Spaces:
Running
Running
| import tempfile | |
| from typing import Optional | |
| import gradio as gr | |
| import numpy as np | |
| from TTS.utils.manage import ModelManager | |
| from TTS.utils.synthesizer import Synthesizer | |
| MODEL_NAMES = [ | |
| "uk/mai/glow-tts" | |
| ] | |
| MODELS = {} | |
| manager = ModelManager() | |
| for MODEL_NAME in MODEL_NAMES: | |
| print(f"downloading {MODEL_NAME}") | |
| model_path, config_path, model_item = manager.download_model( | |
| f"tts_models/{MODEL_NAME}") | |
| vocoder_name: Optional[str] = model_item["default_vocoder"] | |
| vocoder_path = None | |
| vocoder_config_path = None | |
| if vocoder_name is not None: | |
| vocoder_path, vocoder_config_path, _ = manager.download_model( | |
| vocoder_name) | |
| synthesizer = Synthesizer( | |
| model_path, config_path, None, vocoder_path, vocoder_config_path, | |
| ) | |
| MODELS[MODEL_NAME] = synthesizer | |
| def tts(text: str, model_name: str): | |
| print(text, model_name) | |
| synthesizer = MODELS.get(model_name, None) | |
| if synthesizer is None: | |
| raise NameError("model not found") | |
| wavs = synthesizer.tts(text) | |
| # output = (synthesizer.output_sample_rate, np.array(wavs)) | |
| # return output | |
| with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp: | |
| synthesizer.save_wav(wavs, fp) | |
| return fp.name | |
| iface = gr.Interface( | |
| fn=tts, | |
| inputs=[ | |
| gr.inputs.Textbox( | |
| label="Input", | |
| default="Привіт, як твої справи?", | |
| ), | |
| gr.inputs.Radio( | |
| label="Pick a TTS Model", | |
| choices=MODEL_NAMES, | |
| ), | |
| ], | |
| outputs=gr.outputs.Audio(label="Output"), | |
| title="🐸💬 - Coqui TTS", | |
| theme="huggingface", | |
| description="🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production", | |
| article="more info at https://github.com/coqui-ai/TTS", | |
| ) | |
| iface.launch() | |