add_prediction
code_loader.leap_binder.add_prediction
The purpose of the
leap_binder.add_prediction function is to describe the prediction(s) tensors for visualization and analysis purposes. This function adds a prediction type, which later can be assigned to the model graph prediction node(s).code_loader.leap_binder.add_prediction(
name=str,
labels=List[str]
)
Args | Text |
|---|---|
name | (str) with the given name of the input, e.g. image |
labels | (List[str]) an array containing the labels associated with this prediction |
from code_loader.contract.enums import Metric
...
LABELS = ['0','1','2','3','4','5','6','7','8','9']
leap_binder.add_prediction(
name='predicted_digit',
labels=LABELS
)
Full examples can be found at the Dataset Integration section of the following guides:
Last modified 11d ago