import importlib import re import gradio as gr import yaml from gradio.inputs import Textbox from inference.tts.base_tts_infer import BaseTTSInfer from utils.commons.hparams import set_hparams from utils.commons.hparams import hparams as hp import numpy as np from utils.text.text_encoder import PUNCS class GradioInfer: def __init__(self, exp_name, inference_cls, title, description, article, example_inputs): self.exp_name = exp_name self.title = title self.description = description self.article = article self.example_inputs = example_inputs pkg = ".".join(inference_cls.split(".")[:-1]) cls_name = inference_cls.split(".")[-1] self.inference_cls = getattr(importlib.import_module(pkg), cls_name) def greet(self, text): sents = re.split(rf'([{PUNCS}])', text.replace('\n', ',')) if sents[-1] not in list(PUNCS): sents = sents + ['.'] audio_outs = [] s = "" for i in range(0, len(sents), 2): if len(sents[i]) > 0: s += sents[i] + sents[i + 1] if len(s) >= 400 or (i >= len(sents) - 2 and len(s) > 0): audio_out = self.infer_ins.infer_once({ 'text': s }) audio_out = audio_out * 32767 audio_out = audio_out.astype(np.int16) audio_outs.append(audio_out) audio_outs.append(np.zeros(int(hp['audio_sample_rate'] * 0.3)).astype(np.int16)) s = "" audio_outs = np.concatenate(audio_outs) return hp['audio_sample_rate'], audio_outs def run(self): set_hparams(exp_name=self.exp_name) infer_cls = self.inference_cls self.infer_ins: BaseTTSInfer = infer_cls(hp) example_inputs = self.example_inputs iface = gr.Interface(fn=self.greet, inputs=Textbox( lines=10, placeholder=None, default=example_inputs[0], label="input text"), outputs="audio", allow_flagging="never", title=self.title, description=self.description, article=self.article, examples=example_inputs, enable_queue=True) iface.launch(cache_examples=True) if __name__ == '__main__': gradio_config = yaml.safe_load(open('inference/tts/gradio/gradio_settings.yaml')) g = GradioInfer(**gradio_config) g.run()