Roboflow Custom Metadata¶
Class: RoboflowCustomMetadataBlockV1
Source: inference.core.workflows.core_steps.sinks.roboflow.custom_metadata.v1.RoboflowCustomMetadataBlockV1
Block allows users to add custom metadata to each inference result in Roboflow Model Monitoring dashboard.
This is useful for adding information specific to your use case. For example, if you want to be able to filter inferences by a specific label such as location, you can attach those labels to each inference with this block.
For more information on Model Monitoring at Roboflow, see https://docs.roboflow.com/deploy/model-monitoring.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/roboflow_custom_metadata@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
field_value |
str |
This is the name of the metadata field you are creating. | ✅ |
field_name |
str |
Name of the field to be updated.. | ❌ |
fire_and_forget |
bool |
Boolean flag to run the block asynchronously (True) for faster workflows or synchronously (False) for debugging and error handling.. | ✅ |
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 Roboflow Custom Metadata in version v1.
- inputs:
Segment Anything 2 Model,Clip Comparison,Perspective Correction,Object Detection Model,Roboflow Custom Metadata,Object Detection Model,SIFT Comparison,Detection Offset,CogVLM,VLM as Detector,Multi-Label Classification Model,OpenAI,Multi-Label Classification Model,VLM as Detector,Google Vision OCR,Identify Outliers,Roboflow Dataset Upload,Gaze Detection,Identify Changes,VLM as Classifier,Byte Tracker,Llama 3.2 Vision,Detections Stabilizer,Template Matching,Dynamic Zone,Detections Transformation,Time in Zone,Model Monitoring Inference Aggregator,Line Counter,Anthropic Claude,Webhook Sink,Instance Segmentation Model,SIFT Comparison,Time in Zone,Instance Segmentation Model,Slack Notification,Detections Filter,Stitch OCR Detections,Path Deviation,Detections Consensus,Twilio SMS Notification,VLM as Classifier,Keypoint Detection Model,Roboflow Dataset Upload,Google Gemini,JSON Parser,Byte Tracker,Velocity,Keypoint Detection Model,Bounding Rectangle,Florence-2 Model,Single-Label Classification Model,Byte Tracker,Florence-2 Model,Local File Sink,LMM For Classification,Detections Stitch,OCR Model,LMM,Email Notification,Path Deviation,Single-Label Classification Model,YOLO-World Model,CSV Formatter,Detections Classes Replacement,OpenAI - outputs:
Segment Anything 2 Model,Cache Get,Stability AI Inpainting,Clip Comparison,Perspective Correction,Cache Set,Object Detection Model,Roboflow Custom Metadata,Object Detection Model,SIFT Comparison,CogVLM,Ellipse Visualization,Multi-Label Classification Model,OpenAI,Trace Visualization,CLIP Embedding Model,Multi-Label Classification Model,Dot Visualization,Google Vision OCR,Roboflow Dataset Upload,Polygon Zone Visualization,Gaze Detection,Classification Label Visualization,Corner Visualization,Llama 3.2 Vision,Line Counter,Reference Path Visualization,Dynamic Crop,Label Visualization,Mask Visualization,Triangle Visualization,Template Matching,Line Counter Visualization,Model Monitoring Inference Aggregator,Time in Zone,Blur Visualization,Line Counter,Anthropic Claude,Instance Segmentation Model,Webhook Sink,Time in Zone,Instance Segmentation Model,Slack Notification,Pixelate Visualization,Path Deviation,OpenAI,Detections Consensus,Twilio SMS Notification,Keypoint Detection Model,Roboflow Dataset Upload,Google Gemini,Model Comparison Visualization,Halo Visualization,Crop Visualization,Image Blur,Distance Measurement,Circle Visualization,Keypoint Detection Model,Image Preprocessing,Background Color Visualization,Pixel Color Count,Size Measurement,Florence-2 Model,Single-Label Classification Model,Bounding Box Visualization,Florence-2 Model,Local File Sink,LMM For Classification,Stability AI Image Generation,Image Threshold,Detections Stitch,LMM,Keypoint Visualization,Email Notification,Color Visualization,Path Deviation,Single-Label Classification Model,YOLO-World Model,Polygon Visualization
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Roboflow Custom Metadata in version v1 has.
Bindings
-
input
predictions(Union[instance_segmentation_prediction,keypoint_detection_prediction,object_detection_prediction,classification_prediction]): Model predictions to attach custom metadata to..field_value(string): This is the name of the metadata field you are creating.fire_and_forget(boolean): Boolean flag to run the block asynchronously (True) for faster workflows or synchronously (False) for debugging and error handling..
-
output
Example JSON definition of step Roboflow Custom Metadata in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/roboflow_custom_metadata@v1",
"predictions": "$steps.my_step.predictions",
"field_value": "toronto",
"field_name": "The name of the value of the field",
"fire_and_forget": true
}