Gordon Böer gboeer
ilmonteux
/ segmentation_metrics.py
Last active
October 24, 2024 13:19
Semantic segmentation metrics in Keras and Numpy. IoU, Dice in both soft and hard variants. Mean metrics for multiclass prediction. See https://ilmonteux.github.io/2019/05/10/segmentation-metrics.html for discussion
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| import numpy as np | |
| import keras.backend as K | |
| import tensorflow as tf | |
| def metrics_np(y_true, y_pred, metric_name, metric_type='standard', drop_last = True, mean_per_class=False, verbose=False): | |
| """ | |
| Compute mean metrics of two segmentation masks, via numpy. | |
| IoU(A,B) = |A & B| / (| A U B|) | |
| Dice(A,B) = 2*|A & B| / (|A| + |B|) |