From e38255e6e7e506794ae6f70c91d48b2cf51dffbd Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Mon, 6 Jun 2022 09:41:10 -0500
Subject: [PATCH] minor...
---
modules/deeplearning/unet_l1b_l2.py | 47 +++++++++++------------------
1 file changed, 18 insertions(+), 29 deletions(-)
diff --git a/modules/deeplearning/unet_l1b_l2.py b/modules/deeplearning/unet_l1b_l2.py
index fc418e80..aaae7b8c 100644
--- a/modules/deeplearning/unet_l1b_l2.py
+++ b/modules/deeplearning/unet_l1b_l2.py
@@ -214,40 +214,29 @@ class UNET:
# print(e)
def get_in_mem_data_batch(self, idxs, is_training):
-
- dat_files = []
- lbl_files = []
-
if is_training:
- for k in idxs:
- f = self.train_data_files[k]
- nda = np.load(f)
- dat_files.append(nda)
-
- f = self.train_label_files[k]
- nda = np.load(f)
- lbl_files.append(nda)
-
- data = np.concatenate(dat_files)
- label = np.concatenate(lbl_files)
-
- label = label[:, label_idx, :, :]
- label = np.expand_dims(label, axis=3)
+ data_files = self.train_data_files
+ label_files = self.train_label_files
else:
- for k in idxs:
- f = self.test_data_files[k]
- nda = np.load(f)
- dat_files.append(nda)
+ data_files = self.test_data_files
+ label_files = self.test_label_files
+
+ data_s = []
+ label_s = []
+ for k in idxs:
+ f = data_files[k]
+ nda = np.load(f)
+ data_s.append(nda)
- f = self.test_label_files[k]
- nda = np.load(f)
- lbl_files.append(nda)
+ f = label_files[k]
+ nda = np.load(f)
+ label_s.append(nda)
- data = np.concatenate(dat_files)
- label = np.concatenate(lbl_files)
+ data = np.concatenate(data_s)
+ label = np.concatenate(label_s)
- label = label[:, label_idx, :, :]
- label = np.expand_dims(label, axis=3)
+ label = label[:, label_idx, :, :]
+ label = np.expand_dims(label, axis=3)
data = data.astype(np.float32)
label = label.astype(np.float32)
--
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