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:
Slack Notification,Image Slicer,Stability AI Inpainting,Pixelate Visualization,Perspective Correction,Clip Comparison,Relative Static Crop,Roboflow Custom Metadata,Object Detection Model,Detections Consensus,Twilio SMS Notification,VLM as Classifier,SIFT Comparison,Keypoint Detection Model,Roboflow Dataset Upload,Grid Visualization,Ellipse Visualization,SIFT,Model Comparison Visualization,VLM as Detector,Halo Visualization,Image Contours,Multi-Label Classification Model,JSON Parser,Crop Visualization,Absolute Static Crop,Camera Focus,Image Blur,Trace Visualization,Circle Visualization,Image Preprocessing,VLM as Detector,Background Color Visualization,Dot Visualization,Identify Changes,Polygon Zone Visualization,Identify Outliers,Roboflow Dataset Upload,VLM as Classifier,Single-Label Classification Model,Classification Label Visualization,Bounding Box Visualization,Corner Visualization,Local File Sink,Image Slicer,Dynamic Crop,Reference Path Visualization,Label Visualization,Mask Visualization,Stitch Images,Webhook Sink,Triangle Visualization,Stability AI Image Generation,Image Threshold,Line Counter Visualization,Keypoint Visualization,Model Monitoring Inference Aggregator,Color Visualization,Email Notification,Blur Visualization,Instance Segmentation Model,SIFT Comparison,Image Convert Grayscale,Polygon Visualization - outputs:
Keypoint Detection Model,Multi-Label Classification Model,Instance Segmentation Model,Object Detection Model,Roboflow Dataset Upload,Roboflow Custom Metadata,Object Detection Model,Single-Label Classification Model,Classification Label Visualization,Roboflow Dataset Upload,Keypoint Detection Model,Multi-Label Classification Model,Qwen2.5-VL,Model Monitoring Inference Aggregator,Single-Label Classification Model,Webhook Sink,Instance Segmentation Model,Detections Classes Replacement
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:
Slack Notification,Image Slicer,Stability AI Inpainting,Pixelate Visualization,Perspective Correction,Clip Comparison,Relative Static Crop,Roboflow Custom Metadata,Object Detection Model,Detections Consensus,Twilio SMS Notification,VLM as Classifier,SIFT Comparison,Keypoint Detection Model,Roboflow Dataset Upload,Grid Visualization,Ellipse Visualization,SIFT,Model Comparison Visualization,VLM as Detector,Halo Visualization,Image Contours,Multi-Label Classification Model,JSON Parser,Crop Visualization,Absolute Static Crop,Camera Focus,Image Blur,Trace Visualization,Circle Visualization,Image Preprocessing,VLM as Detector,Background Color Visualization,Dot Visualization,Identify Changes,Polygon Zone Visualization,Identify Outliers,Roboflow Dataset Upload,VLM as Classifier,Single-Label Classification Model,Classification Label Visualization,Bounding Box Visualization,Corner Visualization,Local File Sink,Image Slicer,Dynamic Crop,Reference Path Visualization,Label Visualization,Mask Visualization,Stitch Images,Webhook Sink,Triangle Visualization,Stability AI Image Generation,Image Threshold,Line Counter Visualization,Keypoint Visualization,Model Monitoring Inference Aggregator,Color Visualization,Email Notification,Blur Visualization,Instance Segmentation Model,SIFT Comparison,Image Convert Grayscale,Polygon Visualization - outputs:
Segment Anything 2 Model,Cache Get,Stability AI Inpainting,Clip Comparison,Perspective Correction,Cache Set,Roboflow Custom Metadata,SIFT Comparison,CogVLM,Ellipse Visualization,OpenAI,Trace Visualization,CLIP Embedding Model,Dot Visualization,Google Vision OCR,Roboflow Dataset Upload,Polygon Zone Visualization,Classification Label Visualization,Llama 3.2 Vision,Corner Visualization,Line Counter,Dynamic Crop,Reference Path Visualization,Label Visualization,Mask Visualization,Triangle Visualization,Line Counter Visualization,Model Monitoring Inference Aggregator,Time in Zone,Line Counter,Anthropic Claude,Instance Segmentation Model,Webhook Sink,Time in Zone,Instance Segmentation Model,Slack Notification,Path Deviation,OpenAI,Twilio SMS Notification,Roboflow Dataset Upload,Google Gemini,Model Comparison Visualization,Halo Visualization,Crop Visualization,Image Blur,Distance Measurement,Circle Visualization,Image Preprocessing,Background Color Visualization,Pixel Color Count,Size Measurement,Florence-2 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,YOLO-World Model,Detections Classes Replacement,Polygon Visualization
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"
}