Triangle Visualization
Draw triangle markers on an image at specific coordinates based on provided detections.
Draw triangular markers on an image to mark specific points on detected objects, with customizable position, size, color, and outline styling, providing directional indicators and geometric markers for visual annotations.
How This Block Works
This block takes an image and detection predictions and draws triangular markers at specified anchor positions on each detected object. The block:
Takes an image and predictions as input
Determines the triangle position for each detection based on the selected anchor point (center, corners, edges, or center of mass)
Applies color styling based on the selected color palette, with colors assigned by class, index, or track ID
Draws triangular markers with the specified base width and height dimensions, with optional outline thickness using Supervision's TriangleAnnotator
Returns an annotated image with triangular markers overlaid on the original image
The block supports various position options including the center of the bounding box, any of the four corners, edge midpoints, or the center of mass (useful for objects with irregular shapes). Triangles can be customized with different sizes (base width and height), optional outlines for better visibility, and various color palettes. Triangular markers provide a distinctive geometric shape that can serve as directional indicators (pointing in a specific direction) or geometric markers, offering an alternative to circular dots or square markers. This provides a clean visualization style that marks detection locations with directional or geometric emphasis, making it ideal for applications requiring directional indicators, geometric markers, or distinctive point markers.
Common Use Cases
Directional Object Marking: Mark detected objects with triangular markers that can indicate direction or orientation, useful for tracking applications, motion analysis, or directional workflows where the triangle's pointed shape provides directional information
Geometric Marker Visualization: Use triangular markers as distinctive geometric shapes to mark detection locations, providing visual variety compared to circular dots or rectangular bounding boxes for design purposes or geometric emphasis
Minimal Object Marking: Mark detected objects with small triangular markers instead of bounding boxes for cleaner, less cluttered visualizations when working with dense scenes or many detections, with the triangular shape providing visual distinction
Tracking Visualization: Use triangular markers to visualize object trajectories or tracking IDs over time, creating a cleaner alternative to bounding boxes for tracking workflows, with triangles potentially indicating movement direction
Point of Interest Highlighting: Mark specific anchor points (corners, center, center of mass) on detected objects with triangular markers for applications like object tracking, spatial analysis, or geometric annotation workflows
Design and Aesthetic Applications: Create triangular markers for design purposes, user interfaces, dashboards, or artistic visualizations where geometric shapes provide distinctive visual style or aesthetic appeal
Connecting to Other Blocks
The annotated image from this block can be connected to:
Other visualization blocks (e.g., Bounding Box Visualization, Label Visualization, Trace Visualization) to combine triangular markers with additional annotations for comprehensive visualization
Data storage blocks (e.g., Local File Sink, CSV Formatter, Roboflow Dataset Upload) to save annotated images with triangular markers for documentation, reporting, or analysis
Webhook blocks to send visualized results with triangular markers 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 triangular markers as visual evidence in alerts or reports
Video output blocks to create annotated video streams or recordings with triangular markers for live monitoring, tracking visualization, or post-processing analysis
Type identifier
Use the following identifier in step "type" field: roboflow_core/triangle_visualization@v1 to add the block as a 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..
✅
position
str
Anchor position for placing the triangle marker relative to the detection's bounding box. Options include: CENTER (center of box), corners (TOP_LEFT, TOP_RIGHT, BOTTOM_LEFT, BOTTOM_RIGHT), edge midpoints (TOP_CENTER, CENTER_LEFT, CENTER_RIGHT, BOTTOM_CENTER), or CENTER_OF_MASS (center of mass of the object, useful for irregular shapes)..
✅
base
int
Base width of the triangle in pixels. Controls the horizontal width of the triangular marker at its base. Larger values create wider triangles, while smaller values create narrower triangles. Works together with height to control the overall triangle size and shape..
✅
height
int
Height of the triangle in pixels. Controls the vertical height of the triangular marker from base to tip. Larger values create taller triangles, while smaller values create shorter triangles. Works together with base to control the overall triangle size and shape..
✅
outline_thickness
int
Thickness of the triangle outline in pixels. A value of 0 creates a filled triangle with no outline. Higher values create thicker outlines around the triangle border, improving visibility and contrast. Useful for making triangular markers more visible against complex backgrounds..
✅
The Refs column marks possibility to parametrise the property with dynamic values available in workflow runtime. See Bindings for more info.
Input and Output Bindings
The available connections depend on its binding kinds. Check what binding kinds Triangle Visualization in version v1 has.
Input and output 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..position(string): Anchor position for placing the triangle marker relative to the detection's bounding box. Options include: CENTER (center of box), corners (TOP_LEFT, TOP_RIGHT, BOTTOM_LEFT, BOTTOM_RIGHT), edge midpoints (TOP_CENTER, CENTER_LEFT, CENTER_RIGHT, BOTTOM_CENTER), or CENTER_OF_MASS (center of mass of the object, useful for irregular shapes)..base(integer): Base width of the triangle in pixels. Controls the horizontal width of the triangular marker at its base. Larger values create wider triangles, while smaller values create narrower triangles. Works together with height to control the overall triangle size and shape..height(integer): Height of the triangle in pixels. Controls the vertical height of the triangular marker from base to tip. Larger values create taller triangles, while smaller values create shorter triangles. Works together with base to control the overall triangle size and shape..outline_thickness(integer): Thickness of the triangle outline in pixels. A value of 0 creates a filled triangle with no outline. Higher values create thicker outlines around the triangle border, improving visibility and contrast. Useful for making triangular markers more visible against complex backgrounds..
output
image(image): Image in workflows.
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