Ellipse Visualization¶
Class: EllipseVisualizationBlockV1
Source: inference.core.workflows.core_steps.visualizations.ellipse.v1.EllipseVisualizationBlockV1
Draw elliptical outlines around detected objects, providing oval-shaped annotations that can be customized to full ellipses or partial arcs, offering more flexible geometry than circular visualizations.
How This Block Works¶
This block takes an image and detection predictions and draws elliptical (oval-shaped) outlines around each detected object. The block:
- Takes an image and predictions as input
- Identifies bounding box coordinates for each detected object
- Calculates the center point and dimensions (width and height) for each detection based on its bounding box
- Applies color styling based on the selected color palette, with colors assigned by class, index, or track ID
- Draws elliptical outlines around each detected object using Supervision's EllipseAnnotator
- Applies the specified thickness to control the line width of the elliptical outlines
- Uses start and end angle parameters to draw either full ellipses or partial elliptical arcs
- Returns an annotated image with elliptical outlines overlaid on the original image
The block draws ellipses that are typically fitted to each detection's bounding box, creating oval-shaped outlines that adapt to the object's aspect ratio (unlike circles which are always round). Ellipses provide more flexible geometry than circles, as they can represent both round and elongated objects more accurately. The start and end angle parameters allow you to draw full ellipses (360 degrees) or partial arcs, providing additional visual style options. Unlike circle visualization (which always draws complete circles), ellipse visualization can draw partial arcs, creating distinctive visual markers while still clearly indicating object locations.
Common Use Cases¶
- Oval and Elongated Object Highlighting: Highlight detected objects with elliptical outlines when objects are oval-shaped or elongated (e.g., vehicles, elongated products, elliptical objects) where ellipses provide a better fit than circular or rectangular shapes
- Flexible Geometric Visualization: Use elliptical shapes as a more geometrically flexible alternative to circles or bounding boxes, adapting to object aspect ratios for more accurate visual representation
- Partial Arc Annotations: Draw partial elliptical arcs (using start and end angles) to create distinctive, stylized visual markers that indicate object locations with a unique visual style
- Aesthetic Visualization Alternatives: Create visually distinct annotations compared to standard bounding boxes or circles for design purposes, artistic visualizations, or when elliptical shapes better match design aesthetics
- Object Shape Adaptation: Use ellipses when objects have non-square aspect ratios where circular outlines would be less accurate, providing better visual fit for rectangular or elongated objects
- Design and UI Applications: Integrate elliptical outlines into user interfaces, dashboards, or interactive applications where oval shapes provide a softer, more organic visual style than angular rectangles
Connecting to Other Blocks¶
The annotated image from this block can be connected to:
- Other visualization blocks (e.g., Label Visualization, Dot Visualization, Bounding Box Visualization) to combine elliptical outlines with additional annotations for comprehensive visualization
- Data storage blocks (e.g., Local File Sink, CSV Formatter, Roboflow Dataset Upload) to save annotated images with elliptical outlines for documentation, reporting, or analysis
- Webhook blocks to send visualized results with elliptical outlines 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 elliptical outlines as visual evidence in alerts or reports
- Video output blocks to create annotated video streams or recordings with elliptical outlines for live monitoring, tracking visualization, or post-processing analysis
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/ellipse_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.. | ✅ |
color_palette |
str |
Select a color palette for the visualised elements.. | ✅ |
palette_size |
int |
Specify the number of colors in the palette. This applies when using custom or Matplotlib palettes.. | ✅ |
custom_colors |
List[str] |
