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

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[object_detection_prediction, instance_segmentation_prediction]): Model predictions to measure the dimensions of..
  • reference_predictions (Union[object_detection_prediction, instance_segmentation_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[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
    ]
}