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:
Dynamic Crop,OCR Model,Image Blur,Background Subtraction,Google Vision OCR,Google Gemini,Image Preprocessing,Local File Sink,Object Detection Model,Single-Label Classification Model,Bounding Box Visualization,Model Monitoring Inference Aggregator,Keypoint Detection Model,Camera Focus,Identify Outliers,Dot Visualization,Gaze Detection,Florence-2 Model,Roboflow Dataset Upload,CSV Formatter,Depth Estimation,Polygon Visualization,OpenAI,Line Counter,Image Slicer,Detections List Roll-Up,Line Counter Visualization,Heatmap Visualization,Morphological Transformation,Stability AI Image Generation,Google Gemini,Distance Measurement,Keypoint Visualization,Keypoint Detection Model,Background Color Visualization,Label Visualization,Polygon Visualization,LMM,CogVLM,Time in Zone,Triangle Visualization,Stability AI Outpainting,Mask Visualization,Color Visualization,Detections Combine,Text Display,Bounding Rectangle,Reference Path Visualization,Llama 3.2 Vision,OpenAI,Image Threshold,Clip Comparison,Classification Label Visualization,Clip Comparison,Polygon Zone Visualization,Image Contours,VLM As Classifier,Roboflow Custom Metadata,Dynamic Zone,LMM For Classification,Velocity,Halo Visualization,Blur Visualization,Path Deviation,Absolute Static Crop,Anthropic Claude,SAM 3,Detections Transformation,Ellipse Visualization,Identify Changes,Crop Visualization,SIFT Comparison,Path Deviation,Trace Visualization,Twilio SMS Notification,Stitch Images,Detections Stabilizer,Size Measurement,Detections Merge,Time in Zone,Motion Detection,Email Notification,SIFT Comparison,OpenAI,Seg Preview,Time in Zone,Instance Segmentation Model,Anthropic Claude,Multi-Label Classification Model,Email Notification,Slack Notification,Twilio SMS/MMS Notification,Detections Stitch,VLM As Detector,Camera Focus,SAM 3,Stitch OCR Detections,Perspective Correction,PTZ Tracking (ONVIF),Moondream2,Camera Calibration,Corner Visualization,Icon Visualization,Overlap Filter,Qwen3.5-VL,Byte Tracker,VLM As Detector,Halo Visualization,JSON Parser,Detection Event Log,Pixelate Visualization,Contrast Equalization,Dimension Collapse,VLM As Classifier,Instance Segmentation Model,Detections Classes Replacement,Relative Static Crop,Line Counter,Stitch OCR Detections,Webhook Sink,Circle Visualization,Image Convert Grayscale,Grid Visualization,Mask Area Measurement,Byte Tracker,Florence-2 Model,Buffer,SAM 3,SIFT,YOLO-World Model,Object Detection Model,Byte Tracker,Detections Consensus,Template Matching,Anthropic Claude,Google Gemini,Model Comparison Visualization,Detection Offset,QR Code Generator,EasyOCR,Image Slicer,S3 Sink,Stability AI Inpainting,Segment Anything 2 Model,Detections Filter,OpenAI,Pixel Color Count,Roboflow Dataset Upload - outputs:
Dynamic Crop,OCR Model,Barcode Detection,Motion Detection,Email Notification,Image Blur,Background Subtraction,Google Vision OCR,SIFT Comparison,Google Gemini,OpenAI,Image Preprocessing,Qwen2.5-VL,Seg Preview,Object Detection Model,Instance Segmentation Model,Single-Label Classification Model,Bounding Box Visualization,Multi-Label Classification Model,Anthropic Claude,Multi-Label Classification Model,Keypoint Detection Model,Detections Stitch,Twilio SMS/MMS Notification,Camera Focus,VLM As Detector,Gaze Detection,Florence-2 Model,Dot Visualization,Roboflow Dataset Upload,Camera Focus,SAM 3,Depth Estimation,Polygon Visualization,Moondream2,OpenAI,Perspective Correction,Image Slicer,Icon Visualization,Corner Visualization,Camera Calibration,Qwen3.5-VL,Line Counter Visualization,Heatmap Visualization,Google Gemini,Morphological Transformation,Stability AI Image Generation,Keypoint Visualization,VLM As Detector,Keypoint Detection Model,Halo Visualization,Background Color Visualization,Label Visualization,QR Code Detection,Polygon Visualization,Pixelate Visualization,LMM,CogVLM,Time in Zone,Single-Label Classification Model,Qwen3-VL,Contrast Equalization,Triangle Visualization,Stability AI Outpainting,Mask Visualization,VLM As Classifier,Color Visualization,Instance Segmentation Model,Dominant Color,Text Display,Relative Static Crop,Reference Path Visualization,OpenAI,Llama 3.2 Vision,Clip Comparison,Clip Comparison,Classification Label Visualization,Image Threshold,Circle Visualization,Polygon Zone Visualization,Image Contours,Image Convert Grayscale,VLM As Classifier,Byte Tracker,Buffer,Florence-2 Model,SmolVLM2,SAM 3,Perception Encoder Embedding Model,LMM For Classification,SIFT,YOLO-World Model,Halo Visualization,Template Matching,Object Detection Model,Semantic Segmentation Model,Anthropic Claude,Google Gemini,Model Comparison Visualization,Blur Visualization,EasyOCR,Absolute Static Crop,Image Slicer,Anthropic Claude,SAM 3,CLIP Embedding Model,Stability AI Inpainting,Ellipse Visualization,Crop Visualization,Trace Visualization,Segment Anything 2 Model,Stitch Images,Detections Stabilizer,OpenAI,Pixel Color Count,Roboflow Dataset Upload
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[object_detection_prediction,instance_segmentation_prediction,keypoint_detection_prediction,rle_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
}