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

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[list_of_values, instance_segmentation_prediction, object_detection_prediction]): 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_of_values, string]): 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
    ]
}