Property Definition¶
Class: PropertyDefinitionBlockV1
Source: inference.core.workflows.core_steps.formatters.property_definition.v1.PropertyDefinitionBlockV1
Extract specific properties or fields from workflow step outputs using configurable operation chains to extract class names, confidences, counts, coordinates, OCR text, metadata, and other properties from model predictions or workflow data for data transformation, property extraction, metadata access, and value extraction workflows.
How This Block Works¶
This block extracts specific properties from data by applying a chain of operations that navigate and extract values from complex data structures. The block:
- Receives input data from any workflow step (detections, classifications, OCR results, images, or other data types)
- Applies a chain of operations defined in the operations parameter:
- Each operation performs a specific extraction or transformation task
- Operations are executed sequentially, with each operation working on the result of the previous one
- Operations can extract properties, filter data, transform formats, or combine values
- Extracts properties based on operation type:
For Detection Properties: - Extracts properties from object detection, instance segmentation, or keypoint detection predictions - Can extract: class names, confidences, counts, bounding box coordinates (x_min, y_min, x_max, y_max), centers, sizes, tracker IDs, velocities, speeds, path deviations, time in zone, polygons, and more - Returns lists of values (one per detection) or aggregated values
For Classification Properties: - Extracts properties from classification predictions - Can extract: predicted class, confidence scores, all classes, all confidences - Returns single values or lists depending on the property
For OCR Properties: - Extracts text, coordinates, and metadata from OCR results - Can extract: recognized text, bounding box information, confidence scores
For Image Properties: - Extracts metadata and properties from images - Can extract: dimensions, format information, and other image metadata
- Supports compound operations for complex extractions:
- Operations can be chained to perform multi-step extractions
- Can filter detections before extracting properties
- Can select specific detections, transform formats, or combine multiple properties
- Returns the extracted property value:
- Output type depends on the property extracted (list, string, number, dictionary, etc.)
- Returns a single output value containing the extracted property
The block uses a flexible operation system that allows extracting virtually any property from workflow data. Operations can be simple (extract a single property) or compound (filter, transform, then extract). This makes the block highly versatile for accessing specific fields from complex data structures without needing custom code.
Common Use Cases¶
- Property Extraction: Extract specific fields from model predictions (e.g., extract class names from detections, get confidence scores, extract OCR text, get detection counts), enabling property extraction workflows
- Metadata Access: Access metadata and computed properties from workflow steps (e.g., extract tracker IDs, get velocity values, access time in zone, retrieve path deviations), enabling metadata access workflows
- Data Transformation: Transform complex data structures into simpler values for downstream use (e.g., convert detections to lists, extract coordinates, get bounding box centers, extract class lists), enabling data transformation workflows
- Conditional Logic: Extract values for use in conditional logic or decision making (e.g., extract counts for thresholds, get confidences for filtering, extract class names for classification, get coordinates for calculations), enabling conditional logic workflows
- Data Formatting: Format data for storage, display, or API responses (e.g., extract values for JSON output, format data for storage, prepare data for visualization, extract for API responses), enabling data formatting workflows
- Analytics Extraction: Extract metrics and measurements for analysis (e.g., extract detection counts, get confidence statistics, extract measurement values, retrieve analytics metrics), enabling analytics extraction workflows
