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