Icon Visualization

Class: IconVisualizationBlockV1

Source: inference.core.workflows.core_steps.visualizations.icon.v1.IconVisualizationBlockV1

Place custom icon images on images either at fixed positions (static mode) or dynamically positioned on detected objects (dynamic mode), useful for watermarks, labels, badges, or visual markers.

How This Block Works

This block takes an image and optionally detection predictions, then places a custom icon image on the image. The block supports two modes:

Static Mode (for watermarks and fixed positioning): 1. Takes an image and an icon image as input 2. Places the icon at fixed x and y coordinates on the image 3. Supports negative coordinates for positioning from the right or bottom edges 4. Returns an annotated image with the icon at the specified static location

Dynamic Mode (for detection-based positioning): 1. Takes an image, an icon image, and detection predictions as input 2. Positions the icon on each detected object based on the selected anchor point (center, corners, edges, or center of mass) 3. Places the icon at the same position relative to each detection 4. Returns an annotated image with icons overlaid on detected objects

The block supports PNG images with transparency (alpha channel), allowing icons to blend naturally with the background. Icons can be resized to any width and height, making them suitable for various use cases from small badges to large watermarks. In static mode, icons are placed at fixed coordinates, making it ideal for watermarks or branding. In dynamic mode, icons automatically follow detected objects, making it useful for labeling, categorizing, or marking detected items with custom visual indicators.

Common Use Cases

• Watermarks and Branding: Place logos, watermarks, or branding elements at fixed positions (static mode) on images or videos for content protection, copyright marking, or brand identification
• Object Labeling with Icons: Place custom icons on detected objects (dynamic mode) to categorize, label, or mark objects with visual indicators (e.g., warning icons on unsafe objects, category icons for products, status badges)
• Visual Status Indicators: Display status icons (e.g., checkmarks, warning signs, information badges) on detected objects based on classification results, confidence levels, or custom logic for quick visual feedback
• Product Marking and Categorization: Place category icons, product type indicators, or custom markers on detected products in retail, e-commerce, or inventory management workflows
• Custom Annotation Systems: Create custom annotation workflows with specialized icons for quality control, defect marking, or compliance tracking in manufacturing or inspection workflows
• Interactive UI Elements: Add icon-based visual elements to images or videos for user interfaces, dashboards, or interactive applications where custom icons provide intuitive visual cues

Connecting to Other Blocks

The annotated image from this block can be connected to:

• Other visualization blocks (e.g., Label Visualization, Bounding Box Visualization, Polygon Visualization) to combine icon placement with additional annotations for comprehensive visualization
• Data storage blocks (e.g., Local File Sink, CSV Formatter, Roboflow Dataset Upload) to save images with icons for documentation, reporting, or archiving
• Webhook blocks to send visualized results with icons to external systems, APIs, or web applications for display in dashboards or monitoring tools
• Notification blocks (e.g., Email Notification, Slack Notification) to send annotated images with icons as visual evidence in alerts or reports
• Video output blocks to create annotated video streams or recordings with icons for live monitoring, tracking visualization, or post-processing analysis

Type identifier

Use the following identifier in step "type" field: roboflow_core/icon_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..	✅
mode	str	Mode for placing icons. 'static' mode places the icon at fixed x,y coordinates (useful for watermarks or fixed-position elements). 'dynamic' mode places icons on detected objects based on their positions (useful for object labeling or categorization)..	✅
icon_width	int	Width of the icon in pixels. The icon image will be resized to this width while maintaining aspect ratio if height is also specified..	✅
icon_height	int	Height of the icon in pixels. The icon image will be resized to this height while maintaining aspect ratio if width is also specified..	✅
position	str	Anchor position for placing icons relative to each detection's bounding box (dynamic mode only). Options include: CENTER (center of box), corners (TOP_LEFT, TOP_RIGHT, BOTTOM_LEFT, BOTTOM_RIGHT), edge midpoints (TOP_CENTER, CENTER_LEFT, CENTER_RIGHT, BOTTOM_CENTER), or CENTER_OF_MASS (center of mass of the object)..	✅
x_position	int	X coordinate for static mode positioning. Positive values position from the left edge of the image. Negative values position from the right edge (e.g., -10 places the icon 10 pixels from the right edge)..	✅
y_position	int	Y coordinate for static mode positioning. Positive values position from the top edge of the image. Negative values position from the bottom edge (e.g., -10 places the icon 10 pixels from the bottom edge)..	✅

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 Icon Visualization in version v1.

