Size Measurement

Class: SizeMeasurementBlockV1

Source: inference.core.workflows.core_steps.classical_cv.size_measurement.v1.SizeMeasurementBlockV1

The Size Measurement Block calculates the dimensions of objects relative to a reference object. It uses one model to detect the reference object and another to detect the objects to measure. The block outputs the dimensions of the objects in terms of the reference object.

• Reference Object: This is the known object used as a baseline for measurements. Its dimensions are known and used to scale the measurements of other objects.
• Object to Measure: This is the object whose dimensions are being calculated. The block measures these dimensions relative to the reference object.

Block Usage

To use the Size Measurement Block, follow these steps:

1. Select Models: Choose a model to detect the reference object and another model to detect the objects you want to measure.
2. Configure Inputs: Provide the predictions from both models as inputs to the block.
3. Set Reference Dimensions: Specify the known dimensions of the reference object in the format 'width,height' or as a tuple (width, height).
4. Run the Block: Execute the block to calculate the dimensions of the detected objects relative to the reference object.

Example

Imagine you have a scene with a calibration card and several packages. The calibration card has known dimensions of 5.0 inches by 3.0 inches. You want to measure the dimensions of packages in the scene.

• Reference Object: Calibration card with dimensions 5.0 inches (width) by 3.0 inches (height).
• Objects to Measure: Packages detected in the scene.

The block will use the known dimensions of the calibration card to calculate the dimensions of each package. For example, if a package is detected with a width of 100 pixels and a height of 60 pixels, and the calibration card is detected with a width of 50 pixels and a height of 30 pixels, the block will calculate the package's dimensions as:

• Width: (100 pixels / 50 pixels) * 5.0 inches = 10.0 inches
• Height: (60 pixels / 30 pixels) * 3.0 inches = 6.0 inches

This allows you to obtain the real-world dimensions of the packages based on the reference object's known size.

Watch the video tutorial

Type identifier

Use the following identifier in step "type" field: roboflow_core/size_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..	❌
reference_predictions	List[Any]	Reference object used to calculate the dimensions of the specified objects. If multiple objects are provided, the highest confidence prediction will be used..	✅
reference_dimensions	Union[List[float], Tuple[float, float], str]	Dimensions of the reference object in desired units, (e.g. inches). Will be used to convert the pixel dimensions of the other objects to real-world units..	✅

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 Size Measurement in version v1.

• inputs: LMM, Size Measurement, Dynamic Zone, Detections Transformation, Model Monitoring Inference Aggregator, Detections Classes Replacement, Object Detection Model, Line Counter, Local File Sink, Email Notification, Time in Zone, Anthropic Claude, Google Gemini, Florence-2 Model, Multi-Label Classification Model, Segment Anything 2 Model, OCR Model, Byte Tracker, Time in Zone, Roboflow Custom Metadata, Florence-2 Model, LMM For Classification, Overlap Filter, Detection Offset, Perspective Correction, Google Vision OCR, EasyOCR, Llama 3.2 Vision, Detections Stabilizer, SAM 3, Slack Notification, Velocity, Clip Comparison, Stitch OCR Detections, Byte Tracker, OpenAI, Roboflow Dataset Upload, Path Deviation, Template Matching, CogVLM, Email Notification, VLM as Detector, Instance Segmentation Model, Byte Tracker, OpenAI, Clip Comparison, Detections Stitch, Keypoint Detection Model, Object Detection Model, YOLO-World Model, Detections Merge, Moondream2, Seg Preview, Path Deviation, Dimension Collapse, Roboflow Dataset Upload, Buffer, Instance Segmentation Model, Detections Filter, OpenAI, VLM as Classifier, Bounding Rectangle, CSV Formatter, Time in Zone, Detections Combine, Twilio SMS Notification, VLM as Detector, Webhook Sink, Detections Consensus, Single-Label Classification Model, PTZ Tracking (ONVIF).md), Dynamic Crop
• outputs: Polygon Visualization, OpenAI, Grid Visualization, Roboflow Dataset Upload, Size Measurement, Path Deviation, VLM as Classifier, Corner Visualization, Trace Visualization, Classification Label Visualization, Email Notification, VLM as Detector, Object Detection Model, Instance Segmentation Model, Line Counter, Bounding Box Visualization, Mask Visualization, Email Notification, Keypoint Detection Model, Polygon Zone Visualization, Anthropic Claude, Time in Zone, Google Gemini, Clip Comparison, Florence-2 Model, Keypoint Detection Model, Crop Visualization, Object Detection Model, Ellipse Visualization, Triangle Visualization, YOLO-World Model, Seg Preview, Color Visualization, Roboflow Dataset Upload, Path Deviation, Label Visualization, Time in Zone, Keypoint Visualization, Cache Set, Florence-2 Model, Buffer, LMM For Classification, Instance Segmentation Model, Dot Visualization, Circle Visualization, OpenAI, VLM as Classifier, Line Counter, Llama 3.2 Vision, Time in Zone, Reference Path Visualization, SAM 3, VLM as Detector, Webhook Sink, Detections Consensus, Clip Comparison, Line Counter Visualization, Halo Visualization, Perspective Correction

Input and Output Bindings

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

Bindings

• input

  • object_predictions (Union[instance_segmentation_prediction, object_detection_prediction]): Model predictions to measure the dimensions of..
  • reference_predictions (Union[instance_segmentation_prediction, object_detection_prediction, list_of_values]): Reference object used to calculate the dimensions of the specified objects. If multiple objects are provided, the highest confidence prediction will be used..
  • reference_dimensions (Union[string, list_of_values]): Dimensions of the reference object in desired units, (e.g. inches). Will be used to convert the pixel dimensions of the other objects to real-world units..

• output

  • dimensions (list_of_values): List of values of any type.

Example JSON definition of step Size Measurement in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/size_measurement@v1",
    "object_predictions": "$segmentation.object_predictions",
    "reference_predictions": "$segmentation.reference_predictions",
    "reference_dimensions": [
        4.5,
        3.0
    ]
}