Connecting to Other Blocks¶
This block receives data from any workflow step and produces extracted property values:
- After model blocks (detection, classification, OCR, etc.) to extract properties from predictions (e.g., extract class names from detections, get classification results, extract OCR text), enabling model-to-property workflows
- After analytics blocks to extract computed metrics and measurements (e.g., extract velocity values, get time in zone, retrieve path deviations, access tracking information), enabling analytics-to-property workflows
- Before logic blocks like Continue If to use extracted values in conditions (e.g., continue if count exceeds threshold, filter based on extracted confidence, make decisions using extracted values), enabling property-based decision workflows
- Before data storage blocks to format extracted values for storage (e.g., store extracted properties, format values for logging, prepare data for storage), enabling property-to-storage workflows
- Before visualization blocks to provide extracted values for display (e.g., display extracted counts, show extracted text, visualize extracted metrics), enabling property visualization workflows
- Before notification blocks to use extracted values in notifications (e.g., include extracted counts in alerts, send extracted text in messages, use extracted values in notifications), enabling property-based notification workflows
Requirements¶
This block works with any data type from workflow steps. The operations parameter defines a list of operations to perform on the input data. Each operation must be compatible with the data type and previous operation outputs. Common operations include DetectionsPropertyExtract (for detection properties), ClassificationPropertyExtract (for classification properties), and other extraction operations. The block supports compound operations (operations that can contain other operations) for complex extractions. The output type depends on the operations performed and the properties extracted - it can be a list, string, number, dictionary, or other types depending on what is extracted.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/property_definition@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
operations |
List[Union[ClassificationPropertyExtract, ConvertDictionaryToJSON, ConvertImageToBase64, ConvertImageToJPEG, DetectionsFilter, DetectionsOffset, DetectionsPropertyExtract, DetectionsRename, DetectionsSelection, DetectionsShift, DetectionsToDictionary, Divide, ExtractDetectionProperty, ExtractFrameMetadata, ExtractImageProperty, LookupTable, Multiply, NumberRound, NumericSequenceAggregate, PickDetectionsByParentClass, RandomNumber, SequenceAggregate, SequenceApply, SequenceElementsCount, SequenceLength, SequenceMap, SortDetections, StringMatches, StringSubSequence, StringToLowerCase, StringToUpperCase, TimestampToISOFormat, ToBoolean, ToNumber, ToString]] |
List of operations to perform sequentially on the input data. Each operation performs extraction, filtering, transformation, or combination. Operations execute in order, with each operation working on the previous result. Common operations: DetectionsPropertyExtract (extract properties like class_name, confidence, count, coordinates from detections), ClassificationPropertyExtract (extract class, confidence from classifications), DetectionsFilter (filter detections before extraction), DetectionsSelection (select specific detections). Can include single or compound operations for complex extractions.. | ❌ |
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 Property Definition in version v1.
- inputs:
