Multi-Label Classification Model¶

v2¶

Class: RoboflowMultiLabelClassificationModelBlockV2 (there are multiple versions of this block)

Source: inference.core.workflows.core_steps.models.roboflow.multi_label_classification.v2.RoboflowMultiLabelClassificationModelBlockV2

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-label 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_multi_label_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 Multi-Label Classification Model in version v2.

Input and Output Bindings¶

The available connections depend on its binding kinds. Check what binding kinds Multi-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 Multi-Label Classification Model in version v2

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/roboflow_multi_label_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: RoboflowMultiLabelClassificationModelBlockV1 (there are multiple versions of this block)

Source: inference.core.workflows.core_steps.models.roboflow.multi_label_classification.v1.RoboflowMultiLabelClassificationModelBlockV1

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-label 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_multi_label_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 Multi-Label Classification Model in version v1.

Input and Output Bindings¶

The available connections depend on its binding kinds. Check what binding kinds Multi-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 Multi-Label Classification Model in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/roboflow_multi_label_classification_model@v1",
    "images": "$inputs.image",
    "model_id": "my_project/3",
    "confidence": 0.3,
    "disable_active_learning": true,
    "active_learning_target_dataset": "my_project"
}