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

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[rle_instance_segmentation_prediction, keypoint_detection_prediction, object_detection_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
}