app.py

INTROTXT = """# StyleTTS 2
kudos to mrfakename for the base gradio code I'm borrowing here.

日本語用
The Text-guided inference may or may not work. you can only do inference max 512 tokens.
**
"""
import gradio as gr
import styletts2importable
import Text-guided Inferenceimportable
import torch
import os
from txtsplit import txtsplit
import numpy as np
import pickle
theme = gr.themes.Base(theme="NoCrypt/miku",
    font=[gr.themes.GoogleFont('Libre Franklin'), gr.themes.GoogleFont('Public Sans'), 'system-ui', 'sans-serif'],
)

VO_JA_Kamisato_Ayaka_About_Kujou_Sara.wav
voicelist = ['VO_JA_Kamisato_Ayaka_About_Kujou_Sara','hontonokimochi','gaen_original']
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))
if not torch.cuda.is_available(): INTROTXT += "\n\n### You are on a CPU-only system, inference will be much slower.\n\nYou can use the [online demo](https://huggingface.co/spaces/styletts2/styletts2) for fast inference."
def synthesize(text, voice, lngsteps, password, progress=gr.Progress()):
    if text.strip() == "":
        raise gr.Error("You must enter some text")
    if len(text) > 50000:
        raise gr.Error("Text must be <50k characters")
    print("*** saying ***")
    print(text)
    print("*** end ***")
    texts = txtsplit(text)
    v = voice.lower()
    audios = []
    for t in progress.tqdm(texts):
        print(t)
        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, embscale, alpha, beta, 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) > 50000:
        raise gr.Error("Text must be <50k characters")
    if embscale > 1.3 and len(text) < 20:
        gr.Warning("WARNING: You entered short text, you may get static!")
    print("*** saying ***")
    print(text)
    print("*** end ***")
    texts = txtsplit(text)
    audios = []
    # vs = styletts2importable.compute_style(voice)
    vs = styletts2importable.compute_style(voice)
    # print(vs)
    for t in progress.tqdm(texts):
        audios.append(styletts2importable.inference(t, vs, alpha=alpha, beta=beta, diffusion_steps=vcsteps, embedding_scale=embscale))
        # audios.append(styletts2importable.inference(t, vs, diffusion_steps=10, alpha=0.3, beta=0.7, embedding_scale=5))
    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, Text-guided Inferenceimportable.inference(text, noise, diffusion_steps=7, embedding_scale=1))
    if text.strip() == "":
        raise gr.Error("You must enter some text")
    if len(text) > 150000:
        raise gr.Error("Text must be <150k characters")
    print("*** saying ***")
    print(text)
    print("*** end ***")
    texts = txtsplit(text)
    audios = []
    for t in progress.tqdm(texts):
        audios.append(Text-guided Inferenceimportable.inference(t, noise, diffusion_steps=steps, embedding_scale=1))
    return (24000, np.concatenate(audios))


with gr.Blocks() as vctk:
    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=3, step=1, label="Diffusion Steps", info="Higher gives you more diverse results but not necessarily higher quality - これを増えたらもっとエモーショナルな結果になりますが、クオリティーのいい結果になるとは限らない。", 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", waveform_options={'waveform_progress_color': '#3C82F6'})
            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, waveform_options={'waveform_progress_color': '#3C82F6'})
            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)
            embscale = gr.Slider(minimum=1, maximum=10, value=1, step=0.1, label="Embedding Scale (READ WARNING BELOW)", info="Defaults to 1. WARNING: If you set this too high and generate text that's too short you will get static!", interactive=True)
            alpha = gr.Slider(minimum=0, maximum=1, value=0.3, step=0.1, label="Alpha", info="Defaults to 0.3", interactive=True)
            beta = gr.Slider(minimum=0, maximum=1, value=0.7, step=0.1, label="Beta", info="Defaults to 0.7", interactive=True)
        with gr.Column(scale=1):
            clbtn = gr.Button("Synthesize", variant="primary")
            claudio = gr.Audio(interactive=False, label="Synthesized Audio", waveform_options={'waveform_progress_color': '#3C82F6'})
            clbtn.click(clsynthesize, inputs=[clinp, clvoice, vcsteps, embscale, alpha, beta], 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", waveform_options={'waveform_progress_color': '#3C82F6'})
            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(INTROTXT)
    gr.DuplicateButton("Duplicate Space")
    # gr.TabbedInterface([vctk, clone, lj, longText], ['Multi-Voice', 'Voice Cloning', 'Text-guided Inference', 'Long Text [Beta]'])
    gr.TabbedInterface([vctk, clone, lj], ['Multi-Voice', 'Voice Cloning (don't use this,このオプションはこのモデルに利きません。', 'Text-guided Inference', 'Long Text [Beta]'])
    gr.Markdown("""
Demo by [mrfakename](https://twitter.com/realmrfakename). I am not affiliated with the StyleTTS 2 authors.

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
```
""") # Please do not remove this line.
if __name__ == "__main__":
    # demo.queue(api_open=False, max_size=15).launch(show_api=False)
    demo.queue(api_open=False, max_size=15).launch(show_api=False)