snapshot..

modules/deeplearning/srcnn_l1b_l2.py

@@ -29,8 +29,8 @@ NUM_EPOCHS = 60
 TRACK_MOVING_AVERAGE = False
 EARLY_STOP = True
 
-NOISE_TRAINING = False
-NOISE_STDDEV = 0.001
+NOISE_TRAINING = True
+NOISE_STDDEV = 0.01
 DO_AUGMENT = True
 
 DO_ZERO_OUT = False
@@ -51,8 +51,8 @@ mean_std_dct.update(mean_std_dct_l1b)
 mean_std_dct.update(mean_std_dct_l2)
 
 # label_param = 'cloud_fraction'
-# label_param = 'cld_opd_dcomp'
-label_param = 'cloud_probability'
+label_param = 'cld_opd_dcomp'
+# label_param = 'cloud_probability'
 
 params = ['temp_11_0um_nom', 'temp_12_0um_nom', 'refl_0_65um_nom', label_param]
 data_params = ['temp_11_0um_nom']
@@ -408,7 +408,7 @@ class SRCNN:
         activation = tf.nn.relu
         momentum = 0.99
 
-        num_filters = 32
+        num_filters = 64
 
         input_2d = self.inputs[0]
         print('input: ', input_2d.shape)