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

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
}