snapshot...

modules/deeplearning/cloud_fraction_fcn.py

@@ -728,8 +728,6 @@ class SRCNN:
         pred = self.model([data], training=False)
         self.test_probs = pred
         pred = pred.numpy()
-        if label_param != 'cloud_probability':
-            pred = denormalize(pred, label_param, mean_std_dct)
 
         return pred
 
@@ -758,7 +756,7 @@ class SRCNN:
         return self.restore(ckpt_dir)
 
     def run_evaluate(self, data, ckpt_dir):
-        data = tf.convert_to_tensor(data, dtype=tf.float32)
+        #data = tf.convert_to_tensor(data, dtype=tf.float32)
         self.num_data_samples = 80000
         self.build_model()
         self.build_training()