• inputs: Google Vision OCR, VLM as Detector, SIFT, Identify Changes, Dynamic Zone, EasyOCR, Icon Visualization, OpenAI, Circle Visualization, Pixelate Visualization, Twilio SMS/MMS Notification, Line Counter Visualization, Detection Event Log, Camera Calibration, Halo Visualization, Relative Static Crop, QR Code Generator, Seg Preview, Identify Outliers, Detections Stabilizer, Moondream2, Bounding Rectangle, Image Slicer, Keypoint Detection Model, Florence-2 Model, Camera Focus, Byte Tracker, Anthropic Claude, OCR Model, Email Notification, Gaze Detection, Mask Visualization, Anthropic Claude, Contrast Equalization, PTZ Tracking (ONVIF).md), SIFT Comparison, Detections Stitch, Instance Segmentation Model, Byte Tracker, Depth Estimation, Google Gemini, Stitch Images, Path Deviation, Template Matching, YOLO-World Model, Florence-2 Model, Triangle Visualization, Label Visualization, LMM, SIFT Comparison, Detection Offset, Text Display, CSV Formatter, Keypoint Visualization, Pixel Color Count, Detections Combine, JSON Parser, VLM as Classifier, Distance Measurement, Color Visualization, Image Contours, Path Deviation, Roboflow Dataset Upload, Bounding Box Visualization, Morphological Transformation, Line Counter, Detections Classes Replacement, OpenAI, Single-Label Classification Model, Llama 3.2 Vision, Multi-Label Classification Model, Roboflow Dataset Upload, Byte Tracker, Velocity, Model Comparison Visualization, Google Gemini, Time in Zone, Polygon Visualization, Image Slicer, Dynamic Crop, Image Threshold, Local File Sink, Reference Path Visualization, Trace Visualization, Email Notification, Time in Zone, Webhook Sink, Blur Visualization, OpenAI, Ellipse Visualization, Crop Visualization, Polygon Zone Visualization, OpenAI, Grid Visualization, Overlap Filter, Stability AI Inpainting, Detections Transformation, Classification Label Visualization, VLM as Classifier, SAM 3, Stitch OCR Detections, Roboflow Custom Metadata, Instance Segmentation Model, Model Monitoring Inference Aggregator, Image Blur, Corner Visualization, Detections Merge, LMM For Classification, Object Detection Model, Stability AI Outpainting, Time in Zone, SAM 3, Absolute Static Crop, SAM 3, Detections List Roll-Up, VLM as Detector, Background Subtraction, Segment Anything 2 Model, Keypoint Detection Model, Stability AI Image Generation, Line Counter, Detections Consensus, Camera Focus, Detections Filter, Clip Comparison, Twilio SMS Notification, Dot Visualization, CogVLM, Perspective Correction, Image Convert Grayscale, Background Color Visualization, Slack Notification, Motion Detection, Image Preprocessing, Object Detection Model, Anthropic Claude, Google Gemini
• outputs: Byte Tracker, Google Vision OCR, VLM as Detector, Roboflow Dataset Upload, Single-Label Classification Model, SIFT, Qwen3-VL, Model Comparison Visualization, Google Gemini, Polygon Visualization, EasyOCR, Image Slicer, Dynamic Crop, Image Threshold, Icon Visualization, Reference Path Visualization, OpenAI, Circle Visualization, Trace Visualization, Email Notification, Pixelate Visualization, Twilio SMS/MMS Notification, Line Counter Visualization, Camera Calibration, Time in Zone, Halo Visualization, Blur Visualization, Relative Static Crop, OpenAI, QR Code Detection, Ellipse Visualization, Dominant Color, Seg Preview, Crop Visualization, Polygon Zone Visualization, Buffer, Multi-Label Classification Model, Barcode Detection, Perception Encoder Embedding Model, Detections Stabilizer, Moondream2, OpenAI, Stability AI Inpainting, Image Slicer, CLIP Embedding Model, Keypoint Detection Model, Florence-2 Model, VLM as Classifier, SAM 3, Classification Label Visualization, Instance Segmentation Model, Camera Focus, Image Blur, Corner Visualization, Anthropic Claude, Gaze Detection, OCR Model, LMM For Classification, Object Detection Model, Mask Visualization, Anthropic Claude, Stability AI Outpainting, Contrast Equalization, SAM 3, Absolute Static Crop, SAM 3, Qwen2.5-VL, Clip Comparison, VLM as Detector, Background Subtraction, Detections Stitch, Instance Segmentation Model, SmolVLM2, Depth Estimation, Google Gemini, Segment Anything 2 Model, Stitch Images, Keypoint Detection Model, Template Matching, Stability AI Image Generation, YOLO-World Model, Florence-2 Model, Triangle Visualization, Label Visualization, LMM, Camera Focus, SIFT Comparison, Text Display, Clip Comparison, Keypoint Visualization, Dot Visualization, Pixel Color Count, CogVLM, Perspective Correction, Image Convert Grayscale, VLM as Classifier, Color Visualization, Background Color Visualization, Image Contours, Motion Detection, Object Detection Model, Image Preprocessing, Roboflow Dataset Upload, Anthropic Claude, Bounding Box Visualization, Google Gemini, Morphological Transformation, OpenAI, Llama 3.2 Vision, Multi-Label Classification Model, Single-Label Classification Model

