big update

app.py

@@ -40,24 +40,10 @@ st.title('Real-Time Snore Detection App 😴')
 
 uploaded_file = st.file_uploader("Upload Sample", type=["wav"])
 if uploaded_file is not None:
-    st.write("Saving File.....")
     audio = pydub.AudioSegment.from_wav(uploaded_file)
-    audio.export(uploaded_file.name, format='wav')
-    time.sleep(2)
-    st.write("File Saved!")
-
-    
-
-    # PERCENTAGE OF SNORING PLOT
-
-    
-
-if st.button("Analyse"):
-    filename = uploaded_file.name
-    cwdir = os.getcwd()
-    file_path = os.path.join(cwdir, filename)
-    while(endReached==False):
-        sr, waveform = wavfile.read(uploaded_file.name)
+    audio_data = np.array(audio.get_array_of_samples())
+    waveform= audio_data
+    while(endReached == False):
         input_tensor = torch.tensor(waveform[s:n]).unsqueeze(0).to(torch.float32)
         result = model(input_tensor)
         if np.abs(result[0][0]) > np.abs(result[0][1]):
@@ -66,8 +52,9 @@ if st.button("Analyse"):
             snore += 1
         s += 16000
         n += 16000
-        if(n >= len(waveform)):
+        if(n>=len(waveform)):
             endReached = True
+
     total = snore + other
     snore_percentage = (snore / total) * 100
     other_percentage = (other / total) * 100
@@ -85,6 +72,12 @@ if st.button("Analyse"):
         plt.text(percentage, i, f' {percentage:.2f}%', va='center')
     st.write("DONE")
     st.pyplot(plt)
+    
+
+    # # PERCENTAGE OF SNORING PLOT
+
+    
+