From 598460ec8118f171da209de195b0cbc1a1a01976 Mon Sep 17 00:00:00 2001
From: "Daniel.Frisinghelli" <daniel.frisinghelli@eurac.edu>
Date: Fri, 19 Feb 2021 16:49:56 +0100
Subject: [PATCH] Specify labels also for confusion matrix.
---
pysegcnn/core/trainer.py | 12 +++++++++---
1 file changed, 9 insertions(+), 3 deletions(-)
diff --git a/pysegcnn/core/trainer.py b/pysegcnn/core/trainer.py
index d0c2a57..792ebe2 100644
--- a/pysegcnn/core/trainer.py
+++ b/pysegcnn/core/trainer.py
@@ -2733,7 +2733,9 @@ class NetworkInference(BaseConfig):
# calculate confusion matrix
LOGGER.info('Computing confusion matrix ...')
- conf_mat = confusion_matrix(y_true, y_pred)
+ conf_mat = confusion_matrix(
+ y_true, y_pred,
+ labels=np.asarray(list(self.use_labels.keys())))
# add confusion matrix to model output
output['cm'] = conf_mat
@@ -2779,11 +2781,15 @@ class NetworkInference(BaseConfig):
# labels to predict: drop averages
try:
+ # check if for some scenes micro average is calculated rather
+ # than accuracy due to missing class labels
labels = list(report.index.drop(['macro avg', 'weighted avg',
- 'accuracy']))
+ 'micro_avg', 'accuracy']))
except KeyError:
+ # micro average is not calculated for any scene: each scene
+ # contains all the classes
labels = list(report.index.drop(['macro avg', 'weighted avg',
- 'micro avg']))
+ 'accuracy']))
# plot classification report
fig = plot_classification_report(report, labels)
--
GitLab