From dc06a6eafa5efc43b10affc2d15bdba07c7d3358 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Tue, 9 May 2023 10:53:24 -0500
Subject: [PATCH] snapshot...
---
modules/deeplearning/cloud_fraction_fcn_abi.py | 14 +++++++++++---
1 file changed, 11 insertions(+), 3 deletions(-)
diff --git a/modules/deeplearning/cloud_fraction_fcn_abi.py b/modules/deeplearning/cloud_fraction_fcn_abi.py
index e990e5fa..683f2c2b 100644
--- a/modules/deeplearning/cloud_fraction_fcn_abi.py
+++ b/modules/deeplearning/cloud_fraction_fcn_abi.py
@@ -280,6 +280,7 @@ class SRCNN:
self.test_labels = []
self.test_preds = []
self.test_probs = None
+ self.test_input = []
self.learningRateSchedule = None
self.num_data_samples = None
@@ -590,6 +591,7 @@ class SRCNN:
self.test_labels.append(labels)
self.test_preds.append(pred.numpy())
+ self.test_input.append(inputs)
self.test_loss(t_loss)
self.test_accuracy(labels, pred)
@@ -732,9 +734,10 @@ class SRCNN:
labels = np.concatenate(self.test_labels)
preds = np.concatenate(self.test_preds)
+ inputs = np.concatenate(self.test_input)
print(labels.shape, preds.shape)
- return labels, preds
+ return labels, preds, inputs
def do_evaluate(self, inputs, ckpt_dir):
@@ -785,10 +788,15 @@ class SRCNN:
def run_restore_static(directory, ckpt_dir, out_file=None):
nn = SRCNN()
- labels, preds = nn.run_restore(directory, ckpt_dir)
+ labels, preds, inputs = nn.run_restore(directory, ckpt_dir)
if out_file is not None:
np.save(out_file,
- [np.squeeze(labels), preds.argmax(axis=3)])
+ [np.squeeze(labels), preds.argmax(axis=3),
+ denormalize(inputs[:, 1:65, 1:65, 0], 'temp_11_0um_nom', mean_std_dct),
+ denormalize(inputs[:, 1:65, 1:65, 1], 'refl_0_65um_nom', mean_std_dct),
+ denormalize(inputs[:, 1:65, 1:65, 2], 'refl_0_65um_nom', mean_std_dct),
+ inputs[:, 1:65, 1:65, 3],
+ inputs[:, 1:65, 1:65, 4]])
def run_evaluate_static(in_file, out_file, ckpt_dir):
--
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