From 2af4fb2e05073f00b22777f7518bc2f3324ec9cd Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Sat, 11 Feb 2023 09:39:15 -0600
Subject: [PATCH] snapshot...
---
modules/deeplearning/cnn_cld_frac.py | 13 +++++++------
1 file changed, 7 insertions(+), 6 deletions(-)
diff --git a/modules/deeplearning/cnn_cld_frac.py b/modules/deeplearning/cnn_cld_frac.py
index 6c36a4d1..951d8c0b 100644
--- a/modules/deeplearning/cnn_cld_frac.py
+++ b/modules/deeplearning/cnn_cld_frac.py
@@ -763,11 +763,11 @@ class SRCNN:
preds = np.concatenate(self.test_preds)
print(labels.shape, preds.shape)
- if label_param != 'cloud_probability':
- labels_denorm = denormalize(labels, label_param, mean_std_dct)
- preds_denorm = denormalize(preds, label_param, mean_std_dct)
+ # if label_param != 'cloud_probability':
+ # labels_denorm = denormalize(labels, label_param, mean_std_dct)
+ # preds_denorm = denormalize(preds, label_param, mean_std_dct)
- return labels_denorm, preds_denorm
+ return labels, preds
def do_evaluate(self, data, ckpt_dir):
@@ -815,9 +815,10 @@ class SRCNN:
def run_restore_static(directory, ckpt_dir, out_file=None):
nn = SRCNN()
- labels_denorm, preds_denorm = nn.run_restore(directory, ckpt_dir)
+ labels, preds = nn.run_restore(directory, ckpt_dir)
if out_file is not None:
- np.save(out_file, [np.squeeze(labels_denorm), preds_denorm.argmax(axis=3)])
+ np.save(out_file,
+ [np.squeeze(labels), preds.argmax(axis=3), preds[:, :, :, 0], preds[:, :, :, 1], preds[:, :, :, 2]])
def run_evaluate_static(in_file, out_file, ckpt_dir):
--
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