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:
Detections Classes Replacement,Morphological Transformation,Image Preprocessing,Email Notification,VLM As Classifier,Halo Visualization,Morphological Transformation,Detections Transformation,Pixel Color Count,Object Detection Model,Time in Zone,Template Matching,Image Threshold,Text Display,BoT-SORT Tracker,Model Monitoring Inference Aggregator,Pixelate Visualization,Keypoint Detection Model,Time in Zone,Qwen-VL,OpenAI,CogVLM,Crop Visualization,Cosine Similarity,SAM 3,Dot Visualization,Detections Merge,Google Vision OCR,Detections List Roll-Up,PLC EthernetIP,Florence-2 Model,Dimension Collapse,Roboflow Dataset Upload,Qwen3.5-VL,Mask Edge Snap,Roboflow Vision Events,Polygon Zone Visualization,Qwen2.5-VL,Polygon Visualization,SIFT Comparison,Absolute Static Crop,S3 Sink,Twilio SMS/MMS Notification,QR Code Generator,SIFT Comparison,Contrast Enhancement,Per-Class Confidence Filter,Single-Label Classification Model,Cache Get,Stitch OCR Detections,Dynamic Zone,Detections Filter,OCR Model,Byte Tracker,Color Visualization,Roboflow Dataset Upload,Gaze Detection,Bounding Rectangle,Roboflow Custom Metadata,Environment Secrets Store,LMM For Classification,Detections Stabilizer,Line Counter Visualization,Image Blur,Stability AI Inpainting,Object Detection Model,Blur Visualization,OpenAI-Compatible LLM,Path Deviation,Current Time,SAM 3,Perspective Correction,Keypoint Visualization,Byte Tracker,Detection Offset,Anthropic Claude,MQTT Writer,MoonshotAI Kimi,Google Gemini,Identify Changes,Image Slicer,SAM 3,Depth Estimation,Detections Consensus,Detections Stitch,Ellipse Visualization,Google Gemma API,Object Detection Model,PLC ModbusTCP,Slack Notification,Overlap Analysis,Rate Limiter,Identify Outliers,Inner Workflow,Time in Zone,Image Stack,Delta Filter,Google Gemini,Cache Set,Bounding Box Visualization,Label Visualization,Keypoint Detection Model,Size Measurement,Camera Focus,Stitch OCR Detections,CSV Formatter,Keypoint Detection Model,Multi-Label Classification Model,OpenAI,SIFT,Perception Encoder Embedding Model,Anthropic Claude,Image Convert Grayscale,Roboflow Asset Library Attributes,OC-SORT Tracker,Moondream2,CLIP Embedding Model,Florence-2 Model,Seg Preview,Overlap Filter,EasyOCR,YOLO-World Model,Buffer,Segment Anything 2 Model,Multi-Label Classification Model,Twilio SMS Notification,Local File Sink,Single-Label Classification Model,Icon Visualization,Triangle Visualization,VLM As Classifier,Qwen 3.5 API,Mask Area Measurement,Path Deviation,JSON Parser,OpenRouter,Dominant Color,Instance Segmentation Model,Distance Measurement,Qwen3-VL,Instance Segmentation Model,OpenAI,Background Color Visualization,MoonshotAI Kimi,Continue If,Byte Tracker,Google Gemini,Grid Visualization,Clip Comparison,Semantic Segmentation Model,Corner Visualization,Image Slicer,Single-Label Classification Model,Reference Path Visualization,SmolVLM2,Line Counter,First Non Empty Or Default,Halo Visualization,Dynamic Crop,Webhook Sink,Instance Segmentation Model,Stability AI Outpainting,Detection Event Log,VLM As Detector,Relative Static Crop,Anthropic Claude,Expression,Clip Comparison,Multi-Label Classification Model,SORT Tracker,OpenAI,Llama 3.2 Vision,Barcode Detection,ByteTrack Tracker,Velocity,Motion Detection,Detections Combine,Camera Calibration,Model Comparison Visualization,Data Aggregator,Trace Visualization,Google Gemma,PTZ Tracking (ONVIF),Line Counter,OPC UA Writer Sink,QR Code Detection,Circle Visualization,Email Notification,LMM,Event Writer,Instance Segmentation Model,Camera Focus,Contrast Equalization,Heatmap Visualization,Background Subtraction,Image Contours,SAM2 Video Tracker,Qwen 3.6 API,GLM-OCR,Qwen3.5,VLM As Detector,Classification Label Visualization,Llama 3.2 Vision,Property Definition,Stitch Images,Mask Visualization,Microsoft SQL Server Sink,Stability AI Image Generation,Semantic Segmentation Model,Polygon Visualization - outputs:
