Text Display¶
Class: TextDisplayVisualizationBlockV1
Source: inference.core.workflows.core_steps.visualizations.text_display.v1.TextDisplayVisualizationBlockV1
The Text Display block renders text on an image with full control over styling and positioning.
Dynamic Text Content¶
Text content can be parameterized with workflow execution outcomes using the same templating syntax as Email and SMS notification blocks:
text = "Detected {{ '{{' }} $parameters.count {{ '}}' }} objects of class {{ '{{' }} $parameters.class_name {{ '}}' }}"
Parameters are provided via the text_parameters field:
text_parameters = {
"count": "$steps.model.predictions",
"class_name": "$inputs.target_class"
}
You can apply transformations to parameters using text_parameters_operations:
text_parameters_operations = {
"count": [{"type": "SequenceLength"}]
}
Styling Options¶
- text_color: Color of the text. Supports:
- Supervision color names (uppercase): "WHITE", "BLACK", "RED", "GREEN", "BLUE", "YELLOW", "ROBOFLOW", etc.
- Hex format: "#RRGGBB" (e.g., "#FF0000" for red)
- RGB format: "rgb(R, G, B)" (e.g., "rgb(255, 0, 0)" for red)
- BGR format: "bgr(B, G, R)" (e.g., "bgr(0, 0, 255)" for red)
- background_color: Background color behind the text. Supports the same color formats as
text_color. Use "transparent" for no background. - background_opacity: Transparency of the background (0.0 = fully transparent, 1.0 = fully opaque)
- font_scale: Scale factor for the font size
- font_thickness: Thickness of the text strokes
- padding: Padding around the text in pixels
- text_align: Horizontal text alignment ("left", "center", "right")
- border_radius: Radius for rounded corners on the background
Positioning Options¶
The block supports both absolute and relative positioning:
Absolute Positioning (position_mode = "absolute"):
- position_x: X coordinate in pixels from the left edge
- position_y: Y coordinate in pixels from the top edge
Relative Positioning (position_mode = "relative"):
- anchor: Where to anchor the text ("center", "top_left", "top_center", "top_right",
"bottom_left", "bottom_center", "bottom_right", "center_left", "center_right")
- offset_x: Horizontal offset from the anchor point (positive = right)
- offset_y: Vertical offset from the anchor point (positive = down)
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/text_display@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
text |
str |
The text content to display. Supports parameter interpolation using {{ '{{' }} $parameters.name {{ '}}' }} syntax.. | ❌ |
text_parameters |
Dict[str, Union[bool, float, int, str]] |
Parameters to interpolate into the text.. | ✅ |
text_parameters_operations |
Dict[str, List[Union[ClassificationPropertyExtract, ConvertDictionaryToJSON, ConvertImageToBase64, ConvertImageToJPEG, DetectionsFilter, DetectionsOffset, DetectionsPropertyExtract, DetectionsRename, DetectionsSelection, DetectionsShift, DetectionsToDictionary, Divide, ExtractDetectionProperty, ExtractFrameMetadata, ExtractImageProperty, LookupTable, Multiply, NumberRound, NumericSequenceAggregate, PickDetectionsByParentClass, RandomNumber, SequenceAggregate, SequenceApply, SequenceElementsCount, SequenceLength, SequenceMap, SortDetections, StringMatches, StringSubSequence, StringToLowerCase, StringToUpperCase, TimestampToISOFormat, ToBoolean, ToNumber, ToString]]] |
Operations to apply to text parameters before interpolation.. | ❌ |
text_color |
str |
Color of the text. Supports supervision color names (WHITE, BLACK, RED, GREEN, BLUE, YELLOW, ROBOFLOW, etc.), hex format (#RRGGBB), rgb(R,G,B) format, or bgr(B,G,R) format.. | ✅ |
background_color |
str |
Background color behind the text. Supports the same color formats as text_color. Use 'transparent' for no background.. | ✅ |
background_opacity |
float |
Opacity of the background (0.0 = fully transparent, 1.0 = fully opaque).. | ✅ |
font_scale |
float |
Scale factor for the font size.. | ✅ |
font_thickness |
int |
Thickness of the text strokes.. | ✅ |
padding |
int |
Padding around the text in pixels.. | ✅ |
text_align |
str |
Horizontal alignment of the text within its bounding box.. | ✅ |
border_radius |
int |
Radius for rounded corners on the background rectangle.. | ✅ |
position_mode |
str |
Positioning mode: 'absolute' uses exact pixel coordinates, 'relative' uses anchor points with offsets.. | ✅ |
position_x |
int |
X coordinate (pixels from left edge) when using absolute positioning.. | ✅ |
position_y |
int |
Y coordinate (pixels from top edge) when using absolute positioning.. | ✅ |
anchor |
str |
Anchor point for relative positioning.. | ✅ |
offset_x |
int |
Horizontal offset from anchor point (positive = right).. | ✅ |
offset_y |
int |
Vertical offset from anchor point (positive = down).. | ✅ |
copy_image |
bool |
Whether to copy the input image before drawing (preserves original).. | ✅ |
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 Text Display in version v1.
