import io
#
import gradio as gr
import librosa
import numpy as np
import soundfile
from inference.infer_tool import Svc
import logging
from logmmse import logmmse

logging.getLogger('numba').setLevel(logging.WARNING)
#
model_name = "logs/32k/uma1.pth"
config_name = "configs/uma1.json"
model2_name="logs/32k/uma2.pth"
config2_name = "configs/uma2.json"
model3_name="logs/32k/uma3.pth"
config3_name = "configs/uma3.json"
sid_map = {
    "米浴":"rice",
    "东海帝皇":"teio",
    "爱慕织姬":"aimya",
    "成田大进":"taishin",
    "优秀素质":"nature",
    "待兼诗歌剧":"mati",
    "大拓太阳神":"sun",
    "目白善信":"pama",
    "第一红宝石":"ruby"
}

svc = Svc(model_name, config_name)
def vc_fn(sid, vc_input3,vc_input4,vc_transform,sid3):
    if(vc_input3==None and vc_input4==None):
        return "请上传一段音频后再次尝试", None   
    if sid3=='文件':
        sampling_rate, audio = vc_input3 
    else:
        sampling_rate, audio = vc_input4
    # print(audio.shape,sampling_rate)
    duration = audio.shape[0] / sampling_rate
    audio = (audio / np.iinfo(audio.dtype).max).astype(np.float32)
    if len(audio.shape) > 1:
        audio = librosa.to_mono(audio.transpose(1, 0))
    if sampling_rate != 32000:
        audio = librosa.resample(audio, orig_sr=sampling_rate, target_sr=32000)
    audio = logmmse(audio, 32000)
    print(audio.shape)
    out_wav_path = io.BytesIO()
    soundfile.write(out_wav_path, audio, 32000, format="wav")
    out_wav_path.seek(0)
    sid = sid_map[sid]
    print(sid)
    
    if sid in ["rice","teio","aimya"]:
        svc = Svc(model_name, config_name)
    if sid in ["taishin","nature","mati"]:
        svc = Svc(model2_name, config2_name)
    if sid in ["sun","ruby","pama"]:
        svc = Svc(model3_name, config3_name)
    out_audio, _out_sr = svc.infer(sid, vc_transform, out_wav_path)

    _audio = out_audio.cpu().numpy()
    return sid3, (32000, _audio)

#
app = gr.Blocks()
with app:
    with gr.Tabs():
        with gr.TabItem("Basic"):
            gr.Markdown(value="""
                # 前言
                本demo基于[sovits 3.0 32khz版本](https://github.com/innnky/so-vits-svc)训练的，并改写于 `https://huggingface.co/spaces/innnky/nyaru-svc-3.0`，
                https://huggingface.co/spaces/yukie/yukie-sovits3等
                特别感谢innnky佬与yukie佬
                加载赛马娘语音，自用。
                """)
            sid = gr.Dropdown(label="音色", choices=[
                              "东海帝皇", "米浴","爱慕织姬", "成田大进","优秀素质","待兼诗歌剧","大拓太阳神","目白善信","第一红宝石"], value="东海帝皇")
            sid2 = gr.Dropdown(label="上传方式", choices=[
                              "文件", "录音"], value="文件")
            vc_input3 = gr.Audio(label="上传音频")
            vc_input4 = gr.Audio(source="microphone")
            vc_transform = gr.Number(
                label="变调（整数，可以正负，半音数量，升高八度就是12）", value=0)
            vc_submit = gr.Button("转换", variant="primary")
            vc_output1 = gr.Textbox(label="Output Message")
            vc_output2 = gr.Audio(label="Output Audio")

            gr.Markdown(value="""
                ## 注意
                不要使用太长的语音
                """)
        vc_submit.click(vc_fn, [sid,vc_input3,vc_input4, vc_transform,sid2], [
                        vc_output1, vc_output2])

    app.launch()