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

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
}