From cafa8d941b838363ada25dea231fc38570a734f3 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Mon, 16 May 2022 14:01:24 -0500
Subject: [PATCH] snapshot...
---
modules/deeplearning/unet.py | 22 +++++++++++-----------
1 file changed, 11 insertions(+), 11 deletions(-)
diff --git a/modules/deeplearning/unet.py b/modules/deeplearning/unet.py
index efe15ca3..16e44f6f 100644
--- a/modules/deeplearning/unet.py
+++ b/modules/deeplearning/unet.py
@@ -286,7 +286,7 @@ class UNET:
def get_in_mem_data_batch(self, idxs, is_training):
if is_training:
train_data = []
- label_data = []
+ train_label = []
for k in idxs:
f = self.train_data_files[k]
nda = np.load(f)
@@ -294,35 +294,35 @@ class UNET:
f = self.train_label_files[k]
nda = np.load(f)
- label_data.append(nda)
+ train_label.append(nda)
data = np.concatenate(train_data)
data = np.expand_dims(data, axis=3)
- label = np.concatenate(label_data)
+ label = np.concatenate(train_label)
label = np.expand_dims(label, axis=3)
else:
- train_data = []
- label_data = []
+ test_data = []
+ test_label = []
for k in idxs:
f = self.test_data_files[k]
nda = np.load(f)
- train_data.append(nda)
+ test_data.append(nda)
f = self.test_label_files[k]
nda = np.load(f)
- label_data.append(nda)
+ test_label.append(nda)
- data = np.concatenate(train_data)
+ data = np.concatenate(test_data)
data = np.expand_dims(data, axis=3)
- label = np.concatenate(label_data)
+ label = np.concatenate(test_label)
label = np.expand_dims(label, axis=3)
data = data.astype(np.float32)
label = label.astype(np.float32)
- normalize(data, 'M15', mean_std_dct)
- normalize(label, 'M15', mean_std_dct)
+ data = normalize(data, 'M15', mean_std_dct)
+ label = normalize(label, 'M15', mean_std_dct)
if is_training and DO_AUGMENT:
data_ud = np.flip(data, axis=1)
--
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