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: Google Vision OCR, Label Visualization, LMM For Classification, Blur Visualization, Background Color Visualization, Contrast Equalization, Bounding Box Visualization, Keypoint Visualization, Stability AI Outpainting, Reference Path Visualization, Image Slicer, Pixelate Visualization, Single-Label Classification Model, Clip Comparison, CSV Formatter, Image Preprocessing, Color Visualization, SIFT Comparison, Object Detection Model, Email Notification, Anthropic Claude, Circle Visualization, Image Contours, Polygon Zone Visualization, Ellipse Visualization, Line Counter, Email Notification, Clip Comparison, VLM as Classifier, Model Monitoring Inference Aggregator, OCR Model, Absolute Static Crop, Depth Estimation, LMM, Morphological Transformation, Roboflow Dataset Upload, Gaze Detection, Detections Consensus, Crop Visualization, OpenAI, Image Convert Grayscale, VLM as Detector, Roboflow Custom Metadata, Florence-2 Model, CogVLM, Classification Label Visualization, Buffer, Stitch OCR Detections, Keypoint Detection Model, Cosine Similarity, SIFT Comparison, Line Counter, JSON Parser, Camera Calibration, Polygon Visualization, PTZ Tracking (ONVIF).md), Icon Visualization, Identify Changes, Triangle Visualization, Template Matching, Roboflow Dataset Upload, Anthropic Claude, Model Comparison Visualization, Corner Visualization, Florence-2 Model, Distance Measurement, Google Gemini, Google Gemini, EasyOCR, VLM as Detector, Line Counter Visualization, Grid Visualization, Halo Visualization, Size Measurement, Stability AI Image Generation, Identify Outliers, QR Code Generator, Dynamic Zone, Twilio SMS Notification, Relative Static Crop, Dot Visualization, Llama 3.2 Vision, Image Blur, Slack Notification, Dimension Collapse, Local File Sink, OpenAI, Multi-Label Classification Model, Image Slicer, OpenAI, Stability AI Inpainting, Dynamic Crop, Camera Focus, Pixel Color Count, Webhook Sink, Image Threshold, VLM as Classifier, Perspective Correction, Mask Visualization, Trace Visualization, OpenAI, Instance Segmentation Model, Stitch Images, SIFT
• outputs: Google Vision OCR, Label Visualization, LMM For Classification, Blur Visualization, Background Color Visualization, Contrast Equalization, Reference Path Visualization, Keypoint Visualization, Stability AI Outpainting, Bounding Box Visualization, Image Slicer, Pixelate Visualization, Single-Label Classification Model, Clip Comparison, SAM 3, Perception Encoder Embedding Model, Seg Preview, Byte Tracker, Image Preprocessing, SAM 3, Color Visualization, SIFT Comparison, Qwen2.5-VL, Object Detection Model, Dominant Color, Anthropic Claude, Circle Visualization, Image Contours, Object Detection Model, QR Code Detection, Polygon Zone Visualization, Ellipse Visualization, Email Notification, Clip Comparison, Moondream2, VLM as Classifier, OCR Model, Absolute Static Crop, Depth Estimation, LMM, Time in Zone, Morphological Transformation, Roboflow Dataset Upload, Gaze Detection, Crop Visualization, OpenAI, Florence-2 Model, Barcode Detection, Image Convert Grayscale, SAM 3, CogVLM, VLM as Detector, Multi-Label Classification Model, Classification Label Visualization, Buffer, Keypoint Detection Model, Segment Anything 2 Model, Keypoint Detection Model, YOLO-World Model, Polygon Visualization, CLIP Embedding Model, Camera Calibration, Icon Visualization, Triangle Visualization, Template Matching, Roboflow Dataset Upload, Anthropic Claude, Model Comparison Visualization, Corner Visualization, Florence-2 Model, Google Gemini, Google Gemini, EasyOCR, VLM as Detector, Line Counter Visualization, SmolVLM2, Halo Visualization, Stability AI Image Generation, Relative Static Crop, Dot Visualization, Detections Stitch, Llama 3.2 Vision, Image Blur, OpenAI, Instance Segmentation Model, Multi-Label Classification Model, Image Slicer, OpenAI, Stability AI Inpainting, Dynamic Crop, Single-Label Classification Model, Camera Focus, Pixel Color Count, Detections Stabilizer, Instance Segmentation Model, VLM as Classifier, Mask Visualization, Perspective Correction, Image Threshold, OpenAI, Trace Visualization, Stitch Images, SIFT

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
}