Reference Path Visualization¶
Class: 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@v1
to 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:
Anthropic Claude
,Crop Visualization
,SIFT
,Stitch OCR Detections
,Line Counter
,Line Counter
,LMM For Classification
,Blur Visualization
,PTZ Tracking (ONVIF)
.md),Line Counter Visualization
,Color Visualization
,Image Contours
,Camera Focus
,Mask Visualization
,Image Convert Grayscale
,Circle Visualization
,Google Gemini
,Absolute Static Crop
,VLM as Classifier
,Object Detection Model
,Dynamic Zone
,Detections Consensus
,Stitch Images
,Trace Visualization
,Image Preprocessing
,Roboflow Custom Metadata
,OCR Model
,JSON Parser
,Clip Comparison
,Polygon Zone Visualization
,LMM
,QR Code Generator
,Size Measurement
,Halo Visualization
,Perspective Correction
,Florence-2 Model
,Stability AI Inpainting
,Buffer
,Template Matching
,Webhook Sink
,Label Visualization
,Distance Measurement
,VLM as Detector
,Pixel Color Count
,Stability AI Image Generation
,Triangle Visualization
,Keypoint Detection Model
,Background Color Visualization
,Relative Static Crop
,Slack Notification
,Corner Visualization
,Multi-Label Classification Model
,Icon Visualization
,SIFT Comparison
,Pixelate Visualization
,Image Blur
,Model Comparison Visualization
,VLM as Detector
,Llama 3.2 Vision
,Instance Segmentation Model
,CSV Formatter
,Image Threshold
,VLM as Classifier
,Reference Path Visualization
,Google Vision OCR
,Image Slicer
,Roboflow Dataset Upload
,CogVLM
,Identify Outliers
,Depth Estimation
,Roboflow Dataset Upload
,Single-Label Classification Model
,OpenAI
,Classification Label Visualization
,Polygon Visualization
,Stability AI Outpainting
,Keypoint Visualization
,Dot Visualization
,Email Notification
,Grid Visualization
,Local File Sink
,OpenAI
,Bounding Box Visualization
,Camera Calibration
,Ellipse Visualization
,OpenAI
,Florence-2 Model
,Model Monitoring Inference Aggregator
,Image Slicer
,Twilio SMS Notification
,SIFT Comparison
,Dimension Collapse
,Identify Changes
,Clip Comparison
,Dynamic Crop
- outputs:
QR Code Detection
,Anthropic Claude
,Crop Visualization
,SIFT
,LMM For Classification
,Blur Visualization
,Line Counter Visualization
,Color Visualization
,Image Contours
,Camera Focus
,Mask Visualization
,Image Convert Grayscale
,Google Gemini
,Circle Visualization
,Absolute Static Crop
,VLM as Classifier
,Object Detection Model
,Multi-Label Classification Model
,Keypoint Detection Model
,Stitch Images
,Trace Visualization
,Image Preprocessing
,Qwen2.5-VL
,OCR Model
,Object Detection Model
,Clip Comparison
,SmolVLM2
,Polygon Zone Visualization
,LMM
,YOLO-World Model
,Halo Visualization
,CLIP Embedding Model
,Florence-2 Model
,Moondream2
,Perspective Correction
,Stability AI Inpainting
,Buffer
,Template Matching
,Label Visualization
,VLM as Detector
,Pixel Color Count
,Segment Anything 2 Model
,Perception Encoder Embedding Model
,Stability AI Image Generation
,Keypoint Detection Model
,Triangle Visualization
,Background Color Visualization
,Relative Static Crop
,Detections Stabilizer
,Corner Visualization
,Multi-Label Classification Model
,Icon Visualization
,Pixelate Visualization
,Image Blur
,Gaze Detection
,Model Comparison Visualization
,VLM as Detector
,Llama 3.2 Vision
,Time in Zone
,Instance Segmentation Model
,Image Threshold
,VLM as Classifier
,Google Vision OCR
,Reference Path Visualization
,Image Slicer
,Roboflow Dataset Upload
,CogVLM
,Byte Tracker
,Barcode Detection
,Depth Estimation
,Roboflow Dataset Upload
,Single-Label Classification Model
,OpenAI
,Classification Label Visualization
,Polygon Visualization
,Stability AI Outpainting
,Keypoint Visualization
,Dot Visualization
,OpenAI
,Single-Label Classification Model
,Bounding Box Visualization
,Camera Calibration
,Ellipse Visualization
,OpenAI
,Florence-2 Model
,Image Slicer
,Instance Segmentation Model
,SIFT Comparison
,Detections Stitch
,Dominant Color
,Clip Comparison
,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
}