Line Counter Visualization¶
Class: LineCounterZoneVisualizationBlockV1
Source: inference.core.workflows.core_steps.visualizations.line_zone.v1.LineCounterZoneVisualizationBlockV1
The LineCounterZoneVisualization
block draws line
in an image with a specified color and opacity.
Please note: line zone will be drawn on top of image passed to this block,
this block should be placed before other visualization blocks in the workflow.
Type identifier¶
Use the following identifier in step "type"
field: roboflow_core/line_counter_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.. | ✅ |
zone |
List[Any] |
Line in the format [[x1, y1], [x2, y2]] consisting of exactly two points.. | ✅ |
color |
str |
Color of the zone.. | ✅ |
thickness |
int |
Thickness of the lines in pixels.. | ✅ |
text_thickness |
int |
Thickness of the text in pixels.. | ✅ |
text_scale |
float |
Scale of the text.. | ✅ |
count_in |
int |
Reference to the number of objects that crossed into the line zone.. | ✅ |
count_out |
int |
Reference to the number of objects that crossed out of the line zone.. | ✅ |
opacity |
float |
Transparency of the Mask overlay.. | ✅ |
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 Line Counter 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
,Cosine Similarity
,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
,Gaze Detection
,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
Line Counter 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..zone
(list_of_values
): Line in the format [[x1, y1], [x2, y2]] consisting of exactly two points..color
(string
): Color of the zone..thickness
(integer
): Thickness of the lines in pixels..text_thickness
(integer
): Thickness of the text in pixels..text_scale
(float
): Scale of the text..count_in
(integer
): Reference to the number of objects that crossed into the line zone..count_out
(integer
): Reference to the number of objects that crossed out of the line zone..opacity
(float_zero_to_one
): Transparency of the Mask overlay..
-
output
image
(image
): Image in workflows.
Example JSON definition of step Line Counter Visualization
in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/line_counter_visualization@v1",
"image": "$inputs.image",
"copy_image": true,
"zone": [
[
0,
50
],
[
500,
50
]
],
"color": "WHITE",
"thickness": 2,
"text_thickness": 1,
"text_scale": 1.0,
"count_in": "$steps.line_counter.count_in",
"count_out": "$steps.line_counter.count_out",
"opacity": 0.3
}