From e852fdd940dcfea7ce62c3af97bea00da5e996c8 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Wed, 12 Apr 2023 12:39:55 -0500
Subject: [PATCH] snapshot...
---
modules/deeplearning/cloud_opd_srcnn_viirs.py | 28 +++++++++----------
1 file changed, 14 insertions(+), 14 deletions(-)
diff --git a/modules/deeplearning/cloud_opd_srcnn_viirs.py b/modules/deeplearning/cloud_opd_srcnn_viirs.py
index 1eebf7d6..5c85fb49 100644
--- a/modules/deeplearning/cloud_opd_srcnn_viirs.py
+++ b/modules/deeplearning/cloud_opd_srcnn_viirs.py
@@ -67,21 +67,21 @@ print('label_param: ', label_param)
KERNEL_SIZE = 3 # target size: (128, 128)
N_X = N_Y = 1
-LEX_X = LEN_Y = 128
+LEN_X = LEN_Y = 128
if KERNEL_SIZE == 3:
- slc_x = slice(3, N_X*128 + 5)
- slc_y = slice(3, N_Y*128 + 5)
- slc_x_2 = slice(1, int((N_X*128)/2) + 4)
- slc_y_2 = slice(1, int((N_Y*128)/2) + 4)
- x_2 = np.arange(int((N_X*128)/2) + 3)
- y_2 = np.arange(int((N_Y*128)/2) + 3)
- t = np.arange(0, int((N_X*128)/2) + 3, 0.5)
- s = np.arange(0, int((N_Y*128)/2) + 3, 0.5)
- x_k = slice(1, N_X*128 + 3)
- y_k = slice(1, N_Y*128 + 3)
- x_128 = slice(4, N_X*128 + 4)
- y_128 = slice(4, N_Y*128 + 4)
+ slc_x = slice(2, N_X*LEN_X + 4)
+ slc_y = slice(2, N_Y*LEN_Y + 4)
+ slc_x_2 = slice(1, N_X*LEN_X + 6, 2)
+ slc_y_2 = slice(1, N_Y*LEN_Y + 6, 2)
+ x_2 = np.arange(int((N_X*LEN_X)/2) + 3)
+ y_2 = np.arange(int((N_Y*LEN_Y)/2) + 3)
+ t = np.arange(0, int((N_X*LEN_X)/2) + 3, 0.5)
+ s = np.arange(0, int((N_Y*LEN_Y)/2) + 3, 0.5)
+ x_k = slice(1, N_X*LEN_X + 3)
+ y_k = slice(1, N_Y*LEN_Y + 3)
+ x_128 = slice(3, N_X*LEN_X + 3)
+ y_128 = slice(3, N_Y*LEN_Y + 3)
elif KERNEL_SIZE == 5:
slc_x = slice(3, 135)
slc_y = slice(3, 135)
@@ -317,7 +317,7 @@ class SRCNN:
tmp = normalize(tmp, param, mean_std_dct)
data_norm.append(tmp[:, slc_y, slc_x])
# ---------------------------------------------------
- tmp = input_data[:, label_idx, :, :]
+ tmp = input_label[:, label_idx_i, :, :]
tmp = np.where(np.isnan(tmp), 0, tmp)
tmp = upsample(tmp)
data_norm.append(tmp)
--
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