Updates

app.py

@@ -8,8 +8,8 @@ import torch
 import torchaudio
 
 # MODEL LOADING and INITIALISATION
-model = torch.jit.load("snorenetv1_small.ptl")
-model.eval()
+# model = torch.jit.load("snorenetv1_small.ptl")
+# model.eval()
 
 # Session state
 if 'text' not in st.session_state:
@@ -51,14 +51,14 @@ with st.expander('About this App'):
 
 wav_audio_data = st_audiorec()
 if wav_audio_data is not None:
-    np_wav = np.frombuffer(wav_audio_data, dtype=np.int16)
-    num_segments = len(np_wav)//100000
-    segments_list = []
-    for i in range(num_segments):
-        start_sample = i * 100000
-        end_sample = (i + 1) * 100000
-        segment = np_wav[start_sample:end_sample]
-        segments_list.append(segment)
+    # np_wav = np.frombuffer(wav_audio_data, dtype=np.int16)
+    # num_segments = len(np_wav)//100000
+    # segments_list = []
+    # for i in range(num_segments):
+    #     start_sample = i * 100000
+    #     end_sample = (i + 1) * 100000
+    #     segment = np_wav[start_sample:end_sample]
+    #     segments_list.append(segment)
     
     # wav_tensor = torch.tensor(np_wav, dtype=torch.float32)
     # segment_samples = int(44100 * 1)
@@ -69,7 +69,7 @@ if wav_audio_data is not None:
     #     end_sample = (i + 1) * segment_samples
     #     segment = wav_tensor[start_sample:end_sample]
     #     segments_list.append(segment)
-    st.write(segments_list)
+    st.write(type(wav_audio_data))
     # PERCENTAGE OF SNORING PLOT