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

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
}