Detections Classes Replacement,Morphological Transformation,Image Preprocessing,Email Notification,VLM As Classifier,Morphological Transformation,Halo Visualization,Detections Transformation,Pixel Color Count,Object Detection Model,BoT-SORT Tracker,Text Display,Template Matching,Time in Zone,Image Threshold,Model Monitoring Inference Aggregator,Pixelate Visualization,Keypoint Detection Model,Time in Zone,Qwen-VL,OpenAI,CogVLM,Crop Visualization,SAM 3,Cosine Similarity,Dot Visualization,Google Vision OCR,PLC EthernetIP,Detections List Roll-Up,Detections Merge,Florence-2 Model,Dimension Collapse,Roboflow Dataset Upload,Mask Edge Snap,Qwen3.5-VL,Roboflow Vision Events,Polygon Zone Visualization,Qwen2.5-VL,Polygon Visualization,SIFT Comparison,S3 Sink,Absolute Static Crop,Twilio SMS/MMS Notification,QR Code Generator,SIFT Comparison,Contrast Enhancement,Per-Class Confidence Filter,Single-Label Classification Model,Cache Get,Stitch OCR Detections,Dynamic Zone,Detections Filter,OCR Model,Byte Tracker,Color Visualization,Roboflow Dataset Upload,Gaze Detection,Roboflow Custom Metadata,Bounding Rectangle,LMM For Classification,OpenAI-Compatible LLM,Line Counter Visualization,Stability AI Inpainting,Image Blur,Object Detection Model,Blur Visualization,Detections Stabilizer,Path Deviation,Current Time,SAM 3,Perspective Correction,Keypoint Visualization,Byte Tracker,Detection Offset,Anthropic Claude,MQTT Writer,MoonshotAI Kimi,Google Gemini,Image Slicer,Identify Changes,SAM 3,Depth Estimation,Detections Consensus,Ellipse Visualization,Google Gemma API,Detections Stitch,Object Detection Model,PLC ModbusTCP,Slack Notification,Overlap Analysis,Rate Limiter,Identify Outliers,Time in Zone,Inner Workflow,Image Stack,Delta Filter,Google Gemini,Cache Set,Label Visualization,Bounding Box Visualization,Keypoint Detection Model,Stitch OCR Detections,Camera Focus,CSV Formatter,Size Measurement,Keypoint Detection Model,Multi-Label Classification Model,OpenAI,SIFT,Perception Encoder Embedding Model,Anthropic Claude,Image Convert Grayscale,OC-SORT Tracker,Roboflow Asset Library Attributes,Moondream2,CLIP Embedding Model,Florence-2 Model,Seg Preview,Overlap Filter,EasyOCR,YOLO-World Model,Multi-Label Classification Model,Segment Anything 2 Model,Twilio SMS Notification,Buffer,Local File Sink,Single-Label Classification Model,Triangle Visualization,VLM As Classifier,Qwen 3.5 API,Mask Area Measurement,Icon Visualization,Path Deviation,JSON Parser,OpenRouter,Dominant Color,Instance Segmentation Model,Distance Measurement,Qwen3-VL,Instance Segmentation Model,OpenAI,Background Color Visualization,MoonshotAI Kimi,Continue If,Byte Tracker,Google Gemini,Grid Visualization,Clip Comparison,Semantic Segmentation Model,Corner Visualization,Reference Path Visualization,Image Slicer,SmolVLM2,Single-Label Classification Model,Line Counter,Halo Visualization,First Non Empty Or Default,Webhook Sink,Dynamic Crop,Instance Segmentation Model,Stability AI Outpainting,Detection Event Log,VLM As Detector,Relative Static Crop,Anthropic Claude,SORT Tracker,Expression,Clip Comparison,Multi-Label Classification Model,OpenAI,Llama 3.2 Vision,Barcode Detection,ByteTrack Tracker,Velocity,Motion Detection,Detections Combine,Camera Calibration,PTZ Tracking (ONVIF),Trace Visualization,Model Comparison Visualization,Data Aggregator,Google Gemma,OPC UA Writer Sink,Line Counter,QR Code Detection,Circle Visualization,Email Notification,LMM,Event Writer,Instance Segmentation Model,Heatmap Visualization,Background Subtraction,Contrast Equalization,GLM-OCR,Qwen 3.6 API,Image Contours,SAM2 Video Tracker,Camera Focus,Qwen3.5,VLM As Detector,Classification Label Visualization,Llama 3.2 Vision,Property Definition,Stitch Images,Mask Visualization,Microsoft SQL Server Sink,Stability AI Image Generation,Semantic Segmentation Model,Polygon Visualization
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"
}
]
}