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

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[instance_segmentation_prediction, keypoint_detection_prediction, object_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
}