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

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
    ]
}