Update app.py

app.py

@@ -113,8 +113,16 @@ class App:
         with gr.Accordion("Speaker diarization", open=False, visible=True):
             cb_diarize = gr.Checkbox(value=diarization_params["is_diarize"],label="Use diarization",interactive=True)
             tb_hf_token = gr.Text(label="Token", value=diarization_params["hf_token"],info="An access token is required to use diarization & can be created [here](https://hf.co/settings/tokens). If not done yet for your account, you need to accept the terms & conditions of [diarization](https://huggingface.co/pyannote/speaker-diarization-3.1) & [segmentation](https://huggingface.co/pyannote/segmentation-3.0)")
+
+        with gr.Accordion("Advanced audio options", open=False, visible=True):
+            cb_bgm_separation = gr.Checkbox(label="Enable Background Music Remover Filter", value=uvr_params["is_separate_bgm"],
+                                            interactive=True,
+                                            info="Enable to remove background music before transcribing")
+            cb_vad_filter = gr.Checkbox(label="Enable Silero VAD Filter", value=vad_params["vad_filter"],
+                            interactive=True,
+                            info="Enable to transcribe only detected voice parts")
         
-        with gr.Accordion("Advanced options", open=False, visible=True):
+        with gr.Accordion("Advanced options", open=False, visible=False):
             with gr.Accordion("Advanced diarization options", open=False, visible=True):    
                 dd_diarization_device = gr.Dropdown(label="Device",
                                                     choices=self.whisper_inf.diarizer.get_available_device(),
@@ -192,10 +200,9 @@ class App:
                     nb_batch_size = gr.Number(label="Batch Size", value=whisper_params["batch_size"], precision=0)
     
             with gr.Accordion("Background Music Remover Filter", open=False):
-                cb_bgm_separation = gr.Checkbox(label="Enable Background Music Remover Filter", value=uvr_params["is_separate_bgm"],
-                                                interactive=True,
-                                                info="Enabling this will remove background music by submodel before"
-                                                     " transcribing ")
+#                cb_bgm_separation = gr.Checkbox(label="Enable Background Music Remover Filter", value=uvr_params["is_separate_bgm"],
+#                                                interactive=True,
+#                                                info="Enabling this will remove background music by submodel before transcribing.")
                 dd_uvr_device = gr.Dropdown(label="Device", value=self.whisper_inf.music_separator.device,
                                             choices=self.whisper_inf.music_separator.available_devices)
                 dd_uvr_model_size = gr.Dropdown(label="Model", value=uvr_params["model_size"],
@@ -206,9 +213,9 @@ class App:
                                                     value=uvr_params["enable_offload"])
     
             with gr.Accordion("Voice Detection Filter", open=False):
-                cb_vad_filter = gr.Checkbox(label="Enable Silero VAD Filter", value=vad_params["vad_filter"],
-                                            interactive=True,
-                                            info="Enable this to transcribe only detected voice parts by submodel.")
+#                cb_vad_filter = gr.Checkbox(label="Enable Silero VAD Filter", value=vad_params["vad_filter"],
+#                                            interactive=True,
+#                                            info="Enable this to transcribe only detected voice parts by submodel.")
                 sd_threshold = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label="Speech Threshold",
                                          value=vad_params["threshold"],
                                          info="Lower it to be more sensitive to small sounds.")