ApplioRVC-Inference / streamlitpoe.py
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import streamlit as st
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import json
import tempfile
import shutil
temp_dir = tempfile.mkdtemp()
global ckpt_temp_file
global audio_temp_file
global config_temp_file
###################################################
from utils.hparams import hparams
from preprocessing.data_gen_utils import get_pitch_parselmouth,get_pitch_crepe
import numpy as np
import matplotlib.pyplot as plt
import IPython.display as ipd
import utils
import librosa
import torchcrepe
from infer import *
import logging
from infer_tools.infer_tool import *
import io
clip_completed = False
def render_audio(ckpt_temp_file, config_temp_file, audio_temp_file, title):
logging.getLogger('numba').setLevel(logging.WARNING)
title = int(title)
project_name = "Unnamed"
model_path = ckpt_temp_file
config_path= config_temp_file
hubert_gpu=True
svc_model = Svc(project_name,config_path,hubert_gpu, model_path)
print('model loaded')
wav_fn = audio_temp_file
demoaudio, sr = librosa.load(wav_fn)
key = title # 音高调整,支持正负(半音)
# 加速倍数
pndm_speedup = 20
wav_gen='queeeeee.wav'#直接改后缀可以保存不同格式音频,如flac可无损压缩
f0_tst, f0_pred, audio = run_clip(svc_model,file_path=wav_fn, key=key, acc=pndm_speedup, use_crepe=True, use_pe=True, thre=0.05,
use_gt_mel=False, add_noise_step=500,project_name=project_name,out_path=wav_gen)
clip_completed = True
if clip_completed:
# If the 'run_clip' function has completed, use the st.audio function to show an audio player for the file stored in the 'wav_gen' variable
st.audio(wav_gen)
#######################################################
st.set_page_config(
page_title="DiffSVC Render",
page_icon="🧊",
initial_sidebar_state="expanded",
)
############
st.title('DIFF-SVC Render')
###CKPT LOADER
ckpt = st.file_uploader("Choose your CKPT", type= 'ckpt')
# Check if user uploaded a CKPT file
if ckpt is not None:
#TEMP FUNCTION
with tempfile.NamedTemporaryFile(mode="wb", suffix='.ckpt', delete=False) as temp:
# Get the file contents as bytes
bytes_data = ckpt.getvalue()
# Write the bytes to the temporary file
temp.write(bytes_data)
ckpt_temp_file = temp.name
# Print the temporary file name
print(temp.name)
###CONFIG LOADER
config = st.file_uploader("Choose your config", type= 'yaml')
if config is not None:
#TEMP FUNCTION
with tempfile.NamedTemporaryFile(mode="wb", suffix='.yaml', delete=False) as temp:
# Get the file contents as bytes
bytes_data = config.getvalue()
# Write the bytes to the temporary file
temp.write(bytes_data)
config_temp_file = temp.name
# Print the temporary file name
print(temp.name)
##WAV LOADER
audio = st.file_uploader("Choose your audio", type= 'wav' or 'mp3')
if audio is not None:
#TEMP FUNCTION
with tempfile.NamedTemporaryFile(mode="wb", suffix='.wav', delete=False) as temp:
# Get the file contents as bytes
bytes_data = audio.getvalue()
# Write the bytes to the temporary file
temp.write(bytes_data)
audio_temp_file = temp.name
# Print the temporary file name
print(temp.name)
title = st.text_input('Key', '0')
gflag = st.slider('Gender Flag', 0.80, 1.20, 1.00)
###DOWNLOAD
st.button('Render', on_click=render_audio(ckpt_temp_file, config_temp_file, audio_temp_file, title))