diff --git a/modules/deeplearning/cloud_opd_srcnn_abi.py b/modules/deeplearning/cloud_opd_srcnn_abi.py
index 80d4dcd94c58bfbe5e133614a9e08fb14c71b5da..57e1801bf2223fc64ebcb7a2098c79dc7d4416d8 100644
--- a/modules/deeplearning/cloud_opd_srcnn_abi.py
+++ b/modules/deeplearning/cloud_opd_srcnn_abi.py
@@ -762,14 +762,15 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
 
     border = int((KERNEL_SIZE - 1) / 2)
     cld_opd_sres_out[border:(border+ylen), border:(border+xlen)] = cld_opd_sres[0, :, :, 0]
-    refl_out[0:(ylen+2*border), 0:(xlen+2*border)] = refl[0, :, :]
-    cld_opd_out[0:(ylen+2*border), 0:(xlen+2*border)] = cld_opd[0, :, :]
+    # refl_out[0:(ylen+2*border), 0:(xlen+2*border)] = refl[0, :, :]
+    # cld_opd_out[0:(ylen+2*border), 0:(xlen+2*border)] = cld_opd[0, :, :]
 
     # refl_out = denormalize(refl_out, 'refl_0_65um_nom', mean_std_dct)
     # cld_opd_out = denormalize(cld_opd_out, label_param, mean_std_dct)
 
     if out_file is not None:
-        np.save(out_file, (cld_opd_sres_out, refl_out, cld_opd_out, cld_opd_hres))
+        # np.save(out_file, (cld_opd_sres_out, refl_out, cld_opd_out, cld_opd_hres))
+        np.save(out_file, (cld_opd_sres_out, refl, cld_opd, cld_opd_hres))
     else:
         return cld_opd_sres_out, bt, refl