Multi-Label Classification Model¶
v2¶
Class: RoboflowMultiLabelClassificationModelBlockV2 (there are multiple versions of this block)
Warning: This block has multiple versions. Please refer to the specific version for details. You can learn more about how versions work here: Versioning
Run inference on a multi-label classification model hosted on or uploaded to Roboflow.
You can query any model that is private to your account, or any public model available on Roboflow Universe.
You will need to set your Roboflow API key in your Inference environment to use this block. To learn more about setting your Roboflow API key, refer to the Inference documentation.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/roboflow_multi_label_classification_model@v2to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
model_id |
str |
Roboflow model identifier.. | ✅ |
confidence |
float |
Confidence threshold for predictions.. | ✅ |
disable_active_learning |
bool |
Boolean flag to disable project-level active learning for this block.. | ✅ |
active_learning_target_dataset |
str |
Target dataset for active learning, if enabled.. | ✅ |
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 Multi-Label Classification Model in version v2.
- inputs:
Circle Visualization,Background Color Visualization,Corner Visualization,Bounding Box Visualization,JSON Parser,Twilio SMS Notification,Line Counter Visualization,Image Preprocessing,Slack Notification,VLM as Detector,Keypoint Detection Model,VLM as Classifier,Trace Visualization,Label Visualization,Polygon Zone Visualization,Camera Focus,Local File Sink,Image Slicer,Image Slicer,Image Blur,Crop Visualization,Identify Outliers,Dot Visualization,Relative Static Crop,Model Comparison Visualization,Stability AI Inpainting,Single-Label Classification Model,Pixelate Visualization,Roboflow Dataset Upload,Perspective Correction,Detections Consensus,Image Convert Grayscale,Absolute Static Crop,Mask Visualization,Stability AI Image Generation,Webhook Sink,Color Visualization,Image Threshold,Clip Comparison,Dynamic Crop,Halo Visualization,Polygon Visualization,VLM as Classifier,Image Contours,Instance Segmentation Model,Camera Calibration,Email Notification,SIFT,SIFT Comparison,Reference Path Visualization,Object Detection Model,Classification Label Visualization,Triangle Visualization,Multi-Label Classification Model,Model Monitoring Inference Aggregator,SIFT Comparison,VLM as Detector,Roboflow Dataset Upload,Keypoint Visualization,Identify Changes,Roboflow Custom Metadata,Grid Visualization,Ellipse Visualization,Stitch Images,Blur Visualization - outputs:
Webhook Sink,Object Detection Model,Keypoint Detection Model,Detections Classes Replacement,Instance Segmentation Model,Keypoint Detection Model,Instance Segmentation Model,Object Detection Model,Multi-Label Classification Model,Classification Label Visualization,Model Monitoring Inference Aggregator,Single-Label Classification Model,Roboflow Dataset Upload,Multi-Label Classification Model,Roboflow Dataset Upload,Roboflow Custom Metadata,Single-Label Classification Model,Qwen2.5-VL
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Multi-Label Classification Model in version v2 has.
Bindings
-
input
images(image): The image to infer on..model_id(roboflow_model_id): Roboflow model identifier..confidence(float_zero_to_one): Confidence threshold for predictions..disable_active_learning(boolean): Boolean flag to disable project-level active learning for this block..active_learning_target_dataset(roboflow_project): Target dataset for active learning, if enabled..
-
output
predictions(classification_prediction): Predictions from classifier.inference_id(inference_id): Inference identifier.model_id(roboflow_model_id): Roboflow model id.
Example JSON definition of step Multi-Label Classification Model in version v2
{
"name": "<your_step_name_here>",
"type": "roboflow_core/roboflow_multi_label_classification_model@v2",
"images": "$inputs.image",
"model_id": "my_project/3",
"confidence": 0.3,
"disable_active_learning": true,
"active_learning_target_dataset": "my_project"
}
v1¶
Class: RoboflowMultiLabelClassificationModelBlockV1 (there are multiple versions of this block)
Warning: This block has multiple versions. Please refer to the specific version for details. You can learn more about how versions work here: Versioning
Run inference on a multi-label classification model hosted on or uploaded to Roboflow.
