From a48ebfbad65c014bbed7ff46a9caf835db9d0f60 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Tue, 27 Sep 2022 14:53:02 -0500
Subject: [PATCH] snapshot...
---
modules/deeplearning/srcnn_l1b_l2.py | 9 +++++++--
1 file changed, 7 insertions(+), 2 deletions(-)
diff --git a/modules/deeplearning/srcnn_l1b_l2.py b/modules/deeplearning/srcnn_l1b_l2.py
index 8dcebe73..402d88c8 100644
--- a/modules/deeplearning/srcnn_l1b_l2.py
+++ b/modules/deeplearning/srcnn_l1b_l2.py
@@ -13,7 +13,7 @@ import h5py
LOG_DEVICE_PLACEMENT = False
-PROC_BATCH_SIZE = 4
+PROC_BATCH_SIZE = 2
PROC_BATCH_BUFFER_SIZE = 50000
NumClasses = 2
@@ -180,7 +180,7 @@ class SRCNN:
self.test_data_nda = None
self.test_label_nda = None
- self.n_chans = len(data_params)
+ self.n_chans = len(data_params) + 1
self.X_img = tf.keras.Input(shape=(None, None, self.n_chans))
# self.X_img = tf.keras.Input(shape=(36, 36, self.n_chans))
@@ -217,6 +217,11 @@ class SRCNN:
tmp = resample(y_64, x_64, tmp, s, t)
tmp = normalize(tmp, param, mean_std_dct, add_noise=add_noise, noise_scale=noise_scale)
data_norm.append(tmp)
+ # --------
+ tmp = input_data[:, 2, 3:131, 3:131]
+ tmp = normalize(tmp, 'refl_0_65um_nom')
+ data_norm.append(tmp)
+ # ---------
data = np.stack(data_norm, axis=3)
data = data.astype(np.float32)
--
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