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- # !/usr/bin/env python
- # -*- coding: utf-8 -*-
- # ==============================================================================
- #
- # Copyright (c) 2019, NVIDIA CORPORATION. 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.
- #
- # ==============================================================================
- import tensorflow as tf
- __all__ = [
- "iou_score",
- ]
- def iou_score(y_pred, y_true, threshold, eps=1e-5):
- y_true = tf.cast(y_true > threshold, dtype=tf.float32)
- y_pred = tf.cast(y_pred > threshold, dtype=tf.float32)
- intersection = y_true * y_pred
- intersection = tf.reduce_sum(intersection, axis=(1, 2, 3))
- numerator = 2.0 * intersection + eps
- divisor = tf.reduce_sum(y_true, axis=(1, 2, 3)) + tf.reduce_sum(y_pred, axis=(1, 2, 3)) + eps
- return tf.reduce_mean(numerator / divisor)
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