VLM As Classifier,Line Counter,MoonshotAI Kimi,Stability AI Image Generation,Path Deviation,Trace Visualization,Qwen2.5-VL,Image Stack,Anthropic Claude,Per-Class Confidence Filter,Icon Visualization,SIFT Comparison,Morphological Transformation,Color Visualization,SmolVLM2,LMM For Classification,Single-Label Classification Model,Perspective Correction,Clip Comparison,Corner Visualization,Environment Secrets Store,Roboflow Custom Metadata,Detections Merge,Halo Visualization,Dynamic Zone,Keypoint Detection Model,Qwen-VL,JSON Parser,Email Notification,Halo Visualization,Object Detection Model,Data Aggregator,Google Gemma,Background Color Visualization,Ellipse Visualization,Email Notification,Twilio SMS/MMS Notification,Text Display,Polygon Visualization,Crop Visualization,Absolute Static Crop,Image Preprocessing,Template Matching,Model Monitoring Inference Aggregator,Relative Static Crop,OpenRouter,OpenAI,PLC ModbusTCP,Florence-2 Model,VLM As Detector,Motion Detection,Heatmap Visualization,OCR Model,OpenAI,Detections Filter,Perception Encoder Embedding Model,Blur Visualization,Dimension Collapse,Barcode Detection,Depth Estimation,Instance Segmentation Model,Stability AI Outpainting,Anthropic Claude,YOLO-World Model,Google Gemini,Clip Comparison,Google Gemini,PLC EthernetIP,Background Subtraction,Buffer,Keypoint Visualization,CSV Formatter,Webhook Sink,Byte Tracker,Stitch Images,Florence-2 Model,Current Time,Detections List Roll-Up,Contrast Equalization,Mask Edge Snap,OpenAI,Qwen3-VL,Moondream2,Line Counter,VLM As Detector,Google Gemini,Triangle Visualization,Slack Notification,Overlap Filter,Time in Zone,Inner Workflow,CLIP Embedding Model,First Non Empty Or Default,Detections Stabilizer,SIFT,Local File Sink,Multi-Label Classification Model,Cosine Similarity,Image Contours,Keypoint Detection Model,VLM As Classifier,Pixel Color Count,GLM-OCR,Roboflow Asset Library Attributes,Image Slicer,Polygon Zone Visualization,Time in Zone,Google Gemma API,Semantic Segmentation Model,Stitch OCR Detections,Image Threshold,Line Counter Visualization,Distance Measurement,Semantic Segmentation Model,Multi-Label Classification Model,Contrast Enhancement,Camera Calibration,QR Code Generator,Detection Offset,ByteTrack Tracker,Expression,Detection Event Log,Detections Transformation,S3 Sink,Microsoft SQL Server Sink,Mask Area Measurement,Google Vision OCR,Twilio SMS Notification,Image Blur,Detections Combine,Morphological Transformation,Property Definition,Camera Focus,Delta Filter,Size Measurement,Roboflow Vision Events,Stability AI Inpainting,PTZ Tracking (ONVIF),Classification Label Visualization,Bounding Rectangle,SAM2 Video Tracker,Stitch OCR Detections,Event Writer,Grid Visualization,Qwen3.5-VL,Byte Tracker,Switch Case,Dominant Color,Rate Limiter,Mask Visualization,Llama 3.2 Vision,Reference Path Visualization,Velocity,Label Visualization,Identify Outliers,Image Slicer,SIFT Comparison,Byte Tracker,OPC UA Writer Sink,Dot Visualization,Cache Set,Identify Changes,Dynamic Crop,Detections Stitch,Circle Visualization,Path Deviation,BoT-SORT Tracker,SAM3 Video Tracker,Camera Focus,Llama 3.2 Vision,Gaze Detection,Segment Anything 2 Model,OpenAI-Compatible LLM,MoonshotAI Kimi,Single-Label Classification Model,Overlap Analysis,QR Code Detection,Qwen3.5,CogVLM,Object Detection Model,SAM 3 Interactive,Qwen 3.6 API,Detections Consensus,Bounding Box Visualization,Multi-Label Classification Model,LMM,OpenAI,SAM 3,PLC Reader,Image Convert Grayscale,Instance Segmentation Model,Continue If,Roboflow Visual Search,EasyOCR,Roboflow Dataset Upload,SAM 3,Cache Get,Detections Classes Replacement,Instance Segmentation Model,Pixelate Visualization,Keypoint Detection Model,Roboflow Dataset Upload,SORT Tracker,Instance Segmentation Model,PLC Writer,Track Class Lock,Qwen 3.5 API,Anthropic Claude,Object Detection Model,Time in Zone,MQTT Writer,Polygon Visualization,OC-SORT Tracker,SAM 3,Model Comparison Visualization,Single-Label Classification Model,Seg Preview - outputs:
