RoboflowClassificationModel¶

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.

Properties¶

Name	Type	Description	Refs
`name`	`str`	Unique name of step in workflows.	❌
`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 RoboflowClassificationModel.

inputs: AbsoluteStaticCrop, Crop, RelativeStaticCrop
outputs: DetectionFilter, DetectionOffset, ActiveLearningDataCollector

The available connections depend on its binding kinds. Check what binding kinds RoboflowClassificationModel has.

Bindings

input
- images (Batch[image]): Reference at image to be used as input for step processing.
- 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
- prediction_type (Batch[prediction_type]): String value with type of prediction.
- predictions (Batch[classification_prediction]): 'predictions' key from Roboflow classifier output.
- top (Batch[top_class]): Batch of string values representing top class predicted by classification model.
- confidence (float_zero_to_one): float value in range [0.0, 1.0].
- parent_id (Batch[parent_id]): Identifier of parent for step output.

Example JSON definition of RoboflowClassificationModel step

{
    "name": "<your_step_name_here>",
    "type": "RoboflowClassificationModel",
    "images": "$inputs.image",
    "model_id": "my_project/3",
    "confidence": 0.3,
    "disable_active_learning": true,
    "active_learning_target_dataset": "my_project"
}