Define a list of custom colors for bounding boxes in HEX format.. | ✅ |
color_axis |
str |
Choose how bounding box colors are assigned.. | ✅ |
thickness |
int |
Thickness of the ellipse outline in pixels. Higher values create thicker, more visible elliptical outlines.. | ✅ |
start_angle |
int |
Starting angle for drawing the ellipse arc in degrees. Used together with end_angle to control whether a full ellipse (360 degrees) or partial arc is drawn. Angles are measured from the positive x-axis (0 degrees = right, 90 degrees = down, 180 degrees = left, 270 degrees = up).. | ✅ |
end_angle |
int |
Ending angle for drawing the ellipse arc in degrees. Used together with start_angle to control whether a full ellipse (360 degrees) or partial arc is drawn. To draw a full ellipse, set end_angle = start_angle + 360 (or equivalent). Angles are measured from the positive x-axis (0 degrees = right, 90 degrees = down, 180 degrees = left, 270 degrees = up).. | ✅ |
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 Ellipse 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,Clip Comparison,Roboflow Custom Metadata,Detections Merge,Halo Visualization,Dynamic Zone,Keypoint Detection Model,Qwen-VL,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,PLC ModbusTCP,VLM As Detector,Florence-2 Model,Motion Detection,Heatmap Visualization,OCR Model,OpenAI,Detections Filter,Blur Visualization,Dimension Collapse,Depth Estimation,Instance Segmentation Model,Stability AI Outpainting,Anthropic Claude,YOLO-World Model,Google Gemini,Clip Comparison,Google Gemini,PLC EthernetIP,Background Subtraction,Keypoint Visualization,CSV Formatter,Buffer,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,Time in Zone,Google Gemma API,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,Size Measurement,Stability AI Inpainting,PTZ Tracking (ONVIF),Classification Label Visualization,Bounding Rectangle,SAM2 Video Tracker,Stitch OCR Detections,Event Writer,Grid Visualization,Qwen3.5-VL,Mask Visualization,Byte Tracker,Llama 3.2 Vision,Reference Path Visualization,Image Slicer,Label Visualization,Identify Outliers,Velocity,Byte Tracker,SIFT Comparison,OPC UA Writer Sink,Dot Visualization,Identify Changes,Dynamic Crop,Detections Stitch,Circle Visualization,Path Deviation,BoT-SORT Tracker,SAM3 Video Tracker,Camera Focus,Llama 3.2 Vision,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,SAM 3,OpenAI,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,Object Detection Model,Anthropic Claude,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
Ellipse 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[keypoint_detection_prediction,object_detection_prediction,rle_instance_segmentation_prediction,instance_segmentation_prediction]): Model predictions to visualize..color_palette(string): Select a color palette for the visualised elements..palette_size(integer): Specify the number of colors in the palette. This applies when using custom or Matplotlib palettes..custom_colors(list_of_values): Define a list of custom colors for bounding boxes in HEX format..color_axis(string): Choose how bounding box colors are assigned..thickness(integer): Thickness of the ellipse outline in pixels. Higher values create thicker, more visible elliptical outlines..start_angle(integer): Starting angle for drawing the ellipse arc in degrees. Used together with end_angle to control whether a full ellipse (360 degrees) or partial arc is drawn. Angles are measured from the positive x-axis (0 degrees = right, 90 degrees = down, 180 degrees = left, 270 degrees = up)..end_angle(integer): Ending angle for drawing the ellipse arc in degrees. Used together with start_angle to control whether a full ellipse (360 degrees) or partial arc is drawn. To draw a full ellipse, set end_angle = start_angle + 360 (or equivalent). Angles are measured from the positive x-axis (0 degrees = right, 90 degrees = down, 180 degrees = left, 270 degrees = up)..
-
output
image(image): Image in workflows.
Example JSON definition of step Ellipse Visualization in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/ellipse_visualization@v1",
"image": "$inputs.image",
"copy_image": true,
"predictions": "$steps.object_detection_model.predictions",
"color_palette": "DEFAULT",
"palette_size": 10,
"custom_colors": [
"#FF0000",
"#00FF00",
"#0000FF"
],
"color_axis": "CLASS",
"thickness": 2,
"start_angle": -45,
"end_angle": 235
}