From 11dd86e23f751d508440c8148b52e2475260b7ad Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Sat, 13 Aug 2022 10:47:00 -0500
Subject: [PATCH] test...
---
modules/deeplearning/espcn.py | 34 ++++++++++++++++++----------------
1 file changed, 18 insertions(+), 16 deletions(-)
diff --git a/modules/deeplearning/espcn.py b/modules/deeplearning/espcn.py
index 63e7e415..7257ea11 100644
--- a/modules/deeplearning/espcn.py
+++ b/modules/deeplearning/espcn.py
@@ -1,7 +1,7 @@
import glob
import tensorflow as tf
from util.setup import logdir, modeldir, cachepath, now, ancillary_path
-from util.util import EarlyStop, normalize, denormalize
+from util.util import EarlyStop, normalize, denormalize, resample
import os, datetime
import numpy as np
import pickle
@@ -59,6 +59,11 @@ data_idx, label_idx = 1, 1
data_param = data_params[data_idx]
label_param = label_params[label_idx]
+x_70 = np.arange(70)
+y_70 = np.arange(70)
+x_70_2 = x_70[3:67:2]
+y_70_2 = y_70[3:67:2]
+
def build_residual_conv2d_block(conv, num_filters, block_name, activation=tf.nn.leaky_relu, padding='SAME'):
@@ -194,18 +199,15 @@ class ESPCN:
data = np.concatenate(label_s)
label = np.concatenate(label_s)
- # label = label[:, label_idx, :, :]
- #label = label[:, label_idx, 3:67, 3:67]
- label = label[:, label_idx, 0:32, 0:32]
- label = np.expand_dims(label, axis=3)
- #label = tf.image.resize(label, (32, 32), method='nearest').numpy()
-
- # data = data[:, data_idx, :, :]
+ data = data[:, data_idx, :, :]
#data = data[:, data_idx, 3:67, 3:67]
- data = data[:, data_idx, 0:32, 0:32]
+ data = resample(x_70, y_70, data, x_70_2, y_70_2)
data = np.expand_dims(data, axis=3)
- #data = tf.image.resize(data, (32, 32), method='nearest').numpy()
- # data = tf.image.resize(data, (36, 36)).numpy()
+ # data = tf.image.resize(data, (32, 32)).numpy()
+
+ # label = label[:, label_idx, :, :]
+ label = label[:, label_idx, 3:67:2, 3:67:2]
+ label = np.expand_dims(label, axis=3)
data = data.astype(np.float32)
label = label.astype(np.float32)
@@ -357,11 +359,11 @@ class ESPCN:
conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_1')
- # conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_2')
- #
- # conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_3')
- #
- # conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_4')
+ conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_2')
+
+ conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_3')
+
+ conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_4')
conv_b = tf.keras.layers.Conv2D(num_filters, kernel_size=3, strides=1, padding=padding)(conv_b)
--
GitLab