snapshot...

modules/deeplearning/srcnn_l1b_l2.py

@@ -212,8 +212,9 @@ class SRCNN:
             noise_scale = 0.005
 
         data_norm = []
-        for k, param in enumerate(params):
-            tmp = data[:, k, 3:131:2, 3:131:2]
+        for param in data_params:
+            idx = params.index(param)
+            tmp = data[:, idx, 3:131:2, 3:131:2]
             tmp = resample(y_64, x_64, tmp, s, t)
             tmp = normalize(tmp, param, mean_std_dct, add_noise=add_noise, noise_scale=noise_scale)
             data_norm.append(tmp)