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: Roboflow Dataset Upload, VLM as Detector, SIFT, Model Comparison Visualization, Identify Changes, Polygon Visualization, Dynamic Zone, Image Slicer, Dynamic Crop, Image Threshold, Local File Sink, Icon Visualization, Reference Path Visualization, Circle Visualization, Trace Visualization, Email Notification, Pixelate Visualization, Twilio SMS/MMS Notification, Line Counter Visualization, Camera Calibration, Webhook Sink, Halo Visualization, Blur Visualization, Relative Static Crop, QR Code Generator, Ellipse Visualization, Crop Visualization, Polygon Zone Visualization, Identify Outliers, Multi-Label Classification Model, Grid Visualization, Stability AI Inpainting, Image Slicer, Keypoint Detection Model, Classification Label Visualization, VLM as Classifier, Instance Segmentation Model, Roboflow Custom Metadata, Camera Focus, Model Monitoring Inference Aggregator, Image Blur, Corner Visualization, Object Detection Model, Email Notification, Mask Visualization, Stability AI Outpainting, Contrast Equalization, Absolute Static Crop, PTZ Tracking (ONVIF).md), SIFT Comparison, VLM as Detector, Background Subtraction, Depth Estimation, Stitch Images, Stability AI Image Generation, Triangle Visualization, Label Visualization, Detections Consensus, Camera Focus, SIFT Comparison, Text Display, Clip Comparison, Twilio SMS Notification, Keypoint Visualization, Dot Visualization, Perspective Correction, JSON Parser, Image Convert Grayscale, VLM as Classifier, Color Visualization, Background Color Visualization, Slack Notification, Image Contours, Motion Detection, Image Preprocessing, Roboflow Dataset Upload, Bounding Box Visualization, Morphological Transformation, Single-Label Classification Model
• outputs: Roboflow Dataset Upload, Object Detection Model, Webhook Sink, Qwen3-VL, SAM 3, SAM 3, Qwen2.5-VL, Multi-Label Classification Model, Moondream2, Instance Segmentation Model, SmolVLM2, Keypoint Detection Model, Object Detection Model, Keypoint Detection Model, Roboflow Dataset Upload, Classification Label Visualization, SAM 3, Instance Segmentation Model, Roboflow Custom Metadata, Detections Classes Replacement, Model Monitoring Inference Aggregator, Single-Label Classification Model, Multi-Label Classification Model, Single-Label Classification 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: Roboflow Dataset Upload, VLM as Detector, SIFT, Model Comparison Visualization, Identify Changes, Polygon Visualization, Dynamic Zone, Image Slicer, Dynamic Crop, Image Threshold, Local File Sink, Icon Visualization, Reference Path Visualization, Circle Visualization, Trace Visualization, Email Notification, Pixelate Visualization, Twilio SMS/MMS Notification, Line Counter Visualization, Camera Calibration, Webhook Sink, Halo Visualization, Blur Visualization, Relative Static Crop, QR Code Generator, Ellipse Visualization, Crop Visualization, Polygon Zone Visualization, Identify Outliers, Multi-Label Classification Model, Grid Visualization, Stability AI Inpainting, Image Slicer, Keypoint Detection Model, Classification Label Visualization, VLM as Classifier, Instance Segmentation Model, Roboflow Custom Metadata, Camera Focus, Model Monitoring Inference Aggregator, Image Blur, Corner Visualization, Object Detection Model, Email Notification, Mask Visualization, Stability AI Outpainting, Contrast Equalization, Absolute Static Crop, PTZ Tracking (ONVIF).md), SIFT Comparison, VLM as Detector, Background Subtraction, Depth Estimation, Stitch Images, Stability AI Image Generation, Triangle Visualization, Label Visualization, Detections Consensus, Camera Focus, SIFT Comparison, Text Display, Clip Comparison, Twilio SMS Notification, Keypoint Visualization, Dot Visualization, Perspective Correction, JSON Parser, Image Convert Grayscale, VLM as Classifier, Color Visualization, Background Color Visualization, Slack Notification, Image Contours, Motion Detection, Image Preprocessing, Roboflow Dataset Upload, Bounding Box Visualization, Morphological Transformation, Single-Label Classification Model
• outputs: Roboflow Dataset Upload, Google Vision OCR, Model Comparison Visualization, Google Gemini, Time in Zone, Polygon Visualization, Dynamic Crop, Image Threshold, Local File Sink, Icon Visualization, Reference Path Visualization, OpenAI, Circle Visualization, Trace Visualization, Email Notification, Twilio SMS/MMS Notification, Line Counter Visualization, Time in Zone, Webhook Sink, Cache Set, Halo Visualization, QR Code Generator, OpenAI, Ellipse Visualization, Seg Preview, Crop Visualization, Polygon Zone Visualization, Perception Encoder Embedding Model, Moondream2, OpenAI, Stability AI Inpainting, CLIP Embedding Model, Classification Label Visualization, Florence-2 Model, Size Measurement, SAM 3, Roboflow Custom Metadata, Instance Segmentation Model, Stitch OCR Detections, Model Monitoring Inference Aggregator, Image Blur, Corner Visualization, Anthropic Claude, LMM For Classification, Email Notification, Mask Visualization, Anthropic Claude, Stability AI Outpainting, Time in Zone, Contrast Equalization, SAM 3, SAM 3, PTZ Tracking (ONVIF).md), Detections Stitch, Instance Segmentation Model, Depth Estimation, Google Gemini, Segment Anything 2 Model, Path Deviation, Stability AI Image Generation, YOLO-World Model, Florence-2 Model, Line Counter, Triangle Visualization, Label Visualization, LMM, SIFT Comparison, Text Display, Clip Comparison, Twilio SMS Notification, Keypoint Visualization, Cache Get, Pixel Color Count, Dot Visualization, CogVLM, Perspective Correction, Distance Measurement, Color Visualization, Slack Notification, Background Color Visualization, Path Deviation, Image Preprocessing, Roboflow Dataset Upload, Anthropic Claude, Bounding Box Visualization, Google Gemini, Morphological Transformation, Line Counter, Detections Classes Replacement, OpenAI, Llama 3.2 Vision

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"
}