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ApplioRVC-Inference
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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
import requests
from pathlib import Path
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)
# Create an input field for the URL
url = st.text_input("Enter the URL of the CKPT:")

# Download the file when the user presses Enter
if url:
    response = requests.get(url)
    file_content = response.content
    file_name = url.split("/")[-1]

    # Save the file to the local machine
    with open(file_name, "wb") as f:
        f.write(file_content)

    # Save the file path as a variable
    file_path = f.name
    ckpt_temp_file = file_path

# Display the file path
if "file_path" in locals():
    st.success("File saved to: {}".format(file_path))

###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))