From 78120938e5819ea3bc605ecc589d6c417b64be24 Mon Sep 17 00:00:00 2001
From: "Daniel.Frisinghelli" <daniel.frisinghelli@eurac.edu>
Date: Wed, 17 Feb 2021 17:00:06 +0100
Subject: [PATCH] Save scenes as pdf.
---
pysegcnn/core/trainer.py | 27 +++++++++++++--------------
1 file changed, 13 insertions(+), 14 deletions(-)
diff --git a/pysegcnn/core/trainer.py b/pysegcnn/core/trainer.py
index beaa905..b64aa74 100644
--- a/pysegcnn/core/trainer.py
+++ b/pysegcnn/core/trainer.py
@@ -2566,11 +2566,7 @@ class NetworkInference(BaseConfig):
# filename for the plot of the current batch
batch_name = '_'.join([model.state_file.stem,
- '{}_{}.pt'.format(self.trg_ds.name, batch)])
-
- # check if the current batch name exceeds the Windows limit of
- # 255 characters
- batch_name = check_filename_length(batch_name)
+ '{}_{}.pdf'.format(self.trg_ds.name, batch)])
# calculate the accuracy of the prediction
progress += ', Accuracy: {:.2f}'.format(
@@ -2581,15 +2577,18 @@ class NetworkInference(BaseConfig):
if self.plot:
# plot inputs, ground truth and model predictions
- _ = plot_sample(inputs.clip(0, 1),
- self.bands,
- self.use_labels,
- y=labels,
- y_pred={model.__class__.__name__: prdctn},
- accuracy=True,
- state=batch_name,
- plot_path=self.scenes_path,
- **self.plot_kwargs)
+ fig = plot_sample(inputs.clip(0, 1),
+ self.bands,
+ self.use_labels,
+ y=labels,
+ y_pred={'Prediction': prdctn},
+ accuracy=True,
+ **self.plot_kwargs)
+
+ # save figure
+ fig.savefig(check_filename_length(
+ self.scenes_path.joinpath(batch_name)),
+ bbox_inches='tight')
return output
--
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