Update app.py

app.py

@@ -9,22 +9,18 @@ import tensorflow as tf
 model = tf.keras.models.load_model('TTM_model.h5')
 
 def config_audio(audio):
-    print('enter2')
     header = 'ChromaSTFT RMS SpectralCentroid SpectralBandwidth Rolloff ZeroCrossingRate'
     for i in range(1, 21):
         header += f' mfcc{i}'
     header += ' label'
     header = header.split()
-    print(1)
     file = open('predict_file.csv', 'w', newline='')
     with file:
         writer = csv.writer(file)
         writer.writerow(header)
-    print(2)
     #taalfile = audio
     #print('stored in taalfile')
     y, sr = librosa.load(audio, mono=True, duration=30)
-    print(3)
     rms = librosa.feature.rms(y=y)
     chroma = librosa.feature.chroma_stft(y=y, sr=sr)
     spec_centroid = librosa.feature.spectral_centroid(y=y, sr=sr)
@@ -47,11 +43,9 @@ def config_audio(audio):
     
 def predict_audio(Audio_Input):
     audio=Audio_Input.name
-    print('enter1')
     X_predict = config_audio(audio)
     taals = ['addhatrital','bhajani','dadra','deepchandi','ektal','jhaptal','rupak','trital']
     pred = model.predict(X_predict).flatten()
-    print('exit1')
     return {taals[i]: float(pred[i]) for i in range(8)},audio
     
 audio = gr.inputs.Audio(source="upload", optional=False)