diff --git a/modules/deeplearning/cloud_opd_fcn_abi.py b/modules/deeplearning/cloud_opd_fcn_abi.py
index d4ce79a6fe7adaf019f3794eeb68055caae9005e..bc49fe6e5931ef39926847aa0f0b2dee9ad3719a 100644
--- a/modules/deeplearning/cloud_opd_fcn_abi.py
+++ b/modules/deeplearning/cloud_opd_fcn_abi.py
@@ -4,7 +4,8 @@ from deeplearning.cloud_fraction_fcn_abi import get_label_data_5cat
 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, scale, descale, get_grid_values_all, make_tf_callable_generator
+from util.util import EarlyStop, normalize, denormalize, scale, scale2, descale, \
+    get_grid_values_all, make_tf_callable_generator
 import glob
 import os, datetime
 import numpy as np
@@ -314,7 +315,8 @@ class SRCNN:
                 # tmp = normalize(tmp, 'refl_0_65um_nom', mean_std_dct)
                 tmp = scale(tmp, 'refl_0_65um_nom', mean_std_dct)
             else:
-                tmp = np.where(np.isnan(tmp), 0, tmp)
+                # tmp = np.where(np.isnan(tmp), 0, tmp)
+                tmp = scale2(tmp, 0.0, 20.0)
             data_norm.append(tmp)
 
         tmp = input_label[:, label_idx_i, :, :]
@@ -335,7 +337,8 @@ class SRCNN:
             cat_cf = get_label_data_5cat(cld_prob)
             self.test_cat_cf.append(cat_cf)
         label = get_cldy_frac_opd(cld_prob, label)
-        label = scale(label, label_param, mean_std_dct)
+        # label = scale(label, label_param, mean_std_dct)
+        label = np.where(np.isnan(label), 0, label)
 
         label = np.where(np.isnan(label), 0, label)
         label = np.expand_dims(label, axis=3)
@@ -680,8 +683,8 @@ class SRCNN:
 
         # labels = denormalize(labels, label_param, mean_std_dct)
         # preds = denormalize(preds, label_param, mean_std_dct)
-        labels = descale(labels, label_param, mean_std_dct)
-        preds = descale(preds, label_param, mean_std_dct)
+        # labels = descale(labels, label_param, mean_std_dct)
+        # preds = descale(preds, label_param, mean_std_dct)
 
         return labels, cat_cld_frac, preds, inputs