perform on image..	✅
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 Image Blur in version v1.

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

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Image Blur in version v1 has.

Bindings

• input

  • image (image): The input image for this step..
  • blur_type (string): Type of Blur to perform on image..
  • kernel_size (integer): Size of the average pooling kernel used for blurring..

• output

  • image (image): Image in workflows.

Example JSON definition of step Image Blur in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/image_blur@v1",
    "image": "$inputs.image",
    "blur_type": "average",
    "kernel_size": 5
}