snapshot...

modules/deeplearning/srcnn_l1b_l2.py

@@ -708,7 +708,8 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
 
     nn = SRCNN()
     out_sr = nn.run_evaluate(data, ckpt_dir)
-    # out_sr = denormalize(out_sr, label_params[0], mean_std_dct)
+    if label_param != 'cloud_fraction':
+        out_sr = denormalize(out_sr, label_param, mean_std_dct)
     if out_file is not None:
         np.save(out_file, out_sr)
     else: