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

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
}