explore-vits / app.py
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import torch
from transformers import pipeline
import numpy as np
import gradio as gr
set_seed(0)
def _grab_best_device(use_gpu=True):
if torch.cuda.device_count() > 0 and use_gpu:
device = "cuda"
else:
device = "cpu"
return device
device = _grab_best_device()
HUB_PATH = "ylacombe/vits_vctk_welsh_male"
pipe = pipeline(HUB_PATH, device=0)
title = "# 🐶 VITS"
description = """
"""
num_speakers = pipe.model.config.num_speakers
# Inference
def generate_audio(text, spkr_id):
forward_params = {"spkr_id": spkr_id}
output = pipeline(text, forward_params=forward_params)
return (output["sampling_rate"], output["audio"].squeeze())
# Gradio blocks demo
with gr.Blocks() as demo_blocks:
gr.Markdown(title)
gr.Markdown(description)
with gr.Row():
with gr.Column():
inp_text = gr.Textbox(label="Input Text", info="What would you like bark to synthesise?")
spkr = gr.Dropdown(
[i for i in range(num_speakers)],
value=None,
label="Speaker ID",
info="Default: Unconditional Generation"
)
btn = gr.Button("Generate Audio!")
with gr.Column():
out_audio_vocos = gr.Audio(type="numpy", autoplay=False, label="Generated Audio", show_label=True)
btn.click(generate_audio, [inp_text, spk], [out_audio_vocos])
demo_blocks.queue().launch(debug=True)