comparison scripts/load_features.py @ 42:90f8a2ea6f6f branch-tests

notebook results and load_features minor edits

                 bounds = pd.read_csv(segmenter_file, header=None, delimiter=',').get_values()    
             music_idx = self.get_music_idx_from_bounds(bounds, sr=self.framessr2)
         return music_idx
     
     
-    def get_features(self, df, stop_sec=30.0, class_label='Country', precomp_melody=False):
+    def get_features(self, df, stop_sec=30.0, class_label='Country', precomp_melody=True):
         oplist = []
         mflist = []
         chlist = []
         pblist = []        
         clabels = []

             print 'file ' + str(i) + ' of ' + str(n_files)
             music_idx = self.get_music_idx_for_file(df['Speech'].iloc[i])
             if len(music_idx)==0:
                 # no music segments -> skip this file
                 continue
-            try:
+            if 1:
                 op, mfcc = self.get_op_mfcc_for_file(df['Melspec'].iloc[i], stop_sec=stop_sec)
                 ch = self.get_chroma_for_file(df['Chroma'].iloc[i], stop_sec=stop_sec)
                 pb = self.get_pb_for_file(df['Melodia'].iloc[i], precomp_melody=precomp_melody, stop_sec=stop_sec)
                 #if precomp_melody:
                 #    pb = self.load_precomputed_pb_from_melodia(df['Melodia'].iloc[i], stop_sec=stop_sec)
                 #else:
                 #    pb = self.get_pb_from_melodia(df['Melodia'].iloc[i], stop_sec=stop_sec)
-            except:
+            else:
                 continue
             n_stop = np.int(np.ceil(stop_sec * self.framessr2))
             print n_stop, len(op), len(mfcc), len(ch), len(pb)
             min_n_frames = np.min([n_stop, len(op), len(mfcc), len(ch), len(pb)])  # ideally, features should have the same number of frames
             if min_n_frames==0: