Single-Label Classification Model¶
v2¶
Class: RoboflowClassificationModelBlockV2 (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-class 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_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 Single-Label Classification Model in version v2.
- inputs:
Dynamic Crop,Motion Detection,Email Notification,Image Blur,Background Subtraction,SIFT Comparison,Image Preprocessing,Object Detection Model,Local File Sink,Bounding Box Visualization,Multi-Label Classification Model,Model Monitoring Inference Aggregator,Email Notification,Slack Notification,Camera Focus,Identify Outliers,Twilio SMS/MMS Notification,VLM As Detector,Dot Visualization,Roboflow Dataset Upload,Camera Focus,Depth Estimation,Polygon Visualization,Perspective Correction,PTZ Tracking (ONVIF),Camera Calibration,Corner Visualization,Icon Visualization,Image Slicer,Line Counter Visualization,Heatmap Visualization,Morphological Transformation,Stability AI Image Generation,Keypoint Visualization,VLM As Detector,Halo Visualization,Keypoint Detection Model,Background Color Visualization,Label Visualization,JSON Parser,Polygon Visualization,Pixelate Visualization,Single-Label Classification Model,Contrast Equalization,Triangle Visualization,Stability AI Outpainting,Mask Visualization,VLM As Classifier,Color Visualization,Instance Segmentation Model,Text Display,Relative Static Crop,Reference Path Visualization,Image Threshold,Clip Comparison,Classification Label Visualization,Webhook Sink,Circle Visualization,Polygon Zone Visualization,Image Contours,Image Convert Grayscale,Grid Visualization,VLM As Classifier,Roboflow Custom Metadata,Dynamic Zone,SIFT,Halo Visualization,Semantic Segmentation Model,Detections Consensus,Model Comparison Visualization,Blur Visualization,QR Code Generator,Absolute Static Crop,Image Slicer,S3 Sink,Stability AI Inpainting,Ellipse Visualization,Identify Changes,Crop Visualization,SIFT Comparison,Trace Visualization,Twilio SMS Notification,Stitch Images,Roboflow Dataset Upload - outputs:
Webhook Sink,Qwen2.5-VL,Keypoint Detection Model,Instance Segmentation Model,Object Detection Model,Single-Label Classification Model,Model Monitoring Inference Aggregator,Multi-Label Classification Model,Multi-Label Classification Model,Single-Label Classification Model,Keypoint Detection Model,Qwen3-VL,SmolVLM2,SAM 3,SAM 3,Roboflow Custom Metadata,Qwen3.5-VL,Roboflow Dataset Upload,Instance Segmentation Model,Detections Classes Replacement,SAM 3,Moondream2,Roboflow Dataset Upload,Object Detection Model,Semantic Segmentation Model,Classification Label Visualization
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Single-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 Single-Label Classification Model in version v2
{
"name": "<your_step_name_here>",
"type": "roboflow_core/roboflow_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: RoboflowClassificationModelBlockV1 (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-class 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_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 Single-Label Classification Model in version v1.
- inputs:
Dynamic Crop,Motion Detection,Email Notification,Image Blur,Background Subtraction,SIFT Comparison,Image Preprocessing,Object Detection Model,Local File Sink,Bounding Box Visualization,Multi-Label Classification Model,Model Monitoring Inference Aggregator,Email Notification,Slack Notification,Camera Focus,Identify Outliers,Twilio SMS/MMS Notification,VLM As Detector,Dot Visualization,Roboflow Dataset Upload,Camera Focus,Depth Estimation,Polygon Visualization,Perspective Correction,PTZ Tracking (ONVIF),Camera Calibration,Corner Visualization,Icon Visualization,Image Slicer,Line Counter Visualization,Heatmap Visualization,Morphological Transformation,Stability AI Image Generation,Keypoint Visualization,VLM As Detector,Halo Visualization,Keypoint Detection Model,Background Color Visualization,Label Visualization,JSON Parser,Polygon Visualization,Pixelate Visualization,Single-Label Classification Model,Contrast Equalization,Triangle Visualization,Stability AI Outpainting,Mask Visualization,VLM As Classifier,Color Visualization,Instance Segmentation Model,Text Display,Relative Static Crop,Reference Path Visualization,Image Threshold,Clip Comparison,Classification Label Visualization,Webhook Sink,Circle Visualization,Polygon Zone Visualization,Image Contours,Image Convert Grayscale,Grid Visualization,VLM As Classifier,Roboflow Custom Metadata,Dynamic Zone,SIFT,Halo Visualization,Semantic Segmentation Model,Detections Consensus,Model Comparison Visualization,Blur Visualization,QR Code Generator,Absolute Static Crop,Image Slicer,S3 Sink,Stability AI Inpainting,Ellipse Visualization,Identify Changes,Crop Visualization,SIFT Comparison,Trace Visualization,Twilio SMS Notification,Stitch Images,Roboflow Dataset Upload - outputs:
Dynamic Crop,Time in Zone,Email Notification,Image Blur,OpenAI,Google Vision OCR,SIFT Comparison,Google Gemini,Seg Preview,Image Preprocessing,Time in Zone,Instance Segmentation Model,Local File Sink,Model Monitoring Inference Aggregator,Bounding Box Visualization,Anthropic Claude,Email Notification,Slack Notification,Twilio SMS/MMS Notification,Detections Stitch,Dot Visualization,Florence-2 Model,Roboflow Dataset Upload,Cache Set,SAM 3,Depth Estimation,Stitch OCR Detections,Polygon Visualization,Perspective Correction,OpenAI,PTZ Tracking (ONVIF),Line Counter,Moondream2,Icon Visualization,Corner Visualization,Line Counter Visualization,Heatmap Visualization,Google Gemini,Stability AI Image Generation,Morphological Transformation,Distance Measurement,Keypoint Visualization,Halo Visualization,Background Color Visualization,Label Visualization,Polygon Visualization,LMM,CogVLM,Time in Zone,Contrast Equalization,Triangle Visualization,Stability AI Outpainting,Mask Visualization,Color Visualization,Instance Segmentation Model,Detections Classes Replacement,Text Display,Line Counter,Reference Path Visualization,Stitch OCR Detections,OpenAI,Llama 3.2 Vision,Image Threshold,Clip Comparison,Classification Label Visualization,Webhook Sink,Circle Visualization,Polygon Zone Visualization,Florence-2 Model,SAM 3,Roboflow Custom Metadata,Perception Encoder Embedding Model,LMM For Classification,Cache Get,YOLO-World Model,Halo Visualization,Anthropic Claude,Google Gemini,Model Comparison Visualization,QR Code Generator,Path Deviation,S3 Sink,Anthropic Claude,SAM 3,CLIP Embedding Model,Stability AI Inpainting,Ellipse Visualization,Crop Visualization,Path Deviation,Trace Visualization,Segment Anything 2 Model,Twilio SMS Notification,Size Measurement,OpenAI,Pixel Color Count,Roboflow Dataset Upload
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Single-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 Single-Label Classification Model in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/roboflow_classification_model@v1",
"images": "$inputs.image",
"model_id": "my_project/3",
"confidence": 0.3,
"disable_active_learning": true,
"active_learning_target_dataset": "my_project"
}