added data normalization to prevent libSVM sparse format to crash

bob/pad/base/algorithm/SVM.py

@@ -277,6 +277,13 @@ class SVM(Algorithm):
 
             machine = trainer.train(data)  # train the machine
 
+
+            # TODO: find a proper way to handle this - Guillaume HEUSCH, 08-08-2018             
+            if machine.shape[0] != data[0].shape[1]:               
+              data[0] += 1              
+              data[1] += 1               
+              machine = trainer.train(data)  # train the machine
+
             precision_cv = self.comp_prediction_precision(
                 machine, np.copy(real_cv), np.copy(attack_cv))
 
@@ -370,6 +377,12 @@ class SVM(Algorithm):
 
         machine = trainer.train(data)  # train the machine
 
+        # TODO: find a proper way to handle this - Guillaume HEUSCH, 08-08-2018             
+        if machine.shape[0] != data[0].shape[1]:               
+          data[0] += 1              
+          data[1] += 1               
+          machine = trainer.train(data)  # train the machine
+
         if mean_std_norm_flag:
             machine.input_subtract = features_mean  # subtract the mean of train data
             machine.input_divide = features_std  # divide by std of train data