Skip to content

Single-Label Classification Model

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 Parameter to decide if Active Learning data sampling is disabled for the model. ✅
active_learning_target_dataset str Target dataset for Active Learning data sampling - see Roboflow Active Learning docs for more information. ✅

The Refs column marks possibility to parametrise the property with dynamic values available in workflow runtime. See Bindings for more info.

Available Connections

Check what blocks you can connect to Single-Label Classification Model in version v2.

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): Parameter to decide if Active Learning data sampling is disabled for the model.
    • active_learning_target_dataset (roboflow_project): Target dataset for Active Learning data sampling - see Roboflow Active Learning docs for more information.

  • output

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"
}

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 Parameter to decide if Active Learning data sampling is disabled for the model. ✅
active_learning_target_dataset str Target dataset for Active Learning data sampling - see Roboflow Active Learning docs for more information. ✅

The Refs column marks possibility to parametrise the property with dynamic values available in workflow runtime. See Bindings for more info.

Available Connections

Check what blocks you can connect to Single-Label Classification Model in version v1.

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): Parameter to decide if Active Learning data sampling is disabled for the model.
    • active_learning_target_dataset (roboflow_project): Target dataset for Active Learning data sampling - see Roboflow Active Learning docs for more information.

  • output

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"
}