Distance Measurement

Class: DistanceMeasurementBlockV1

Source: inference.core.workflows.core_steps.classical_cv.distance_measurement.v1.DistanceMeasurementBlockV1

Calculate the distance between two bounding boxes on a 2D plane, leveraging a perpendicular camera view and either a reference object or a pixel-to-unit scaling ratio for precise measurements.

Type identifier

Use the following identifier in step "type" field: roboflow_core/distance_measurement@v1to add the block as as step in your workflow.

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
object_1_class_name	str	The class name of the first object..	❌
object_2_class_name	str	The class name of the second object..	❌
reference_axis	str	The axis along which the distance will be measured..	❌
calibration_method	str	Select how to calibrate the measurement of distance between objects..	❌
reference_object_class_name	str	The class name of the reference object..	✅
reference_width	float	Width of the reference object in centimeters.	✅
reference_height	float	Height of the reference object in centimeters.	✅
pixel_ratio	float	The pixel-to-centimeter ratio of the input image, i.e. 1 centimeter = 100 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 Distance Measurement in version v1.

• inputs: Segment Anything 2 Model, Instance Segmentation Model, Model Monitoring Inference Aggregator, Keypoint Detection Model, Byte Tracker, VLM as Classifier, Camera Focus, Perspective Correction, VLM as Detector, Google Vision OCR, Detections Stitch, Detections Stabilizer, YOLO-World Model, Multi-Label Classification Model, VLM as Detector, Dynamic Zone, Object Detection Model, OpenAI, CogVLM, Detections Transformation, Email Notification, Time in Zone, Moondream2, Dynamic Crop, Slack Notification, Detections Classes Replacement, Byte Tracker, Twilio SMS Notification, Byte Tracker, Detection Offset, Roboflow Custom Metadata, Template Matching, Time in Zone, Clip Comparison, Detections Consensus, LMM, LMM For Classification, Single-Label Classification Model, Overlap Filter, Instance Segmentation Model, Florence-2 Model, Roboflow Dataset Upload, Google Gemini, Webhook Sink, Stitch OCR Detections, Detections Merge, Velocity, Local File Sink, Bounding Rectangle, Gaze Detection, Roboflow Dataset Upload, Anthropic Claude, Detections Filter, Florence-2 Model, OpenAI, Path Deviation, Path Deviation, Llama 3.2 Vision, Identify Changes, Object Detection Model, OCR Model, Line Counter, CSV Formatter, Cosine Similarity
• outputs: SIFT Comparison, Keypoint Detection Model, Byte Tracker, Image Threshold, Polygon Visualization, Dynamic Zone, Pixelate Visualization, Identify Outliers, Circle Visualization, Dot Visualization, Slack Notification, Absolute Static Crop, Byte Tracker, Keypoint Visualization, Byte Tracker, Detection Offset, Detections Consensus, Label Visualization, Image Slicer, Keypoint Detection Model, Triangle Visualization, Anthropic Claude, Corner Visualization, Image Contours, Instance Segmentation Model, Perspective Correction, Detections Stabilizer, Line Counter Visualization, Object Detection Model, Email Notification, Color Visualization, Image Slicer, Mask Visualization, Twilio SMS Notification, Crop Visualization, Grid Visualization, Pixel Color Count, Stitch Images, Instance Segmentation Model, Bounding Box Visualization, Webhook Sink, Stitch OCR Detections, Ellipse Visualization, Dominant Color, Image Blur, Reference Path Visualization, SIFT Comparison, Image Preprocessing, Classification Label Visualization, Blur Visualization, Identify Changes, Object Detection Model, Trace Visualization, Halo Visualization

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Distance Measurement in version v1 has.

Bindings

• input

  • predictions (Union[object_detection_prediction, instance_segmentation_prediction]): The output of a detection model describing the bounding boxes that will be used to measure the objects..
  • reference_object_class_name (string): The class name of the reference object..
  • reference_width (float): Width of the reference object in centimeters.
  • reference_height (float): Height of the reference object in centimeters.
  • pixel_ratio (float): The pixel-to-centimeter ratio of the input image, i.e. 1 centimeter = 100 pixels..

• output

  • distance_cm (integer): Integer value.
  • distance_pixel (integer): Integer value.

Example JSON definition of step Distance Measurement in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/distance_measurement@v1",
    "predictions": "$steps.model.predictions",
    "object_1_class_name": "car",
    "object_2_class_name": "person",
    "reference_axis": "vertical",
    "calibration_method": "<block_does_not_provide_example>",
    "reference_object_class_name": "reference-object",
    "reference_width": 2.5,
    "reference_height": 2.5,
    "pixel_ratio": 100
}