Pixelate Visualization

Class: PixelateVisualizationBlockV1

Source: inference.core.workflows.core_steps.visualizations.pixelate.v1.PixelateVisualizationBlockV1

The PixelateVisualization block pixelates detected objects in an image using Supervision's sv.PixelateAnnotator.

Type identifier

Use the following identifier in step "type" field: roboflow_core/pixelate_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..	✅
pixel_size	int	Size of the pixelation..	✅

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 Pixelate Visualization in version v1.

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

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Pixelate 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..
  • pixel_size (integer): Size of the pixelation..

• output

  • image (image): Image in workflows.

Example JSON definition of step Pixelate Visualization in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/pixelate_visualization@v1",
    "image": "$inputs.image",
    "copy_image": true,
    "predictions": "$steps.object_detection_model.predictions",
    "pixel_size": 20
}