Reference Path Visualization

Class: ReferencePathVisualizationBlockV1

Source: inference.core.workflows.core_steps.visualizations.reference_path.v1.ReferencePathVisualizationBlockV1

The Reference Path Visualization block draws reference path in the image. To be used in combination with Path deviation block - to display the reference path.

Type identifier

Use the following identifier in step "type" field: roboflow_core/reference_path_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..	✅
reference_path	List[Any]	Reference path in a format [(x1, y1), (x2, y2), (x3, y3), ...].	✅
color	str	Color of the zone..	✅
thickness	int	Thickness of the lines in pixels..	✅

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 Reference Path Visualization in version v1.

• inputs: Size Measurement, Roboflow Custom Metadata, LMM, Buffer, Image Convert Grayscale, VLM as Detector, Absolute Static Crop, Multi-Label Classification Model, Distance Measurement, Relative Static Crop, Line Counter Visualization, Background Color Visualization, OCR Model, Camera Focus, Image Contours, Image Slicer, Reference Path Visualization, Keypoint Detection Model, Instance Segmentation Model, SIFT Comparison, Object Detection Model, Triangle Visualization, Line Counter, Depth Estimation, Llama 3.2 Vision, Roboflow Dataset Upload, Dynamic Zone, Google Vision OCR, Clip Comparison, Perspective Correction, Crop Visualization, Webhook Sink, Identify Changes, Dot Visualization, Model Comparison Visualization, Email Notification, Classification Label Visualization, Camera Calibration, Dimension Collapse, Slack Notification, Stability AI Image Generation, Trace Visualization, Line Counter, Corner Visualization, Image Threshold, Blur Visualization, Local File Sink, CogVLM, Stability AI Inpainting, SIFT, Circle Visualization, JSON Parser, OpenAI, Florence-2 Model, Twilio SMS Notification, Label Visualization, Stitch Images, Image Preprocessing, Template Matching, Grid Visualization, Polygon Zone Visualization, Keypoint Visualization, LMM For Classification, Stitch OCR Detections, Bounding Box Visualization, Image Blur, OpenAI, Halo Visualization, Google Gemini, Ellipse Visualization, Color Visualization, Pixelate Visualization, SIFT Comparison, Pixel Color Count, VLM as Detector, Roboflow Dataset Upload, Polygon Visualization, Single-Label Classification Model, VLM as Classifier, CSV Formatter, Image Slicer, Model Monitoring Inference Aggregator, Clip Comparison, Mask Visualization, VLM as Classifier, Identify Outliers, Anthropic Claude, Florence-2 Model, Dynamic Crop, Detections Consensus
• outputs: LMM, Buffer, Image Convert Grayscale, VLM as Detector, Absolute Static Crop, Multi-Label Classification Model, Relative Static Crop, Line Counter Visualization, Gaze Detection, Background Color Visualization, OCR Model, Camera Focus, Image Contours, Image Slicer, Reference Path Visualization, Keypoint Detection Model, Instance Segmentation Model, SIFT Comparison, Object Detection Model, Triangle Visualization, Detections Stabilizer, Multi-Label Classification Model, Depth Estimation, Google Vision OCR, Llama 3.2 Vision, Roboflow Dataset Upload, Clip Comparison, Perspective Correction, Object Detection Model, Crop Visualization, Dot Visualization, Model Comparison Visualization, Instance Segmentation Model, Classification Label Visualization, Camera Calibration, Qwen2.5-VL, Stability AI Image Generation, Trace Visualization, Time in Zone, Corner Visualization, Image Threshold, Blur Visualization, QR Code Detection, CogVLM, Stability AI Inpainting, Keypoint Detection Model, SIFT, Circle Visualization, OpenAI, Moondream2, Florence-2 Model, Label Visualization, Stitch Images, Image Preprocessing, Detections Stitch, Template Matching, Byte Tracker, SmolVLM2, Dominant Color, Polygon Zone Visualization, Keypoint Visualization, LMM For Classification, Bounding Box Visualization, CLIP Embedding Model, OpenAI, Halo Visualization, Google Gemini, Ellipse Visualization, Image Blur, Color Visualization, Barcode Detection, Pixelate Visualization, Single-Label Classification Model, Pixel Color Count, YOLO-World Model, VLM as Detector, Roboflow Dataset Upload, Segment Anything 2 Model, Polygon Visualization, Single-Label Classification Model, VLM as Classifier, Image Slicer, Clip Comparison, Mask Visualization, VLM as Classifier, Anthropic Claude, Florence-2 Model, Dynamic Crop

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Reference Path 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..
  • reference_path (list_of_values): Reference path in a format [(x1, y1), (x2, y2), (x3, y3), ...].
  • color (string): Color of the zone..
  • thickness (integer): Thickness of the lines in pixels..

• output

  • image (image): Image in workflows.

Example JSON definition of step Reference Path Visualization in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/reference_path_visualization@v1",
    "image": "$inputs.image",
    "copy_image": true,
    "reference_path": "$inputs.expected_path",
    "color": "WHITE",
    "thickness": 2
}