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