From ccac0beb7c3e8aa22d5631c2bd41f2f0dc496715 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Thu, 24 Aug 2023 14:13:07 -0500
Subject: [PATCH] snapshot...
---
modules/deeplearning/cloud_opd_fcn_abi.py | 17 +++--------------
1 file changed, 3 insertions(+), 14 deletions(-)
diff --git a/modules/deeplearning/cloud_opd_fcn_abi.py b/modules/deeplearning/cloud_opd_fcn_abi.py
index 9ac85b9f..9280e9b0 100644
--- a/modules/deeplearning/cloud_opd_fcn_abi.py
+++ b/modules/deeplearning/cloud_opd_fcn_abi.py
@@ -1,6 +1,7 @@
import tensorflow as tf
from util.plot_cm import confusion_matrix_values
+from util.augment import augment_image
from util.setup_cloud_fraction import logdir, modeldir, now, ancillary_path
from util.util import EarlyStop, normalize, denormalize, get_grid_values_all
import glob
@@ -502,23 +503,11 @@ class SRCNN:
self.initial_learning_rate = initial_learning_rate
def build_evaluation(self):
+ self.train_accuracy = tf.keras.metrics.MeanAbsoluteError(name='train_accuracy')
+ self.test_accuracy = tf.keras.metrics.MeanAbsoluteError(name='test_accuracy')
self.train_loss = tf.keras.metrics.Mean(name='train_loss')
self.test_loss = tf.keras.metrics.Mean(name='test_loss')
- if NumClasses == 2:
- self.train_accuracy = tf.keras.metrics.BinaryAccuracy(name='train_accuracy')
- self.test_accuracy = tf.keras.metrics.BinaryAccuracy(name='test_accuracy')
- self.test_auc = tf.keras.metrics.AUC(name='test_auc')
- self.test_recall = tf.keras.metrics.Recall(name='test_recall')
- self.test_precision = tf.keras.metrics.Precision(name='test_precision')
- self.test_true_neg = tf.keras.metrics.TrueNegatives(name='test_true_neg')
- self.test_true_pos = tf.keras.metrics.TruePositives(name='test_true_pos')
- self.test_false_neg = tf.keras.metrics.FalseNegatives(name='test_false_neg')
- self.test_false_pos = tf.keras.metrics.FalsePositives(name='test_false_pos')
- else:
- self.train_accuracy = tf.keras.metrics.SparseCategoricalAccuracy(name='train_accuracy')
- self.test_accuracy = tf.keras.metrics.SparseCategoricalAccuracy(name='test_accuracy')
-
@tf.function(input_signature=[tf.TensorSpec(None, tf.float32), tf.TensorSpec(None, tf.float32)])
def train_step(self, inputs, labels):
labels = tf.squeeze(labels, axis=[3])
--
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