Update app.py

app.py

@@ -33,26 +33,7 @@ script_choices = {
 tts = TTS("tts_models/multilingual/multi-dataset/bark", gpu=True)
 
 
-def split_process(audio, chosen_out_track):
-    gr.Info("Cleaning your audio sample...")
-    os.makedirs("out", exist_ok=True)
-    write('test.wav', audio[0], audio[1])
-    os.system("python3 -m demucs.separate -n mdx_extra_q -j 4 test.wav -o out")
-    # return "./out/mdx_extra_q/test/vocals.wav","./out/mdx_extra_q/test/bass.wav","./out/mdx_extra_q/test/drums.wav","./out/mdx_extra_q/test/other.wav"
-    if chosen_out_track == "vocals":
-        print("Audio sample cleaned")
-        return "./out/mdx_extra_q/test/vocals.wav"
-    elif chosen_out_track == "bass":
-        return "./out/mdx_extra_q/test/bass.wav"
-    elif chosen_out_track == "drums":
-        return "./out/mdx_extra_q/test/drums.wav"
-    elif chosen_out_track == "other":
-        return "./out/mdx_extra_q/test/other.wav"
-    elif chosen_out_track == "all-in":
-        return "test.wav"
-
-
-def infer(prompt, input_wav_file, clean_audio, hidden_numpy_audio, script_type):
+def infer(prompt, input_wav_file, script_type):
     print("""
 —————
 NEW INFERENCE:
@@ -60,21 +41,6 @@ NEW INFERENCE:
     """)
     if prompt == "":
         gr.Warning("Do not forget to provide a tts prompt !")
-
-    if clean_audio is True:
-        print("We want to clean audio sample")
-        new_name = os.path.splitext(os.path.basename(input_wav_file))[0]
-        if os.path.exists(os.path.join("bark_voices", f"{new_name}_cleaned")):
-            print("This file has already been cleaned")
-            check_name = os.path.join("bark_voices", f"{new_name}_cleaned")
-            source_path = os.path.join(check_name, f"{new_name}_cleaned.wav")
-        else:
-            source_path = split_process(hidden_numpy_audio, "vocals")
-
-            new_path = os.path.join(os.path.dirname(
-                source_path), f"{new_name}_cleaned.wav")
-            os.rename(source_path, new_path)
-            source_path = new_path
     else:
         source_path = input_wav_file
 
@@ -237,8 +203,7 @@ with gr.Blocks(css=css) as demo:
 
         submit_btn.click(
             fn=infer,
-            inputs=[script_text, micro_in,
-                    hidden_audio_numpy, script_type_dropdown],
+            inputs=[script_text, micro_in, script_type_dropdown],
             outputs=[cloned_out, video_out, npz_file, folder_path]
         )
 demo.queue(api_open=False, max_size=10).launch()