Update app.py
Browse files
app.py
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@@ -97,7 +97,7 @@ def wipe_npz_file(folder_path):
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print("YO")
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def split_process(audio, chosen_out_track):
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gr.Info("Cleaning your audio sample")
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os.makedirs("out", exist_ok=True)
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write('test.wav', audio[0], audio[1])
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os.system("python3 -m demucs.separate -n mdx_extra_q -j 4 test.wav -o out")
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@@ -123,7 +123,11 @@ def update_selection(selected_state: gr.SelectData):
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def infer(prompt, input_wav_file, clean_audio, hidden_numpy_audio):
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if clean_audio is True :
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print("We want to clean audio sample")
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# Extract the file name without the extension
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@@ -184,12 +188,17 @@ def infer(prompt, input_wav_file, clean_audio, hidden_numpy_audio):
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# Print the contents
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for item in contents:
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print(item)
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tts_video = gr.make_waveform(audio="output.wav")
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print("FINISHED")
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return "output.wav", tts_video, gr.update(value=f"bark_voices/{file_name}/{contents[1]}", visible=True), gr.Group.update(visible=True), destination_path
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def infer_from_c(prompt, c_name):
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print(f"USING VOICE LIBRARY: {c_name}")
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# Split the text into sentences based on common punctuation marks
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sentences = re.split(r'(?<=[.!?])\s+', prompt)
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@@ -200,11 +209,13 @@ def infer_from_c(prompt, c_name):
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# Join the selected sentences back into a single string
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limited_prompt = ' '.join(first_nb_sentences)
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tts.tts_to_file(text=limited_prompt,
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file_path="output.wav",
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voice_dir="examples/library/",
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speaker=f"{c_name}")
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tts_video = gr.make_waveform(audio="output.wav")
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print("FINISHED")
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return "output.wav", tts_video, gr.update(value=f"examples/library/{c_name}/{c_name}.npz", visible=True), gr.Group.update(visible=True)
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print("YO")
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def split_process(audio, chosen_out_track):
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gr.Info("Cleaning your audio sample...")
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os.makedirs("out", exist_ok=True)
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write('test.wav', audio[0], audio[1])
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os.system("python3 -m demucs.separate -n mdx_extra_q -j 4 test.wav -o out")
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def infer(prompt, input_wav_file, clean_audio, hidden_numpy_audio):
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print"""
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βββββ
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NEW INFERENCE:
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βββββββ
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"""
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if clean_audio is True :
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print("We want to clean audio sample")
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# Extract the file name without the extension
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# Print the contents
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for item in contents:
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print(item)
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gr.Info("Preparing final waveform video ...")
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tts_video = gr.make_waveform(audio="output.wav")
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print("FINISHED")
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return "output.wav", tts_video, gr.update(value=f"bark_voices/{file_name}/{contents[1]}", visible=True), gr.Group.update(visible=True), destination_path
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def infer_from_c(prompt, c_name):
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print"""
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βββββ
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NEW INFERENCE:
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βββββββ
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"""
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print(f"USING VOICE LIBRARY: {c_name}")
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# Split the text into sentences based on common punctuation marks
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sentences = re.split(r'(?<=[.!?])\s+', prompt)
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# Join the selected sentences back into a single string
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limited_prompt = ' '.join(first_nb_sentences)
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gr.Info(f"Generating audio from prompt with {c_name} ;)")
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tts.tts_to_file(text=limited_prompt,
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file_path="output.wav",
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voice_dir="examples/library/",
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speaker=f"{c_name}")
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gr.Info("Preparing final waveform video ...")
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tts_video = gr.make_waveform(audio="output.wav")
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print("FINISHED")
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return "output.wav", tts_video, gr.update(value=f"examples/library/{c_name}/{c_name}.npz", visible=True), gr.Group.update(visible=True)
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