- inputs:
Icon Visualization,Moondream2,Slack Notification,Label Visualization,Instance Segmentation Model,Multi-Label Classification Model,Dot Visualization,Camera Calibration,Trace Visualization,SAM 3,Time in Zone,Roboflow Custom Metadata,Dynamic Zone,Semantic Segmentation Model,Delta Filter,Relative Static Crop,Image Threshold,Keypoint Visualization,Overlap Filter,PTZ Tracking (ONVIF),Template Matching,Single-Label Classification Model,Path Deviation,Blur Visualization,Circle Visualization,Keypoint Detection Model,Crop Visualization,Detections Merge,Classification Label Visualization,OpenAI,Email Notification,Google Gemini,OpenAI,Identify Outliers,Twilio SMS Notification,YOLO-World Model,CSV Formatter,Twilio SMS/MMS Notification,Model Monitoring Inference Aggregator,Keypoint Detection Model,Anthropic Claude,Google Gemini,Image Convert Grayscale,Path Deviation,Detections Filter,Time in Zone,Distance Measurement,Stability AI Inpainting,Depth Estimation,S3 Sink,Inner Workflow,Model Comparison Visualization,Byte Tracker,SAM2 Video Tracker,Motion Detection,Google Gemini,Detections Classes Replacement,Detections List Roll-Up,CLIP Embedding Model,Florence-2 Model,Size Measurement,LMM,Dynamic Crop,Detection Offset,SAM 3,Barcode Detection,Clip Comparison,Perception Encoder Embedding Model,SIFT Comparison,Detections Stabilizer,Byte Tracker,Multi-Label Classification Model,Property Definition,VLM As Detector,Grid Visualization,Polygon Visualization,Webhook Sink,Semantic Segmentation Model,Seg Preview,Image Slicer,Bounding Rectangle,SORT Tracker,OC-SORT Tracker,OCR Model,Detection Event Log,Qwen3-VL,Object Detection Model,Object Detection Model,GLM-OCR,Roboflow Dataset Upload,Object Detection Model,Polygon Zone Visualization,Detections Stitch,SIFT,Morphological Transformation,Perspective Correction,Instance Segmentation Model,Florence-2 Model,Detections Combine,Cache Get,Anthropic Claude,Rate Limiter,Image Slicer,Absolute Static Crop,SmolVLM2,Cache Set,Data Aggregator,Email Notification,Camera Focus,EasyOCR,SAM 3,Gaze Detection,Polygon Visualization,OpenAI,VLM As Classifier,Stitch OCR Detections,Color Visualization,Continue If,Byte Tracker,Line Counter,Local File Sink,Image Contours,Mask Area Measurement,Roboflow Vision Events,OpenAI,Single-Label Classification Model,Llama 3.2 Vision,First Non Empty Or Default,Clip Comparison,Instance Segmentation Model,VLM As Detector,Cosine Similarity,JSON Parser,Time in Zone,Triangle Visualization,LMM For Classification,Pixel Color Count,Background Color Visualization,Stitch OCR Detections,Expression,Identify Changes,Line Counter,Qwen3.5-VL,CogVLM,Qwen2.5-VL,Image Blur,Stitch Images,Anthropic Claude,Dominant Color,Contrast Equalization,Corner Visualization,Velocity,Halo Visualization,Stability AI Image Generation,Detections Consensus,Reference Path Visualization,Buffer,QR Code Detection,Line Counter Visualization,ByteTrack Tracker,Multi-Label Classification Model,Keypoint Detection Model,Roboflow Dataset Upload,Heatmap Visualization,Text Display,VLM As Classifier,Segment Anything 2 Model,Camera Focus,Single-Label Classification Model,Detections Transformation,Image Preprocessing,SIFT Comparison,Environment Secrets Store,Bounding Box Visualization,Stability AI Outpainting,Halo Visualization,Background Subtraction,Dimension Collapse,QR Code Generator,Pixelate Visualization,Ellipse Visualization,Google Vision OCR,Mask Visualization - outputs:
Icon Visualization,Moondream2,Instance Segmentation Model,Label Visualization,Multi-Label Classification Model,Dot Visualization,Camera Calibration,Trace Visualization,SAM 3,Time in Zone,Semantic Segmentation Model,Relative Static Crop,Image Threshold,Keypoint Visualization,Template Matching,Single-Label Classification Model,Blur Visualization,Circle Visualization,Keypoint Detection Model,Crop Visualization,Email Notification,Classification Label Visualization,OpenAI,Google Gemini,OpenAI,YOLO-World Model,Twilio SMS/MMS Notification,Keypoint Detection Model,Anthropic Claude,Google Gemini,Image Convert Grayscale,Stability AI Inpainting,Depth Estimation,Model