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Icon 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..
  • icon (image): The icon image to place on the input image. PNG format with transparency (alpha channel) is recommended for best results, as it allows the icon to blend naturally with the background. The icon will be resized to the specified width and height..
  • mode (string): Mode for placing icons. 'static' mode places the icon at fixed x,y coordinates (useful for watermarks or fixed-position elements). 'dynamic' mode places icons on detected objects based on their positions (useful for object labeling or categorization)..
  • predictions (Union[instance_segmentation_prediction, object_detection_prediction, rle_instance_segmentation_prediction, keypoint_detection_prediction]): Model predictions to place icons on (required for dynamic mode). Icons will be positioned on each detected object based on the selected position anchor point..
  • icon_width (integer): Width of the icon in pixels. The icon image will be resized to this width while maintaining aspect ratio if height is also specified..
  • icon_height (integer): Height of the icon in pixels. The icon image will be resized to this height while maintaining aspect ratio if width is also specified..
  • position (string): Anchor position for placing icons relative to each detection's bounding box (dynamic mode only). Options include: CENTER (center of box), corners (TOP_LEFT, TOP_RIGHT, BOTTOM_LEFT, BOTTOM_RIGHT), edge midpoints (TOP_CENTER, CENTER_LEFT, CENTER_RIGHT, BOTTOM_CENTER), or CENTER_OF_MASS (center of mass of the object)..
  • x_position (integer): X coordinate for static mode positioning. Positive values position from the left edge of the image. Negative values position from the right edge (e.g., -10 places the icon 10 pixels from the right edge)..
  • y_position (integer): Y coordinate for static mode positioning. Positive values position from the top edge of the image. Negative values position from the bottom edge (e.g., -10 places the icon 10 pixels from the bottom edge)..

• output

  • image (image): Image in workflows.

Example JSON definition of step Icon Visualization in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/icon_visualization@v1",
    "image": "$inputs.image",
    "copy_image": true,
    "icon": "$inputs.icon",
    "mode": "static",
    "predictions": "$steps.object_detection_model.predictions",
    "icon_width": 64,
    "icon_height": 64,
    "position": "TOP_CENTER",
    "x_position": 10,
    "y_position": 10
}