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:
Twilio SMS Notification,Slack Notification,VLM as Detector,VLM as Classifier,LMM,Path Deviation,Detections Merge,Google Gemini,Detection Offset,Roboflow Dataset Upload,Single-Label Classification Model,Line Counter,OpenAI,Detections Consensus,Gaze Detection,Webhook Sink,Detections Classes Replacement,VLM as Classifier,Dynamic Zone,Instance Segmentation Model,CogVLM,Email Notification,Object Detection Model,Single-Label Classification Model,Llama 3.2 Vision,Google Vision OCR,Roboflow Dataset Upload,Byte Tracker,JSON Parser,Object Detection Model,Keypoint Detection Model,Local File Sink,Detections Transformation,Anthropic Claude,Identify Outliers,Detections Stitch,OCR Model,YOLO-World Model,Stitch OCR Detections,Byte Tracker,Perspective Correction,OpenAI,Path Deviation,Time in Zone,Detections Filter,Clip Comparison,Time in Zone,Dynamic Crop,Template Matching,CSV Formatter,Byte Tracker,Florence-2 Model,Instance Segmentation Model,Keypoint Detection Model,SIFT Comparison,Multi-Label Classification Model,Florence-2 Model,Model Monitoring Inference Aggregator,Bounding Rectangle,Velocity,SIFT Comparison,VLM as Detector,Identify Changes,Multi-Label Classification Model,LMM For Classification,Roboflow Custom Metadata,Segment Anything 2 Model,Detections Stabilizer - outputs:
Circle Visualization,Background Color Visualization,Corner Visualization,Twilio SMS Notification,Slack Notification,LMM,Polygon Zone Visualization,Image Blur,Cache Set,Dot Visualization,Path Deviation,Google Gemini,Roboflow Dataset Upload,Single-Label Classification Model,Stability AI Inpainting,Pixelate Visualization,Line Counter,OpenAI,Detections Consensus,Gaze Detection,Distance Measurement,Stability AI Image Generation,Webhook Sink,Color Visualization,Image Threshold,Halo Visualization,Polygon Visualization,Instance Segmentation Model,CogVLM,Email Notification,Object Detection Model,Classification Label Visualization,Single-Label Classification Model,Llama 3.2 Vision,Google Vision OCR,Roboflow Dataset Upload,Ellipse Visualization,Size Measurement,Pixel Color Count,Cache Get,Bounding Box Visualization,Object Detection Model,Line Counter Visualization,Image Preprocessing,Keypoint Detection Model,Trace Visualization,Label Visualization,Local File Sink,Anthropic Claude,Crop Visualization,Detections Stitch,YOLO-World Model,Model Comparison Visualization,Perspective Correction,OpenAI,Path Deviation,Mask Visualization,Time in Zone,Clip Comparison,Time in Zone,Dynamic Crop,Template Matching,Florence-2 Model,Instance Segmentation Model,Keypoint Detection Model,Reference Path Visualization,Multi-Label Classification Model,Florence-2 Model,Triangle Visualization,Model Monitoring Inference Aggregator,CLIP Embedding Model,SIFT Comparison,Keypoint Visualization,Multi-Label Classification Model,LMM For Classification,Roboflow Custom Metadata,Line Counter,Segment Anything 2 Model,Blur 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[keypoint_detection_prediction,classification_prediction,instance_segmentation_prediction,object_detection_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
}