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| import importlib | |
| import re | |
| import gradio as gr | |
| import yaml | |
| from gradio.components import Textbox, Dropdown | |
| from inference.m4singer.base_svs_infer import BaseSVSInfer | |
| from utils.hparams import set_hparams | |
| from utils.hparams import hparams as hp | |
| import numpy as np | |
| from inference.m4singer.gradio.share_btn import community_icon_html, loading_icon_html, share_js | |
| 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, singer, text, notes, notes_duration): | |
| PUNCS = '。？；：' | |
| sents = re.split(rf'([{PUNCS}])', text.replace('\n', ',')) | |
| sents_notes = re.split(rf'([{PUNCS}])', notes.replace('\n', ',')) | |
| sents_notes_dur = re.split(rf'([{PUNCS}])', notes_duration.replace('\n', ',')) | |
| if sents[-1] not in list(PUNCS): | |
| sents = sents + [''] | |
| sents_notes = sents_notes + [''] | |
| sents_notes_dur = sents_notes_dur + [''] | |
| audio_outs = [] | |
| s, n, n_dur = "", "", "" | |
| for i in range(0, len(sents), 2): | |
| if len(sents[i]) > 0: | |
| s += sents[i] + sents[i + 1] | |
| n += sents_notes[i] + sents_notes[i+1] | |
| n_dur += sents_notes_dur[i] + sents_notes_dur[i+1] | |
| if len(s) >= 400 or (i >= len(sents) - 2 and len(s) > 0): | |
| audio_out = self.infer_ins.infer_once({ | |
| 'spk_name': singer, | |
| 'text': s, | |
| 'notes': n, | |
| 'notes_duration': n_dur, | |
| }) | |
| 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 = "" | |
| n = "" | |
| audio_outs = np.concatenate(audio_outs) | |
| return (hp['audio_sample_rate'], audio_outs), gr.update(visible=True), gr.update(visible=True), gr.update(visible=True) | |
| def run(self): | |
| set_hparams(config=f'checkpoints/{self.exp_name}/config.yaml', exp_name=self.exp_name, print_hparams=False) | |
| infer_cls = self.inference_cls | |
| self.infer_ins: BaseSVSInfer = infer_cls(hp) | |
| example_inputs = self.example_inputs | |
| for i in range(len(example_inputs)): | |
| singer, text, notes, notes_dur = example_inputs[i].split('<sep>') | |
| example_inputs[i] = [singer, text, notes, notes_dur] | |
| singerList = \ | |
| [ | |
| 'Tenor-1', 'Tenor-2', 'Tenor-3', 'Tenor-4', 'Tenor-5', 'Tenor-6', 'Tenor-7', | |
| 'Alto-1', 'Alto-2', 'Alto-3', 'Alto-4', 'Alto-5', 'Alto-6', 'Alto-7', | |
| 'Soprano-1', 'Soprano-2', 'Soprano-3', | |
| 'Bass-1', 'Bass-2', 'Bass-3', | |
| ] | |
| css = """ | |
| #share-btn-container { | |
| display: flex; padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; width: 13rem; | |
| } | |
| #share-btn { | |
| all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.25rem !important; padding-bottom: 0.25rem !important;right:0; | |
| } | |
| #share-btn * { | |
| all: unset; | |
| } | |
| #share-btn-container div:nth-child(-n+2){ | |
| width: auto !important; | |
| min-height: 0px !important; | |
| } | |
| #share-btn-container .wrap { | |
| display: none !important; | |
| } | |
| """ | |
| with gr.Blocks(css=css) as demo: | |
| gr.HTML("""<div style="text-align: center; margin: 0 auto;"> | |
| <div | |
| style=" | |
| display: inline-flex; | |
| align-items: center; | |
| gap: 0.8rem; | |
| font-size: 1.75rem; | |
| " | |
| > | |
| <h1 style="font-weight: 900; margin-bottom: 10px; margin-top: 14px;"> | |
| M4Singer | |
| </h1> | |
| </div> | |
| </div> | |
| """ | |
| ) | |
| gr.Markdown(self.description) | |
| with gr.Row(): | |
| with gr.Column(): | |
| singer_l = Dropdown(choices=singerList, value=example_inputs[0][0], label="SingerID", elem_id="inp_singer") | |
| inp_text = Textbox(lines=2, placeholder=None, value=example_inputs[0][1], label="input text", elem_id="inp_text") | |
| inp_note = Textbox(lines=2, placeholder=None, value=example_inputs[0][2], label="input note", elem_id="inp_note") | |
| inp_duration = Textbox(lines=2, placeholder=None, value=example_inputs[0][3], label="input duration", elem_id="inp_duration") | |
| generate = gr.Button("Generate Singing Voice from Musical Score") | |
| with gr.Column(): | |
| singing_output = gr.Audio(label="Result", type="numpy", elem_id="music-output") | |
| with gr.Group(elem_id="share-btn-container"): | |
| community_icon = gr.HTML(community_icon_html, visible=False) | |
| loading_icon = gr.HTML(loading_icon_html, visible=False) | |
| share_button = gr.Button("滔滔AI，为爱滔滔💕", elem_id="share-btn", visible=False) | |
| gr.Examples(examples=self.example_inputs, | |
| inputs=[singer_l, inp_text, inp_note, inp_duration], | |
| outputs=[singing_output, share_button, community_icon, loading_icon], | |
| fn=self.greet, | |
| cache_examples=True) | |
| gr.Markdown(self.article) | |
| generate.click(self.greet, | |
| inputs=[singer_l, inp_text, inp_note, inp_duration], | |
| outputs=[singing_output, share_button, community_icon, loading_icon],) | |
| demo.queue().launch(share=True) | |
| if __name__ == '__main__': | |
| gradio_config = yaml.safe_load(open('inference/m4singer/gradio/gradio_settings.yaml')) | |
| g = GradioInfer(**gradio_config) | |
| g.run() | |