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:

1. Takes an image and predictions as input
2. Identifies bounding box coordinates for each detected object
3. Calculates the center point and dimensions (width and height) for each detection based on its bounding box
4. Applies color styling based on the selected color palette, with colors assigned by class, index, or track ID
5. Draws elliptical outlines around each detected object using Supervision's EllipseAnnotator
6. Applies the specified thickness to control the line width of the elliptical outlines
7. Uses start and end angle parameters to draw either full ellipses or partial elliptical arcs
8. 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: Google Vision OCR, VLM as Detector, SIFT, Identify Changes, Dynamic Zone, EasyOCR, Icon Visualization, OpenAI, Circle Visualization, Pixelate Visualization, Twilio SMS/MMS Notification, Line Counter Visualization, Detection Event Log, Camera Calibration, Halo Visualization, Relative Static Crop, QR Code Generator, Seg Preview, Identify Outliers, Detections Stabilizer, Moondream2, Bounding Rectangle, Image Slicer, Keypoint Detection Model, Florence-2 Model, Camera Focus, Byte Tracker, Anthropic Claude, OCR Model, Email Notification, Gaze Detection, Mask Visualization, Anthropic Claude, Contrast Equalization, PTZ Tracking (ONVIF).md), Clip Comparison, SIFT Comparison, Detections Stitch, Instance Segmentation Model, Byte Tracker, Depth Estimation, Google Gemini, Stitch Images, Path Deviation, Template Matching, YOLO-World Model, Florence-2 Model, Triangle Visualization, Label Visualization, LMM, SIFT Comparison, Detection Offset, Text Display, CSV Formatter, Keypoint Visualization, Pixel Color Count, Detections Combine, JSON Parser, VLM as Classifier, Distance Measurement, Color Visualization, Image Contours, Path Deviation, Roboflow Dataset Upload, Bounding Box Visualization, Morphological Transformation, Line Counter, Detections Classes Replacement, OpenAI, Llama 3.2 Vision, Single-Label Classification Model, Multi-Label Classification Model, Roboflow Dataset Upload, Byte Tracker, Velocity, Model Comparison Visualization, Time in Zone, Google Gemini, Polygon Visualization, Dimension Collapse, Image Slicer, Dynamic Crop, Image Threshold, Local File Sink, Reference Path Visualization, Trace Visualization, Email Notification, Time in Zone, Webhook Sink, Blur Visualization, OpenAI, Ellipse Visualization, Crop Visualization, Polygon Zone Visualization, Buffer, OpenAI, Grid Visualization, Overlap Filter, Stability AI Inpainting, Detections Transformation, Classification Label Visualization, VLM as Classifier, SAM 3, Instance Segmentation Model, Roboflow Custom Metadata, Stitch OCR Detections, Size Measurement, Model Monitoring Inference Aggregator, Image Blur, Corner Visualization, Detections Merge, Object Detection Model, LMM For Classification, Stability AI Outpainting, Time in Zone, SAM 3, Absolute Static Crop, SAM 3, Detections List Roll-Up, VLM as Detector, Background Subtraction, Segment Anything 2 Model, Keypoint Detection Model, Stability AI Image Generation, Line Counter, Detections Consensus, Camera Focus, Detections Filter, Clip Comparison, Twilio SMS Notification, Dot Visualization, CogVLM, Perspective Correction, Image Convert Grayscale, Background Color Visualization, Slack Notification, Motion Detection, Image Preprocessing, Object Detection Model, Anthropic Claude, Google Gemini
• outputs: Byte Tracker, Google Vision OCR, VLM as Detector, Roboflow Dataset Upload, Single-Label Classification Model, SIFT, Qwen3-VL, Model Comparison Visualization, Google Gemini, Polygon Visualization, EasyOCR, Image Slicer, Dynamic Crop, Image Threshold, Icon Visualization, Reference Path Visualization, OpenAI, Circle Visualization, Trace Visualization, Email Notification, Pixelate Visualization, Twilio SMS/MMS Notification, Line Counter Visualization, Camera Calibration, Time in Zone, Halo Visualization, Blur Visualization, Relative Static Crop, OpenAI, QR Code Detection, Ellipse Visualization, Dominant Color, Seg Preview, Crop Visualization, Polygon Zone Visualization, Buffer, Multi-Label Classification Model, Barcode Detection, Perception Encoder Embedding Model, Detections Stabilizer, Moondream2, OpenAI, Stability AI Inpainting, Image Slicer, CLIP Embedding Model, Keypoint Detection Model, Florence-2 Model, VLM as Classifier, SAM 3, Classification Label Visualization, Instance Segmentation Model, Camera Focus, Image Blur, Corner Visualization, Anthropic Claude, Gaze Detection, OCR Model, LMM For Classification, Object Detection Model, Mask Visualization, Anthropic Claude, Stability AI Outpainting, Contrast Equalization, SAM 3, Absolute Static Crop, SAM 3, Qwen2.5-VL, Clip Comparison, VLM as Detector, Background Subtraction, Detections Stitch, Instance Segmentation Model, SmolVLM2, Depth Estimation, Google Gemini, Segment Anything 2 Model, Stitch Images, Keypoint Detection Model, Template Matching, Stability AI Image Generation, YOLO-World Model, Florence-2 Model, Triangle Visualization, Label Visualization, LMM, Camera Focus, SIFT Comparison, Text Display, Clip Comparison, Keypoint Visualization, Dot Visualization, Pixel Color Count, CogVLM, Perspective Correction, Image Convert Grayscale, VLM as Classifier, Color Visualization, Background Color Visualization, Image Contours, Motion Detection, Object Detection Model, Image Preprocessing, Roboflow Dataset Upload, Anthropic Claude, Bounding Box Visualization, Google Gemini, Morphological Transformation, OpenAI, Llama 3.2 Vision, Multi-Label Classification Model, Single-Label Classification Model

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[instance_segmentation_prediction, keypoint_detection_prediction, object_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
}