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

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
}