snapshot...

modules/deeplearning/cloud_opd_srcnn_viirs.py

@@ -66,24 +66,23 @@ print('data_params_full: ', data_params_full)
 print('label_param: ', label_param)
 
 KERNEL_SIZE = 3  # target size: (128, 128)
-N_X = N_Y = 1
 LEN_X = LEN_Y = 128
 
 if KERNEL_SIZE == 3:
-    slc_x_m = slice(1, int((N_X*LEN_X)/2) + 4)
-    slc_y_m = slice(1, int((N_Y*LEN_Y)/2) + 4)
-    slc_x = slice(3, N_X*LEN_X + 5)
-    slc_y = slice(3, N_Y*LEN_Y + 5)
-    slc_x_2 = slice(2, N_X*LEN_X + 7, 2)
-    slc_y_2 = slice(2, N_Y*LEN_Y + 7, 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(4, N_X*LEN_X + 4)
-    y_128 = slice(4, N_Y*LEN_Y + 4)
+    slc_x_m = slice(1, int(LEN_X/2) + 4)
+    slc_y_m = slice(1, int(LEN_Y/2) + 4)
+    slc_x = slice(3, LEN_X + 5)
+    slc_y = slice(3, LEN_Y + 5)
+    slc_x_2 = slice(2, LEN_X + 7, 2)
+    slc_y_2 = slice(2, LEN_Y + 7, 2)
+    x_2 = np.arange(int(LEN_X/2) + 3)
+    y_2 = np.arange(int(LEN_Y/2) + 3)
+    t = np.arange(0, int(LEN_X/2) + 3, 0.5)
+    s = np.arange(0, int(LEN_Y/2) + 3, 0.5)
+    x_k = slice(1, LEN_X + 3)
+    y_k = slice(1, LEN_Y + 3)
+    x_128 = slice(4, LEN_X + 4)
+    y_128 = slice(4, LEN_Y + 4)
 elif KERNEL_SIZE == 5:
     slc_x = slice(3, 135)
     slc_y = slice(3, 135)