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:
SAM 3,Image Preprocessing,Anthropic Claude,Image Slicer,Time in Zone,Dynamic Crop,Mask Area Measurement,BoT-SORT Tracker,Bounding Box Visualization,Mask Edge Snap,Object Detection Model,Path Deviation,Absolute Static Crop,SIFT Comparison,Stitch Images,Stitch OCR Detections,OpenAI,Instance Segmentation Model,Email Notification,Stability AI Inpainting,Frame Delay,Distance Measurement,EasyOCR,Llama 3.2 Vision,Track Class Lock,Florence-2 Model,Gaze Detection,Roboflow Custom Metadata,Dynamic Zone,Auto Rotate on Edges,YOLO-World Model,Keypoint Detection Model,Detections Transformation,Byte Tracker,Stability AI Outpainting,Model Comparison Visualization,Slack Notification,Detections Classes Replacement,Line Counter Visualization,Camera Calibration,Byte Tracker,PLC Reader,Single-Label Classification Model,Clip Comparison,VLM As Detector,CogVLM,SORT Tracker,Camera Focus,Corner Visualization,Ellipse Visualization,PP-OCR,Morphological Transformation,Detections List Roll-Up,Anthropic Claude,Roboflow Visual Search,Color Visualization,Instance Segmentation Model,OpenAI,Triangle Visualization,Time in Zone,Detections Stabilizer,Detection Event Log,Object Detection Model,Image Contours,SAM 3,Image Threshold,SAM 3,Detections Merge,Current Time,Roboflow Visual Search Classifier,QR Code Generator,OpenAI-Compatible LLM,Florence-2 Model,Polygon Zone Visualization,Stitch OCR Detections,Roboflow Asset Library Attributes,Path Deviation,Microsoft SQL Server Sink,Moondream2,VLM As Classifier,Camera Focus,Image Convert Grayscale,Label Visualization,Llama 3.2 Vision,Stability AI Image Generation,Detection Offset,VLM As Detector,Instance Segmentation Model,Line Counter,MQTT Writer,Roboflow Dataset Upload,Local File Sink,Identify Outliers,VLM As Classifier,Bounding Rectangle,Event Writer,Google Gemini,Depth Estimation,Seg Preview,Byte Tracker,Google Gemini,OpenAI,Trace Visualization,Twilio SMS Notification,Pixel Color Count,SAM 3 Interactive,Detections Filter,LMM For Classification,Object Detection Model,Velocity,Webhook Sink,Halo Visualization,Mask Visualization,Template Matching,Pixelate Visualization,Twilio SMS/MMS Notification,MoonshotAI Kimi,Dot Visualization,Multi-Label Classification Model,Image Stack,OPC UA Writer Sink,Google Gemini,OC-SORT Tracker,Keypoint Visualization,LMM,Detections Combine,Image Slicer,PTZ Tracking (ONVIF),Time in Zone,OCR Model,Circle Visualization,Contrast Enhancement,Relative Static Crop,SAM2 Video Tracker,ByteTrack Tracker,Morphological Transformation,Per-Class Confidence Filter,Email Notification,Halo Visualization,Cosmos 3,Polygon Visualization,Qwen-VL,PLC Writer,Google Gemma,Crop Visualization,Qwen 3.5 API,Model Monitoring Inference Aggregator,Keypoint Detection Model,Icon Visualization,Heatmap Visualization,Motion Detection,Google Gemma API,Detections Consensus,Instance Segmentation Model,CSV Formatter,Image Blur,Segment Anything 2 Model,Background Color Visualization,Grid Visualization,SAM3 Video Tracker,Detections Stitch,Blur Visualization,GLM-OCR,Anthropic Claude,Reference Path Visualization,Classification Label Visualization,Google Vision OCR,Perspective Correction,Background Subtraction,Polygon Visualization,Contrast Equalization,SIFT,Qwen 3.6 API,Text Display,JSON Parser,MoonshotAI Kimi,OpenRouter,Qwen3.5-VL,Roboflow Vision Events,Identify Changes,OpenAI,SIFT Comparison,Keypoint Detection Model,Overlap Filter,S3 Sink,Line Counter,Roboflow Dataset Upload - outputs:
