def df2classifications(df):
"""Converts a pandas DataFrame to a
:class:`fiftyone.core.labels.Classifications` instance.
Args:
df: a pandas.DataFrame
Required columns:
LabelName - the label MID
Confidence - float [0, 1]
Optional Columns:
Source - 'freeform', 'verification', ...
Returns:
a :class:`fiftyone.core.labels.Classifications` instance
"""
supplemental_columns = [fn for fn in CLASSIFICATION_COLUMNS if fn in df]
return fol.Classifications(classifications=[
fol.Classification(
label=row.LabelName,
confidence=row.Confidence,
**{sc: row[sc]
for sc in supplemental_columns},
) for _, row in df.iterrows()
])
def _parse_label(self, target):
try:
label = self.classes[target]
except:
label = str(target)
return fol.Classification(label=label)
def _parse_label(self, features):
label = features["label"].numpy().decode()
return fol.Classification(label=label)