From 585c71d1a580b3394ffa25d489562139e8060b5d Mon Sep 17 00:00:00 2001
From: "Daniel.Frisinghelli" <daniel.frisinghelli@eurac.edu>
Date: Tue, 16 Feb 2021 15:30:28 +0100
Subject: [PATCH] Fixed a bug: Add classification report after computing
confusion matrix.
---
pysegcnn/core/trainer.py | 6 ++++--
1 file changed, 4 insertions(+), 2 deletions(-)
diff --git a/pysegcnn/core/trainer.py b/pysegcnn/core/trainer.py
index 39e677d..88e0fc6 100644
--- a/pysegcnn/core/trainer.py
+++ b/pysegcnn/core/trainer.py
@@ -2738,7 +2738,6 @@ class NetworkInference(BaseConfig):
# compute k-fold average estimate of each metric across all models
LOGGER.info('Calculating k-fold estimate of metrics ...')
report = df.groupby(df.index, sort=False).mean()
- inference['report'] = report
# labels to predict
labels = list(report.index.drop(['macro avg', 'weighted avg',
@@ -2749,7 +2748,7 @@ class NetworkInference(BaseConfig):
report_name = self.report_path.joinpath(self.report_name(kfold))
fig.savefig(report_name, dpi=300, bbox_inches='tight')
- # chech whether to compute the aggregated confusion matrix
+ # check whether to compute the aggregated confusion matrix
if self.cm:
# initialize the aggregated confusion matrix
cm_agg = np.zeros(shape=2 * (len(labels), ))
@@ -2765,4 +2764,7 @@ class NetworkInference(BaseConfig):
plot_confusion_matrix(cm_agg, labels, state_file=kfold,
outpath=self.perfmc_path)
+ # add aggregated classification report
+ inference['report'] = report
+
return inference
--
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