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