From 0eec8d81f1fb17fc63c7eb96213f146423a7bc94 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Tue, 5 Apr 2022 14:18:20 -0500
Subject: [PATCH] snapshot...
---
modules/deeplearning/unet.py | 4 ++++
1 file changed, 4 insertions(+)
diff --git a/modules/deeplearning/unet.py b/modules/deeplearning/unet.py
index e16946ef..27fcc7bd 100644
--- a/modules/deeplearning/unet.py
+++ b/modules/deeplearning/unet.py
@@ -610,22 +610,26 @@ class UNET:
conv = tf.keras.layers.concatenate([conv, conv_4])
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)
num_filters /= 2
conv = tf.keras.layers.Conv2DTranspose(num_filters, kernel_size=3, strides=2, padding=padding)(conv)
conv = tf.keras.layers.concatenate([conv, conv_3])
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)
num_filters /= 2
conv = tf.keras.layers.Conv2DTranspose(num_filters, kernel_size=3, strides=2, padding=padding)(conv)
conv = tf.keras.layers.concatenate([conv, conv_2])
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)
num_filters /= 2
conv = tf.keras.layers.Conv2DTranspose(num_filters, kernel_size=3, strides=2, padding=padding)(conv)
conv = tf.keras.layers.concatenate([conv, conv_1])
+ print(conv.shape)
if NumClasses == 2:
activation = tf.nn.sigmoid # For binary
--
GitLab