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| import gradio as gr | |
| import styletts2importable | |
| import ljspeechimportable | |
| import torch | |
| import os | |
| from tortoise.utils.text import split_and_recombine_text | |
| import numpy as np | |
| import pickle | |
| theme = gr.themes.Base( | |
| font=[gr.themes.GoogleFont('Libre Franklin'), gr.themes.GoogleFont('Public Sans'), 'system-ui', 'sans-serif'], | |
| ) | |
| voicelist = ['f-us-1', 'f-us-2', 'f-us-3', 'f-us-4', 'm-us-1', 'm-us-2', 'm-us-3', 'm-us-4'] | |
| voices = {} | |
| import phonemizer | |
| global_phonemizer = phonemizer.backend.EspeakBackend(language='en-us', preserve_punctuation=True, with_stress=True) | |
| # todo: cache computed style, load using pickle | |
| # if os.path.exists('voices.pkl'): | |
| # with open('voices.pkl', 'rb') as f: | |
| # voices = pickle.load(f) | |
| # else: | |
| for v in voicelist: | |
| voices[v] = styletts2importable.compute_style(f'voices/{v}.wav') | |
| # def synthesize(text, voice, multispeakersteps): | |
| # if text.strip() == "": | |
| # raise gr.Error("You must enter some text") | |
| # # if len(global_phonemizer.phonemize([text])) > 300: | |
| # if len(text) > 300: | |
| # raise gr.Error("Text must be under 300 characters") | |
| # v = voice.lower() | |
| # # return (24000, styletts2importable.inference(text, voices[v], alpha=0.3, beta=0.7, diffusion_steps=7, embedding_scale=1)) | |
| # return (24000, styletts2importable.inference(text, voices[v], alpha=0.3, beta=0.7, diffusion_steps=multispeakersteps, embedding_scale=1)) | |
| def synthesize(text, voice, lngsteps, password, progress=gr.Progress()): | |
| if text.strip() == "": | |
| raise gr.Error("You must enter some text") | |
| if len(text) > 7500: | |
| raise gr.Error("Text must be <7.5k characters") | |
| texts = split_and_recombine_text(text) | |
| v = voice.lower() | |
| audios = [] | |
| for t in progress.tqdm(texts): | |
| audios.append(styletts2importable.inference(t, voices[v], alpha=0.3, beta=0.7, diffusion_steps=lngsteps, embedding_scale=1)) | |
| return (24000, np.concatenate(audios)) | |
| # def longsynthesize(text, voice, lngsteps, password, progress=gr.Progress()): | |
| # if password == os.environ['ACCESS_CODE']: | |
| # if text.strip() == "": | |
| # raise gr.Error("You must enter some text") | |
| # if lngsteps > 25: | |
| # raise gr.Error("Max 25 steps") | |
| # if lngsteps < 5: | |
| # raise gr.Error("Min 5 steps") | |
| # texts = split_and_recombine_text(text) | |
| # v = voice.lower() | |
| # audios = [] | |
| # for t in progress.tqdm(texts): | |
| # audios.append(styletts2importable.inference(t, voices[v], alpha=0.3, beta=0.7, diffusion_steps=lngsteps, embedding_scale=1)) | |
| # return (24000, np.concatenate(audios)) | |
| # else: | |
| # raise gr.Error('Wrong access code') | |
| def clsynthesize(text, voice, vcsteps, progress=gr.Progress()): | |
| # if text.strip() == "": | |
| # raise gr.Error("You must enter some text") | |
| # # if global_phonemizer.phonemize([text]) > 300: | |
| # if len(text) > 400: | |
| # raise gr.Error("Text must be under 400 characters") | |
| # # return (24000, styletts2importable.inference(text, styletts2importable.compute_style(voice), alpha=0.3, beta=0.7, diffusion_steps=20, embedding_scale=1)) | |
| # return (24000, styletts2importable.inference(text, styletts2importable.compute_style(voice), alpha=0.3, beta=0.7, diffusion_steps=vcsteps, embedding_scale=1)) | |
| if text.strip() == "": | |
| raise gr.Error("You must enter some text") | |
| if len(text) > 7500: | |
| raise gr.Error("Text must be <7.5k characters") | |
| texts = split_and_recombine_text(text) | |
| audios = [] | |
| for t in progress.tqdm(texts): | |
| audios.append(styletts2importable.inference(t, styletts2importable.compute_style(voice), alpha=0.3, beta=0.7, diffusion_steps=vcsteps, embedding_scale=1)) | |
| return (24000, np.concatenate(audios)) | |
| def ljsynthesize(text, steps, progress=gr.Progress()): | |
| # if text.strip() == "": | |
| # raise gr.Error("You must enter some text") | |
| # # if global_phonemizer.phonemize([text]) > 300: | |
| # if len(text) > 400: | |
| # raise gr.Error("Text must be under 400 characters") | |
| noise = torch.randn(1,1,256).to('cuda' if torch.cuda.is_available() else 'cpu') | |
| # return (24000, ljspeechimportable.inference(text, noise, diffusion_steps=7, embedding_scale=1)) | |
| if text.strip() == "": | |
| raise gr.Error("You must enter some text") | |
| if len(text) > 7500: | |
| raise gr.Error("Text must be <7.5k characters") | |
| texts = split_and_recombine_text(text) | |
| audios = [] | |
| for t in progress.tqdm(texts): | |
| audios.append(ljspeechimportable.inference(t, noise, diffusion_steps=steps, embedding_scale=1)) | |
| return (24000, np.concatenate(audios)) | |
