Update app.py

app.py

@@ -4,7 +4,7 @@ import pandas as pd
 
 ## libraries for training dl models
 import tensorflow as tf
-from tensorflow import keras 
+
 
 ## libraries for reading audio files 
 import librosa as lib 
@@ -18,15 +18,15 @@ model = keras.models.load_model('heartbeatsound_classification.h5')
 
 def loading_sound_file(sound_file, sr=22050, duration=10):
     input_length = sr * duration
-    X, sr = librosa.load(sound_file, sr=sr, duration=duration) 
-    dur = librosa.get_duration(y=X, sr=sr)
+    X, sr = lib.load(sound_file, sr=sr, duration=duration) 
+    dur = lib.get_duration(y=X, sr=sr)
     
     # pad audio file same duration
     if (round(dur) < duration):
         print ("fixing audio lenght :", file_name)
-        y = librosa.util.fix_length(X, input_length) 
+        y = lib.util.fix_length(X, input_length) 
     # extract normalized mfcc feature from data
-    mfccs = np.mean(librosa.feature.mfcc(y=X, sr=sr, n_mfcc=25).T,axis=0)
+    mfccs = np.mean(lib.feature.mfcc(y=X, sr=sr, n_mfcc=25).T,axis=0)
 
     data = np.array(mfccs).reshape([-1,1])