You can query any model that is private to your account, or any public model available on Roboflow Universe.
You will need to set your Roboflow API key in your Inference environment to use this block. To learn more about setting your Roboflow API key, refer to the Inference documentation.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/roboflow_multi_label_classification_model@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
model_id |
str |
Roboflow model identifier.. | ✅ |
confidence |
float |
Confidence threshold for predictions.. | ✅ |
disable_active_learning |
bool |
Boolean flag to disable project-level active learning for this block.. | ✅ |
active_learning_target_dataset |
str |
Target dataset for active learning, if enabled.. | ✅ |
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 Multi-Label Classification Model in version v1.
- inputs:
Circle Visualization,Background Color Visualization,Corner Visualization,Bounding Box Visualization,JSON Parser,Twilio SMS Notification,Line Counter Visualization,Image Preprocessing,Slack Notification,VLM as Detector,Keypoint Detection Model,VLM as Classifier,Trace Visualization,Label Visualization,Polygon Zone Visualization,Camera Focus,Local File Sink,Image Slicer,Image Slicer,Image Blur,Crop Visualization,Identify Outliers,Dot Visualization,Relative Static Crop,Model Comparison Visualization,Stability AI Inpainting,Single-Label Classification Model,Pixelate Visualization,Roboflow Dataset Upload,Perspective Correction,Detections Consensus,Image Convert Grayscale,Absolute Static Crop,Mask Visualization,Stability AI Image Generation,Webhook Sink,Color Visualization,Image Threshold,Clip Comparison,Dynamic Crop,Halo Visualization,Polygon Visualization,VLM as Classifier,Image Contours,Instance Segmentation Model,Camera Calibration,Email Notification,SIFT,SIFT Comparison,Reference Path Visualization,Object Detection Model,Classification Label Visualization,Triangle Visualization,Multi-Label Classification Model,Model Monitoring Inference Aggregator,SIFT Comparison,VLM as Detector,Roboflow Dataset Upload,Keypoint Visualization,Identify Changes,Roboflow Custom Metadata,Grid Visualization,Ellipse Visualization,Stitch Images,Blur Visualization - 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,Stability AI Inpainting,Line Counter,OpenAI,Distance Measurement,Stability AI Image Generation,Webhook Sink,Color Visualization,Image Threshold,Halo Visualization,Polygon Visualization,Detections Classes Replacement,CogVLM,Instance Segmentation Model,Email Notification,Classification Label Visualization,Llama 3.2 Vision,Google Vision OCR,Roboflow Dataset Upload,Ellipse Visualization,Size Measurement,Pixel Color Count,Cache Get,Bounding Box Visualization,Line Counter Visualization,Image Preprocessing,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,Florence-2 Model,Instance Segmentation Model,Florence-2 Model,Reference Path Visualization,CLIP Embedding Model,Model Monitoring Inference Aggregator,Triangle Visualization,SIFT Comparison,Keypoint Visualization,LMM For Classification,Roboflow Custom Metadata,Line Counter,Segment Anything 2 Model
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Multi-Label Classification Model in version v1 has.
Bindings
-
input
images(image): The image to infer on..model_id(roboflow_model_id): Roboflow model identifier..confidence(float_zero_to_one): Confidence threshold for predictions..disable_active_learning(boolean): Boolean flag to disable project-level active learning for this block..active_learning_target_dataset(roboflow_project): Target dataset for active learning, if enabled..
-
output
predictions(classification_prediction): Predictions from classifier.inference_id(string): String value.
Example JSON definition of step Multi-Label Classification Model in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/roboflow_multi_label_classification_model@v1",
"images": "$inputs.image",
"model_id": "my_project/3",
"confidence": 0.3,
"disable_active_learning": true,
"active_learning_target_dataset": "my_project"
}