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

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
}