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

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[list_of_values, object_detection_prediction, instance_segmentation_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
    ]
}