DeepLearningExamples/TensorFlow/Segmentation/UNet_Industrial/utils/metrics.py

42 lines
1.3 KiB
Python

# !/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)