From 4978b9b02fdc3aba4d8ceb0789345e18f6ff14f7 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Wed, 3 Aug 2022 13:30:51 -0500
Subject: [PATCH] snapshot...
---
modules/deeplearning/espcn.py | 20 +++++++++++++-------
1 file changed, 13 insertions(+), 7 deletions(-)
diff --git a/modules/deeplearning/espcn.py b/modules/deeplearning/espcn.py
index a09007e1..f665a5cf 100644
--- a/modules/deeplearning/espcn.py
+++ b/modules/deeplearning/espcn.py
@@ -210,12 +210,14 @@ class ESPCN:
self.n_chans = 1
- self.X_img = tf.keras.Input(shape=(None, None, self.n_chans))
+ #self.X_img = tf.keras.Input(shape=(None, None, self.n_chans))
# self.X_img = tf.keras.Input(shape=(36, 36, self.n_chans))
+ self.X_img = tf.keras.Input(shape=(32, 32, self.n_chans))
self.inputs.append(self.X_img)
- self.inputs.append(tf.keras.Input(shape=(None, None, self.n_chans)))
+ #self.inputs.append(tf.keras.Input(shape=(None, None, self.n_chans)))
# self.inputs.append(tf.keras.Input(shape=(36, 36, self.n_chans)))
+ self.inputs.append(tf.keras.Input(shape=(32, 32, self.n_chans)))
self.DISK_CACHE = False
@@ -420,20 +422,19 @@ class ESPCN:
print('input: ', input_2d.shape)
# conv = tf.keras.layers.Conv2D(num_filters, kernel_size=5, strides=1, padding='VALID', activation=None)(input_2d)
conv = input_2d
- print('Contracting Branch')
print('input: ', conv.shape)
skip = conv
if NOISE_TRAINING:
conv = tf.keras.layers.GaussianNoise(stddev=NOISE_STDDEV)(conv)
- conv = tf.keras.layers.Conv2D(num_filters, kernel_size=3, strides=1, padding=padding, activation=activation)(conv)
+ conv = tf.keras.layers.Conv2D(num_filters, kernel_size=5, strides=1, padding=padding, activation=activation)(conv)
conv = tf.keras.layers.BatchNormalization()(conv)
print(conv.shape)
- # conv = tf.keras.layers.Conv2D(num_filters, kernel_size=3, strides=1, padding=padding, activation=activation)(conv)
- # conv = tf.keras.layers.BatchNormalization()(conv)
- # print(conv.shape)
+ conv = tf.keras.layers.Conv2D(num_filters, kernel_size=3, strides=1, padding=padding, activation=activation)(conv)
+ conv = tf.keras.layers.BatchNormalization()(conv)
+ print(conv.shape)
conv = tf.keras.layers.Conv2D(num_filters, kernel_size=3, strides=1, padding=padding, activation=None)(conv)
conv = tf.keras.layers.BatchNormalization()(conv)
@@ -447,10 +448,15 @@ class ESPCN:
conv = tf.keras.layers.BatchNormalization()(conv)
print(conv.shape)
+ conv = tf.keras.layers.Conv2D(num_filters/2, kernel_size=3, strides=1, padding=padding, activation=activation)(conv)
+ conv = tf.keras.layers.BatchNormalization()(conv)
+ print(conv.shape)
+
conv = tf.keras.layers.Conv2D(4, kernel_size=3, strides=1, padding=padding, activation=activation)(conv)
print(conv.shape)
conv = tf.nn.depth_to_space(conv, block_size=2)
+ conv = tf.keras.layers.Activation(activation=activation)(conv)
print(conv.shape)
if NumClasses == 2:
--
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