Update app.py

app.py

@@ -25,28 +25,20 @@ def classify_audio(audio_file):
     id2label  = model.config.id2label
     
     sr, raw_wav = audio_file
-    
-    #y = raw_wav.astype(np.float32)
-    #y /= np.max(np.abs(y))
-
     y = raw_wav.astype(np.float32, order='C') / np.iinfo(raw_wav.dtype).max
 
-
-
     output = ''
     if sr != 16000:
         y = librosa.resample(y, orig_sr=sr, target_sr=model_sr)
         output += "{} sampling rate is uncompatible, converted to {} as the model was trained on {} sampling rate<br>".format(sr, model_sr, model_sr)
-    
 
     
     norm_wav = (y - mean) / (std+0.000001)
     mask = torch.ones(1, len(norm_wav))
     wavs = torch.tensor(norm_wav).unsqueeze(0)
-    
-    pred = model(wavs, mask).detach().numpy()
 
     
+    pred = model(wavs, mask).detach().numpy()
     for att_i, att_val in enumerate(pred[0]):
         output += "{}: \t{:0.4f}\n".format(id2label[att_i], att_val)