Comparison Visualization,SAM2 Video Tracker,Motion Detection,Google Gemini,CLIP Embedding Model,Florence-2 Model,LMM,Dynamic Crop,SAM 3,Barcode Detection,Clip Comparison,Perception Encoder Embedding Model,Detections Stabilizer,Byte Tracker,VLM As Detector,Multi-Label Classification Model,Polygon Visualization,Mask Visualization,Semantic Segmentation Model,Seg Preview,Image Slicer,SORT Tracker,OC-SORT Tracker,OCR Model,Qwen3-VL,Object Detection Model,Object Detection Model,GLM-OCR,Roboflow Dataset Upload,Object Detection Model,Polygon Zone Visualization,Detections Stitch,SIFT,Morphological Transformation,Instance Segmentation Model,Perspective Correction,Anthropic Claude,Image Slicer,Absolute Static Crop,SmolVLM2,EasyOCR,Camera Focus,SAM 3,Gaze Detection,Polygon Visualization,OpenAI,VLM As Classifier,Color Visualization,Image Contours,Roboflow Vision Events,OpenAI,Single-Label Classification Model,Llama 3.2 Vision,VLM As Detector,Instance Segmentation Model,Clip Comparison,LMM For Classification,Triangle Visualization,Pixel Color Count,Background Color Visualization,Qwen3.5-VL,CogVLM,Qwen2.5-VL,Image Blur,Anthropic Claude,Stitch Images,Dominant Color,Contrast Equalization,Corner Visualization,Stability AI Image Generation,Halo Visualization,Reference Path Visualization,QR Code Detection,Buffer,Line Counter Visualization,ByteTrack Tracker,Multi-Label Classification Model,Keypoint Detection Model,Roboflow Dataset Upload,Heatmap Visualization,Text Display,VLM As Classifier,Segment Anything 2 Model,Camera Focus,Single-Label Classification Model,Image Preprocessing,SIFT Comparison,Stability AI Outpainting,Bounding Box Visualization,Halo Visualization,Background Subtraction,Pixelate Visualization,Google Vision OCR,Ellipse Visualization,Florence-2 Model
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Text Display in version v1 has.
Bindings
-
input
image(image): The image to display text on..text_parameters(*): Parameters to interpolate into the text..text_color(string): Color of the text. Supports supervision color names (WHITE, BLACK, RED, GREEN, BLUE, YELLOW, ROBOFLOW, etc.), hex format (#RRGGBB), rgb(R,G,B) format, or bgr(B,G,R) format..background_color(string): Background color behind the text. Supports the same color formats as text_color. Use 'transparent' for no background..background_opacity(float_zero_to_one): Opacity of the background (0.0 = fully transparent, 1.0 = fully opaque)..font_scale(float): Scale factor for the font size..font_thickness(integer): Thickness of the text strokes..padding(integer): Padding around the text in pixels..text_align(string): Horizontal alignment of the text within its bounding box..border_radius(integer): Radius for rounded corners on the background rectangle..position_mode(string): Positioning mode: 'absolute' uses exact pixel coordinates, 'relative' uses anchor points with offsets..position_x(integer): X coordinate (pixels from left edge) when using absolute positioning..position_y(integer): Y coordinate (pixels from top edge) when using absolute positioning..anchor(string): Anchor point for relative positioning..offset_x(integer): Horizontal offset from anchor point (positive = right)..offset_y(integer): Vertical offset from anchor point (positive = down)..copy_image(boolean): Whether to copy the input image before drawing (preserves original)..
-
output
image(image): Image in workflows.
Example JSON definition of step Text Display in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/text_display@v1",
"image": "$inputs.image",
"text": "Detection count: {{ '{{' }} $parameters.count {{ '}}' }}",
"text_parameters": {
"class_name": "$inputs.target_class",
"count": "$steps.model.predictions"
},
"text_parameters_operations": {
"count": [
{
"type": "SequenceLength"
}
]
},
"text_color": "WHITE",
"background_color": "BLACK",
"background_opacity": 1.0,
"font_scale": 1.0,
"font_thickness": 1,
"padding": 5,
"text_align": "left",
"border_radius": 0,
"position_mode": "absolute",
"position_x": 10,
"position_y": 10,
"anchor": "center",
"offset_x": 0,
"offset_y": 0,
"copy_image": true
}