You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
29 lines
1.0 KiB
29 lines
1.0 KiB
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
from typing import List
|
|
|
|
import numpy as np
|
|
from sklearn.metrics import roc_curve
|
|
|
|
|
|
def compute_eer(labels: np.ndarray, scores: np.ndarray) -> List[float]:
|
|
'''
|
|
Compute EER and return score threshold.
|
|
'''
|
|
fpr, tpr, threshold = roc_curve(y_true=labels, y_score=scores)
|
|
fnr = 1 - tpr
|
|
eer_threshold = threshold[np.nanargmin(np.absolute((fnr - fpr)))]
|
|
eer = fpr[np.nanargmin(np.absolute((fnr - fpr)))]
|
|
return eer, eer_threshold
|