Single-Label Classification Model

v2

Class: RoboflowClassificationModelBlockV2 (there are multiple versions of this block)

Source: inference.core.workflows.core_steps.models.roboflow.multi_class_classification.v2.RoboflowClassificationModelBlockV2

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: Trace Visualization, Contrast Equalization, Detections Consensus, Circle Visualization, Background Color Visualization, Slack Notification, VLM As Classifier, Color Visualization, Image Slicer, Stability AI Inpainting, Reference Path Visualization, Corner Visualization, Clip Comparison, Local File Sink, JSON Parser, Relative Static Crop, Perspective Correction, Roboflow Dataset Upload, Model Monitoring Inference Aggregator, Image Threshold, Pixelate Visualization, Multi-Label Classification Model, Polygon Visualization, Ellipse Visualization, Email Notification, Label Visualization, VLM As Detector, Image Slicer, Object Detection Model, Bounding Box Visualization, Crop Visualization, Twilio SMS/MMS Notification, VLM As Detector, Image Blur, Halo Visualization, Icon Visualization, SIFT, Triangle Visualization, Image Contours, Morphological Transformation, Motion Detection, Instance Segmentation Model, Stitch Images, SIFT Comparison, Heatmap Visualization, Blur Visualization, Polygon Visualization, Mask Visualization, Email Notification, Stability AI Outpainting, Camera Calibration, Dynamic Zone, Line Counter Visualization, Camera Focus, Webhook Sink, Image Convert Grayscale, Keypoint Detection Model, Twilio SMS Notification, Camera Focus, Classification Label Visualization, Model Comparison Visualization, Roboflow Dataset Upload, Stability AI Image Generation, SIFT Comparison, Polygon Zone Visualization, VLM As Classifier, Grid Visualization, Background Subtraction, Halo Visualization, Keypoint Visualization, QR Code Generator, Identify Outliers, Depth Estimation, Text Display, Single-Label Classification Model, Dot Visualization, Identify Changes, Roboflow Custom Metadata, PTZ Tracking (ONVIF).md), Dynamic Crop, Image Preprocessing, Absolute Static Crop
• outputs: Classification Label Visualization, Object Detection Model, SAM 3, SmolVLM2, Roboflow Dataset Upload, Qwen3-VL, Qwen2.5-VL, Moondream2, Detections Classes Replacement, Single-Label Classification Model, SAM 3, Roboflow Dataset Upload, Model Monitoring Inference Aggregator, Instance Segmentation Model, Instance Segmentation Model, Multi-Label Classification Model, Object Detection Model, Single-Label Classification Model, Roboflow Custom Metadata, Webhook Sink, Keypoint Detection Model, SAM 3, Multi-Label Classification Model, Keypoint Detection Model

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)

Source: inference.core.workflows.core_steps.models.roboflow.multi_class_classification.v1.RoboflowClassificationModelBlockV1

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: Trace Visualization, Contrast Equalization, Detections Consensus, Circle Visualization, Background Color Visualization, Slack Notification, VLM As Classifier, Color Visualization, Image Slicer, Stability AI Inpainting, Reference Path Visualization, Corner Visualization, Clip Comparison, Local File Sink, JSON Parser, Relative Static Crop, Perspective Correction, Roboflow Dataset Upload, Model Monitoring Inference Aggregator, Image Threshold, Pixelate Visualization, Multi-Label Classification Model, Polygon Visualization, Ellipse Visualization, Email Notification, Label Visualization, VLM As Detector, Image Slicer, Object Detection Model, Bounding Box Visualization, Crop Visualization, Twilio SMS/MMS Notification, VLM As Detector, Image Blur, Halo Visualization, Icon Visualization, SIFT, Triangle Visualization, Image Contours, Morphological Transformation, Motion Detection, Instance Segmentation Model, Stitch Images, SIFT Comparison, Heatmap Visualization, Blur Visualization, Polygon Visualization, Mask Visualization, Email Notification, Stability AI Outpainting, Camera Calibration, Dynamic Zone, Line Counter Visualization, Camera Focus, Webhook Sink, Image Convert Grayscale, Keypoint Detection Model, Twilio SMS Notification, Camera Focus, Classification Label Visualization, Model Comparison Visualization, Roboflow Dataset Upload, Stability AI Image Generation, SIFT Comparison, Polygon Zone Visualization, VLM As Classifier, Grid Visualization, Background Subtraction, Halo Visualization, Keypoint Visualization, QR Code Generator, Identify Outliers, Depth Estimation, Text Display, Single-Label Classification Model, Dot Visualization, Identify Changes, Roboflow Custom Metadata, PTZ Tracking (ONVIF).md), Dynamic Crop, Image Preprocessing, Absolute Static Crop
• outputs: Trace Visualization, Contrast Equalization, CLIP Embedding Model, Circle Visualization, Background Color Visualization, Size Measurement, Slack Notification, Perception Encoder Embedding Model, Color Visualization, Florence-2 Model, Stability AI Inpainting, Reference Path Visualization, OpenAI, Corner Visualization, SAM 3, Pixel Color Count, Clip Comparison, Local File Sink, Seg Preview, Perspective Correction, Roboflow Dataset Upload, OpenAI, Model Monitoring Inference Aggregator, Instance Segmentation Model, Image Threshold, Email Notification, Polygon Visualization, Ellipse Visualization, CogVLM, Label Visualization, Bounding Box Visualization, Google Vision OCR, Crop Visualization, SAM 3, Stitch OCR Detections, Twilio SMS/MMS Notification, Stitch OCR Detections, Time in Zone, Image Blur, Moondream2, Path Deviation, Halo Visualization, Anthropic Claude, Icon Visualization, Triangle Visualization, Anthropic Claude, Morphological Transformation, Line Counter, Instance Segmentation Model, Heatmap Visualization, SAM 3, Time in Zone, OpenAI, Polygon Visualization, Mask Visualization, Detections Stitch, Email Notification, Cache Get, Stability AI Outpainting, Time in Zone, Detections Classes Replacement, Google Gemini, Segment Anything 2 Model, LMM For Classification, Anthropic Claude, Google Gemini, Google Gemini, Line Counter Visualization, OpenAI, Webhook Sink, Twilio SMS Notification, LMM, Classification Label Visualization, Model Comparison Visualization, Roboflow Dataset Upload, Stability AI Image Generation, SIFT Comparison, Polygon Zone Visualization, Distance Measurement, YOLO-World Model, Line Counter, Halo Visualization, Florence-2 Model, Keypoint Visualization, QR Code Generator, Depth Estimation, Text Display, Dot Visualization, Cache Set, Llama 3.2 Vision, Roboflow Custom Metadata, PTZ Tracking (ONVIF).md), Dynamic Crop, Image Preprocessing, Path Deviation

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"
}