comparison scripts/load_features.py @ 46:3ed4c6af5a93 branch-tests

fixed indentation

             #min_dur_sec=8.0
             #min_n_frames = np.int(np.floor(min_dur_sec * self.framessr2))
             if len(music_idx)==0:  # or len(music_idx)<min_n_frames:
                 # no music segments or music segment too short -> skip this file
                 continue
-            if 1:
+            try:
                 # allow feature extraction of longer segments (2*stop_sec)
                 # because some of it might be speech segments that are filtered out
                 stop_sec_feat = 2 * stop_sec  
                 op, mfcc = self.get_op_mfcc_for_file(df['Melspec'].iloc[i], stop_sec=stop_sec_feat)
                 ch = self.get_chroma_for_file(df['Chroma'].iloc[i], stop_sec=stop_sec_feat)
                 pb = self.get_pb_for_file(df['Melodia'].iloc[i], precomp_melody=precomp_melody, stop_sec=stop_sec_feat)
                 #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)
-            else:
+            except:
                 continue
             n_stop = np.int(np.ceil(stop_sec * self.framessr2))
             print n_stop, len(op), len(mfcc), len(ch), len(pb)
             max_n_frames = np.min([n_stop, len(op), len(mfcc), len(ch), len(pb)])  # ideally, features should have the same number of frames
             if max_n_frames==0:

         root_SM = '/import/c4dm-04/mariap/FeatureCsvs/PB-melodia/'
         if 'SampleAudio' in base:
             root = root_SM
         else:
             root = root_BL
-        base = base.split('_')[-1].split('.csv')[0]+'_vamp_mtg-melodia_melodia_melody.csv'
+            base = base.split('_')[-1].split('.csv')[0]+'_vamp_mtg-melodia_melodia_melody.csv'
         bihist_file = os.path.join(root, base)
         if not os.path.exists(bihist_file):
             return pbihist
         print 'load precomputed pitch bihist', root
         pbihist = np.loadtxt(bihist_file, delimiter=',').T