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

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
}