diff --git a/modules/deeplearning/cloud_fraction_fcn_abi.py b/modules/deeplearning/cloud_fraction_fcn_abi.py
index 02bdc61864f16dc5d415912f59ad923c3b20c2ce..717009d1aec0e5fee9b8c2147ed7d7c120edbf82 100644
--- a/modules/deeplearning/cloud_fraction_fcn_abi.py
+++ b/modules/deeplearning/cloud_fraction_fcn_abi.py
@@ -154,27 +154,31 @@ def get_min_max_std(grd_k):
     return lo, hi, std, avg
 
 
-def get_label_data(grd_k):
+def get_label_data_5cat(grd_k):
     grd_k = np.where(np.isnan(grd_k), 0, grd_k)
-    grd_k = np.where(grd_k < 0.50, 0, 1)
+    grd_k = np.where(grd_k < 0.5, 0, 1)
 
-    a = grd_k[:, 0::4, 0::4]
-    b = grd_k[:, 1::4, 0::4]
-    c = grd_k[:, 0::4, 1::4]
-    d = grd_k[:, 1::4, 1::4]
-    s = a + b + c + d
+    s = grd_k[:, 0::4, 0::4] + grd_k[:, 1::4, 0::4] + grd_k[:, 2::4, 0::4] + grd_k[:, 3::4, 0::4] + \
+        grd_k[:, 0::4, 1::4] + grd_k[:, 1::4, 1::4] + grd_k[:, 2::4, 1::4] + grd_k[:, 3::4, 1::4] + \
+        grd_k[:, 0::4, 2::4] + grd_k[:, 1::4, 2::4] + grd_k[:, 2::4, 2::4] + grd_k[:, 3::4, 2::4] + \
+        grd_k[:, 0::4, 3::4] + grd_k[:, 1::4, 3::4] + grd_k[:, 2::4, 3::4] + grd_k[:, 3::4, 3::4]
+
+    cat_0 = np.logical_and(s >= 0, s < 2)
+    cat_1 = np.logical_and(s >= 2, s < 6)
+    cat_2 = np.logical_and(s >= 6, s < 11)
+    cat_3 = np.logical_and(s >= 11, s < 15)
+    cat_4 = np.logical_and(s >= 15, s <= 16)
 
-    cat_0 = (s <= 1)
-    cat_1 = np.logical_and(s > 1, s < 15)
-    cat_2 = (s >= 15)
     s[cat_0] = 0
     s[cat_1] = 1
     s[cat_2] = 2
+    s[cat_3] = 3
+    s[cat_4] = 4
 
     return s
 
 
-def get_label_data_5cat(grd_k):
+def get_label_data(grd_k):
     grd_k = np.where(np.isnan(grd_k), 0, grd_k)
     grd_k = np.where(grd_k < 0.5, 0, 1)
 
@@ -183,17 +187,13 @@ def get_label_data_5cat(grd_k):
         grd_k[:, 0::4, 2::4] + grd_k[:, 1::4, 2::4] + grd_k[:, 2::4, 2::4] + grd_k[:, 3::4, 2::4] + \
         grd_k[:, 0::4, 3::4] + grd_k[:, 1::4, 3::4] + grd_k[:, 2::4, 3::4] + grd_k[:, 3::4, 3::4]
 
-    cat_0 = np.logical_and(s >= 0, s < 2)
-    cat_1 = np.logical_and(s >= 2, s < 6)
-    cat_2 = np.logical_and(s >= 6, s < 11)
-    cat_3 = np.logical_and(s >= 11, s < 15)
-    cat_4 = np.logical_and(s >= 15, s <= 16)
+    cat_0 = np.logical_and(s >= 0, s < 3)
+    cat_1 = np.logical_and(s >= 3, s < 14)
+    cat_2 = np.logical_and(s >= 14, s <= 16)
 
     s[cat_0] = 0
     s[cat_1] = 1
     s[cat_2] = 2
-    s[cat_3] = 3
-    s[cat_4] = 4
 
     return s