SAM 3,Image Preprocessing,Single-Label Classification Model,Anthropic Claude,Image Slicer,CLIP Embedding Model,Dynamic Crop,BoT-SORT Tracker,Bounding Box Visualization,Mask Edge Snap,Object Detection Model,QR Code Detection,Absolute Static Crop,SIFT Comparison,Stitch Images,OpenAI,Instance Segmentation Model,Email Notification,Stability AI Inpainting,Frame Delay,EasyOCR,Llama 3.2 Vision,Track Class Lock,Florence-2 Model,Gaze Detection,Auto Rotate on Edges,YOLO-World Model,Dominant Color,Keypoint Detection Model,Stability AI Outpainting,Model Comparison Visualization,Line Counter Visualization,Camera Calibration,Single-Label Classification Model,Clip Comparison,VLM As Detector,CogVLM,SORT Tracker,Corner Visualization,PP-OCR,Camera Focus,Ellipse Visualization,Morphological Transformation,Anthropic Claude,Roboflow Visual Search,Instance Segmentation Model,Color Visualization,OpenAI,Time in Zone,Triangle Visualization,Detections Stabilizer,Object Detection Model,Image Contours,SAM 3,Image Threshold,SAM 3,Barcode Detection,Roboflow Visual Search Classifier,Qwen2.5-VL,Florence-2 Model,Semantic Segmentation Model,SmolVLM2,Polygon Zone Visualization,GeoTag Detection,Moondream2,VLM As Classifier,Camera Focus,Image Convert Grayscale,Label Visualization,Llama 3.2 Vision,Stability AI Image Generation,VLM As Detector,Perception Encoder Embedding Model,Instance Segmentation Model,Roboflow Dataset Upload,VLM As Classifier,Google Gemini,Event Writer,Semantic Segmentation Model,Depth Estimation,Seg Preview,Byte Tracker,Google Gemini,OpenAI,Trace Visualization,Pixel Color Count,SAM 3 Interactive,LMM For Classification,Object Detection Model,Halo Visualization,Buffer,Mask Visualization,Template Matching,Twilio SMS/MMS Notification,Pixelate Visualization,MoonshotAI Kimi,Dot Visualization,Multi-Label Classification Model,Image Stack,Google Gemini,OC-SORT Tracker,Keypoint Visualization,LMM,Image Slicer,OCR Model,Circle Visualization,Contrast Enhancement,Relative Static Crop,SAM2 Video Tracker,ByteTrack Tracker,Morphological Transformation,Halo Visualization,Clip Comparison,Cosmos 3,Polygon Visualization,Qwen-VL,Google Gemma,Crop Visualization,Qwen 3.5 API,Qwen3-VL,Qwen3.5,Keypoint Detection Model,Single-Label Classification Model,Icon Visualization,Heatmap Visualization,Motion Detection,Multi-Label Classification Model,Google Gemma API,Instance Segmentation Model,SAM3 Video Tracker,Image Blur,Background Color Visualization,Detections Stitch,Segment Anything 2 Model,Blur Visualization,GLM-OCR,Anthropic Claude,Reference Path Visualization,Classification Label Visualization,Google Vision OCR,Background Subtraction,Perspective Correction,Polygon Visualization,Contrast Equalization,SIFT,Qwen 3.6 API,Text Display,MoonshotAI Kimi,OpenRouter,Qwen3.5-VL,Roboflow Vision Events,OpenAI,Keypoint Detection Model,Multi-Label Classification Model,Roboflow Dataset Upload
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,keypoint_detection_prediction,rle_instance_segmentation_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
}