From e54600f59212b07c6613515e0137fdcc254c20ef Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Tue, 13 Jun 2023 14:43:41 -0500
Subject: [PATCH] snapshot...
---
modules/deeplearning/cloud_opd_srcnn_abi.py | 12 ++++++------
1 file changed, 6 insertions(+), 6 deletions(-)
diff --git a/modules/deeplearning/cloud_opd_srcnn_abi.py b/modules/deeplearning/cloud_opd_srcnn_abi.py
index 1a7d51b0..a052109e 100644
--- a/modules/deeplearning/cloud_opd_srcnn_abi.py
+++ b/modules/deeplearning/cloud_opd_srcnn_abi.py
@@ -299,8 +299,8 @@ class SRCNN:
# -----------------------------------------------------
# -----------------------------------------------------
label = input_label[:, label_idx_i, ::2, ::2]
- # label = normalize(label, label_param, mean_std_dct)
- label = scale(label, label_param, mean_std_dct)
+ label = normalize(label, label_param, mean_std_dct)
+ # label = scale(label, label_param, mean_std_dct)
label = label[:, self.y_128, self.x_128]
label = np.where(np.isnan(label), 0, label)
@@ -415,13 +415,13 @@ class SRCNN:
conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_2', kernel_size=KERNEL_SIZE, scale=scale)
- conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_3', kernel_size=KERNEL_SIZE, scale=scale)
+ #conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_3', kernel_size=KERNEL_SIZE, scale=scale)
- conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_4', kernel_size=KERNEL_SIZE, scale=scale)
+ #conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_4', kernel_size=KERNEL_SIZE, scale=scale)
- conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_5', kernel_size=KERNEL_SIZE, scale=scale)
+ #conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_5', kernel_size=KERNEL_SIZE, scale=scale)
- conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_6', kernel_size=KERNEL_SIZE, scale=scale)
+ #conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_6', kernel_size=KERNEL_SIZE, scale=scale)
conv_b = tf.keras.layers.Conv2D(num_filters, kernel_size=3, strides=1, activation=activation, kernel_initializer='he_uniform', padding=padding)(conv_b)
--
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