Multi-Label Classification Model¶
Version v1
¶
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@v1
to add the block as
as step in your workflow.
Properties¶
Name | Type | Description | Refs |
---|---|---|---|
name |
str |
The unique name of 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 Multi-Label Classification Model
in version v1
.
- inputs:
Label Visualization
,Crop Visualization
,Mask Visualization
,Blur Visualization
,Image Contours
,Bounding Box Visualization
,Image Convert Grayscale
,Camera Focus
,Dot Visualization
,Color Visualization
,Corner Visualization
,Circle Visualization
,Perspective Correction
,Image Slicer
,Triangle Visualization
,Relative Static Crop
,Absolute Static Crop
,Halo Visualization
,Background Color Visualization
,SIFT
,Pixelate Visualization
,Polygon Visualization
,Dynamic Crop
,Image Blur
,Ellipse Visualization
,Image Threshold
- outputs:
Property Definition
,Roboflow Dataset Upload
,Roboflow Dataset Upload
,Roboflow Custom Metadata
,Detections Classes Replacement
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
): 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
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"
}