| with gr.Blocks() as vctk: # just realized it isn't vctk but libritts but i'm too lazy to change it rn | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| inp = gr.Textbox(label="Text", info="What would you like StyleTTS 2 to read? It works better on full sentences.", interactive=True) | |
| voice = gr.Dropdown(voicelist, label="Voice", info="Select a default voice.", value='m-us-2', interactive=True) | |
| multispeakersteps = gr.Slider(minimum=3, maximum=15, value=7, step=1, label="Diffusion Steps", info="Theoretically, higher should be better quality but slower, but we cannot notice a difference. Try with lower steps first - it is faster", interactive=True) | |
| # use_gruut = gr.Checkbox(label="Use alternate phonemizer (Gruut) - Experimental") | |
| with gr.Column(scale=1): | |
| btn = gr.Button("Synthesize", variant="primary") | |
| audio = gr.Audio(interactive=False, label="Synthesized Audio") | |
| btn.click(synthesize, inputs=[inp, voice, multispeakersteps], outputs=[audio], concurrency_limit=4) | |
| with gr.Blocks() as clone: | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| clinp = gr.Textbox(label="Text", info="What would you like StyleTTS 2 to read? It works better on full sentences.", interactive=True) | |
| clvoice = gr.Audio(label="Voice", interactive=True, type='filepath', max_length=300) | |
| vcsteps = gr.Slider(minimum=3, maximum=20, value=20, step=1, label="Diffusion Steps", info="Theoretically, higher should be better quality but slower, but we cannot notice a difference. Try with lower steps first - it is faster", interactive=True) | |
| with gr.Column(scale=1): | |
| clbtn = gr.Button("Synthesize", variant="primary") | |
| claudio = gr.Audio(interactive=False, label="Synthesized Audio") | |
| clbtn.click(clsynthesize, inputs=[clinp, clvoice, vcsteps], outputs=[claudio], concurrency_limit=4) | |
| # with gr.Blocks() as longText: | |
| # with gr.Row(): | |
| # with gr.Column(scale=1): | |
| # lnginp = gr.Textbox(label="Text", info="What would you like StyleTTS 2 to read? It works better on full sentences.", interactive=True) | |
| # lngvoice = gr.Dropdown(voicelist, label="Voice", info="Select a default voice.", value='m-us-1', interactive=True) | |
| # lngsteps = gr.Slider(minimum=5, maximum=25, value=10, step=1, label="Diffusion Steps", info="Higher = better quality, but slower", interactive=True) | |
| # lngpwd = gr.Textbox(label="Access code", info="This feature is in beta. You need an access code to use it as it uses more resources and we would like to prevent abuse") | |
| # with gr.Column(scale=1): | |
| # lngbtn = gr.Button("Synthesize", variant="primary") | |
| # lngaudio = gr.Audio(interactive=False, label="Synthesized Audio") | |
| # lngbtn.click(longsynthesize, inputs=[lnginp, lngvoice, lngsteps, lngpwd], outputs=[lngaudio], concurrency_limit=4) | |
| with gr.Blocks() as lj: | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| ljinp = gr.Textbox(label="Text", info="What would you like StyleTTS 2 to read? It works better on full sentences.", interactive=True) | |
| ljsteps = gr.Slider(minimum=3, maximum=20, value=3, step=1, label="Diffusion Steps", info="Theoretically, higher should be better quality but slower, but we cannot notice a difference. Try with lower steps first - it is faster", interactive=True) | |
| with gr.Column(scale=1): | |
| ljbtn = gr.Button("Synthesize", variant="primary") | |
| ljaudio = gr.Audio(interactive=False, label="Synthesized Audio") | |
| ljbtn.click(ljsynthesize, inputs=[ljinp, ljsteps], outputs=[ljaudio], concurrency_limit=4) | |
| with gr.Blocks(title="StyleTTS 2", css="footer{display:none !important}", theme=theme) as demo: | |
| gr.Markdown("""# Nice TTS ❃ | |
| Enjoy that """) | |
| gr.HTML("""<script async src="https://www.googletagmanager.com/gtag/js?id=G-KP5GWL8NN5"></script> | |
| <script> | |
| window.dataLayer = window.dataLayer || []; | |
| function gtag(){dataLayer.push(arguments);} | |
| gtag('js', new Date()); | |
| gtag('config', 'G-KP5GWL8NN5'); | |
| </script> | |
| <script type="text/javascript"> | |
| (function(c,l,a,r,i,t,y){ | |
| c[a]=c[a]||function(){(c[a].q=c[a].q||[]).push(arguments)}; | |
| t=l.createElement(r);t.async=1;t.src="https://www.clarity.ms/tag/"+i; | |
| y=l.getElementsByTagName(r)[0];y.parentNode.insertBefore(t,y); | |
| })(window, document, "clarity", "script", "jydi4lprw6"); | |
| </script>""") | |
| # gr.TabbedInterface([vctk, clone, lj, longText], ['Multi-Voice', 'Voice Cloning', 'LJSpeech', 'Long Text [Beta]']) | |
| gr.TabbedInterface([vctk, clone, lj], ['Multi-Voice', 'Voice Cloning', 'LJSpeech', 'Long Text [Beta]']) | |
| gr.Markdown(""" | |
| Welcome to experiment online. | |
| Run this demo locally using Docker: | |
| ```bash | |
| docker run -it -p 7860:7860 --platform=linux/amd64 --gpus all registry.hf.space/styletts2-styletts2:latest python app.py | |
| ``` | |
| """) | |
| if __name__ == "__main__": | |
| demo.queue(api_open=False, max_size=15).launch(show_api=False) | |