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 in Roboflow Customer Metadata. | ❌ |
fire_and_forget |
bool |
Boolean flag dictating if sink is supposed to be executed in the background, not waiting on status of registration before end of workflow run. Use True if best-effort registration is needed, use False while debugging and if error handling is needed. |
✅ |
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:
Path Deviation,Multi-Label Classification Model,LMM For Classification,Keypoint Detection Model,Gaze Detection,Instance Segmentation Model,Single-Label Classification Model,OCR Model,Object Detection Model,Line Counter,Detections Filter,YOLO-World Model,Model Monitoring Inference Aggregator,VLM as Detector,Google Vision OCR,Email Notification,CogVLM,Byte Tracker,Detections Classes Replacement,Template Matching,Detection Offset,Roboflow Dataset Upload,Slack Notification,Stitch OCR Detections,Identify Changes,Byte Tracker,LMM,VLM as Detector,Byte Tracker,Bounding Rectangle,Object Detection Model,Time in Zone,Detections Stitch,Florence-2 Model,SIFT Comparison,Keypoint Detection Model,Perspective Correction,Local File Sink,VLM as Classifier,Twilio SMS Notification,Detections Consensus,Webhook Sink,OpenAI,Roboflow Custom Metadata,Instance Segmentation Model,Roboflow Dataset Upload,Clip Comparison,VLM as Classifier,Anthropic Claude,SIFT Comparison,Google Gemini,Segment Anything 2 Model,JSON Parser,Single-Label Classification Model,Identify Outliers,Time in Zone,Florence-2 Model,Detections Stabilizer,Path Deviation,OpenAI,Multi-Label Classification Model,CSV Formatter,Llama 3.2 Vision,Detections Transformation - outputs:
Multi-Label Classification Model,Pixelate Visualization,Path Deviation,LMM For Classification,Keypoint Detection Model,Gaze Detection,Line Counter,Instance Segmentation Model,CLIP Embedding Model,Single-Label Classification Model,Blur Visualization,Mask Visualization,Object Detection Model,Line Counter,YOLO-World Model,Model Monitoring Inference Aggregator,Cache Get,Polygon Visualization,Halo Visualization,Google Vision OCR,Email Notification,Model Comparison Visualization,CogVLM,Image Threshold,Keypoint Visualization,Template Matching,Image Preprocessing,Slack Notification,Roboflow Dataset Upload,Background Color Visualization,Bounding Box Visualization,Label Visualization,Classification Label Visualization,Ellipse Visualization,Line Counter Visualization,LMM,Reference Path Visualization,Stability AI Inpainting,Dynamic Crop,Triangle Visualization,Object Detection Model,Distance Measurement,Time in Zone,Detections Stitch,Florence-2 Model,SIFT Comparison,Keypoint Detection Model,Corner Visualization,Perspective Correction,Local File Sink,Polygon Zone Visualization,Twilio SMS Notification,Trace Visualization,Webhook Sink,Detections Consensus,Size Measurement,Roboflow Custom Metadata,OpenAI,Cache Set,Instance Segmentation Model,Crop Visualization,Roboflow Dataset Upload,Clip Comparison,Anthropic Claude,Image Blur,Dot Visualization,Circle Visualization,Google Gemini,Segment Anything 2 Model,Single-Label Classification Model,Time in Zone,Florence-2 Model,Path Deviation,OpenAI,Color Visualization,Multi-Label Classification Model,Pixel Color Count,Llama 3.2 Vision
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,classification_prediction,object_detection_prediction]): Reference data to extract property from.field_value(string): This is the name of the metadata field you are creating.fire_and_forget(boolean): Boolean flag dictating if sink is supposed to be executed in the background, not waiting on status of registration before end of workflow run. UseTrueif best-effort registration is needed, useFalsewhile debugging and if error handling is needed.
-
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
}