VLM As Classifier,Line Counter,MoonshotAI Kimi,Stability AI Image Generation,Trace Visualization,Path Deviation,Qwen2.5-VL,Image Stack,Anthropic Claude,Per-Class Confidence Filter,Icon Visualization,SIFT Comparison,Morphological Transformation,Color Visualization,SmolVLM2,LMM For Classification,Single-Label Classification Model,Perspective Correction,Corner Visualization,Clip Comparison,Roboflow Custom Metadata,Detections Merge,Halo Visualization,Dynamic Zone,Qwen-VL,Keypoint Detection Model,JSON Parser,Email Notification,Halo Visualization,Object Detection Model,Data Aggregator,Google Gemma,Background Color Visualization,Email Notification,Ellipse Visualization,Twilio SMS/MMS Notification,Text Display,Polygon Visualization,Crop Visualization,Absolute Static Crop,Image Preprocessing,Template Matching,Model Monitoring Inference Aggregator,Relative Static Crop,OpenRouter,OpenAI,PLC ModbusTCP,VLM As Detector,Florence-2 Model,OpenAI,Heatmap Visualization,Motion Detection,OCR Model,Detections Filter,Perception Encoder Embedding Model,Blur Visualization,Barcode Detection,Dimension Collapse,Depth Estimation,Instance Segmentation Model,Stability AI Outpainting,Anthropic Claude,YOLO-World Model,Google Gemini,Clip Comparison,Google Gemini,PLC EthernetIP,Background Subtraction,Keypoint Visualization,Buffer,CSV Formatter,Webhook Sink,Byte Tracker,Stitch Images,Florence-2 Model,Current Time,Detections List Roll-Up,Contrast Equalization,Mask Edge Snap,OpenAI,Qwen3-VL,Moondream2,Line Counter,VLM As Detector,Google Gemini,Triangle Visualization,Slack Notification,Overlap Filter,Time in Zone,Inner Workflow,CLIP Embedding Model,First Non Empty Or Default,Detections Stabilizer,SIFT,Local File Sink,Multi-Label Classification Model,Cosine Similarity,Image Contours,Keypoint Detection Model,VLM As Classifier,Pixel Color Count,GLM-OCR,Roboflow Asset Library Attributes,Image Slicer,Polygon Zone Visualization,Google Gemma API,Time in Zone,Contrast Enhancement,Stitch OCR Detections,Line Counter Visualization,Image Threshold,Semantic Segmentation Model,Distance Measurement,Multi-Label Classification Model,Semantic Segmentation Model,Camera Calibration,QR Code Generator,Detection Offset,ByteTrack Tracker,Expression,Detection Event Log,Detections Transformation,S3 Sink,Microsoft SQL Server Sink,Mask Area Measurement,Google Vision OCR,Twilio SMS Notification,Image Blur,Detections Combine,Morphological Transformation,Property Definition,Camera Focus,Roboflow Vision Events,Size Measurement,Delta Filter,PTZ Tracking (ONVIF),Stability AI Inpainting,Classification Label Visualization,SAM2 Video Tracker,Stitch OCR Detections,Bounding Rectangle,Event Writer,Grid Visualization,Qwen3.5-VL,Mask Visualization,Dominant Color,Byte Tracker,Rate Limiter,Llama 3.2 Vision,Switch Case,Image Slicer,Velocity,Label Visualization,Identify Outliers,Reference Path Visualization,Byte Tracker,SIFT Comparison,OPC UA Writer Sink,Dot Visualization,Identify Changes,Cache Set,Path Deviation,Detections Stitch,Circle Visualization,Llama 3.2 Vision,BoT-SORT Tracker,SAM3 Video Tracker,Dynamic Crop,Camera Focus,Gaze Detection,Segment Anything 2 Model,OpenAI-Compatible LLM,MoonshotAI Kimi,Single-Label Classification Model,Overlap Analysis,Qwen3.5,QR Code Detection,CogVLM,Object Detection Model,SAM 3 Interactive,Qwen 3.6 API,Detections Consensus,Bounding Box Visualization,Multi-Label Classification Model,LMM,SAM 3,OpenAI,PLC Reader,Image Convert Grayscale,Instance Segmentation Model,Continue If,Roboflow Visual Search,EasyOCR,Roboflow Dataset Upload,SAM 3,Cache Get,Instance Segmentation Model,Detections Classes Replacement,Pixelate Visualization,Keypoint Detection Model,Instance Segmentation Model,SORT Tracker,PLC Writer,Roboflow Dataset Upload,Track Class Lock,Qwen 3.5 API,Object Detection Model,Anthropic Claude,Time in Zone,MQTT Writer,Polygon Visualization,OC-SORT Tracker,SAM 3,Model Comparison Visualization,Single-Label Classification Model,Seg Preview
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Property Definition in version v1 has.
Bindings
-
input
data(*): Input data from any workflow step to extract properties from. Can be detections, classifications, OCR results, images, or any other workflow output. The data type determines which operations are applicable. Examples: detection predictions for extracting class names, classification results for extracting predicted class, OCR results for extracting text..
-
output
output(*): Equivalent of any element.
Example JSON definition of step Property Definition in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/property_definition@v1",
"data": "$steps.object_detection_model.predictions",
"operations": [
{
"property_name": "class_name",
"type": "DetectionsPropertyExtract"
}
]
}