OPENGIT/Retrieval-based-Voice-Conversion-WebUI
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Update infer-web.py

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liujing04 2023-04-09 15:21:05 +00:00 committed by GitHub
parent 25c16c4276
commit 47c665384f
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1 changed files with 7 additions and 7 deletions
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infer-web.py
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@ -88,8 +88,8 @@ def vc_single(sid,input_audio,f0_up_key,f0_file,f0_method,file_index,file_big_np
def vc_multi(sid,dir_path,opt_root,paths,f0_up_key,f0_method,file_index,file_big_npy,index_rate):
try:
dir_path=dir_path.strip(" ")#防止小白拷路径头尾带了空格
opt_root=opt_root.strip(" ")
dir_path=dir_path.strip(" ").strip('"').strip("\n").strip('"').strip(" ")#防止小白拷路径头尾带了空格和"和回车
opt_root=opt_root.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
os.makedirs(opt_root, exist_ok=True)
try:
if(dir_path!=""):paths=[os.path.join(dir_path,name)for name in os.listdir(dir_path)]
@ -115,9 +115,9 @@ def vc_multi(sid,dir_path,opt_root,paths,f0_up_key,f0_method,file_index,file_big
def uvr(model_name,inp_root,save_root_vocal,paths,save_root_ins):
infos = []
try:
inp_root = inp_root.strip(" ").strip("\n")
save_root_vocal = save_root_vocal.strip(" ").strip("\n")
save_root_ins = save_root_ins.strip(" ").strip("\n")
inp_root = inp_root.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
save_root_vocal = save_root_vocal.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
save_root_ins = save_root_ins.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
pre_fun = _audio_pre_(model_path=os.path.join(weight_uvr5_root,model_name+".pth"), device=device, is_half=is_half)
if (inp_root != ""):paths = [os.path.join(inp_root, name) for name in os.listdir(inp_root)]
else:paths = [path.name for path in paths]
@ -569,8 +569,8 @@ with gr.Blocks() as app:
""")
with gr.Row():
save_epoch10 = gr.Slider(minimum=0, maximum=50, step=1, label='保存频率save_every_epoch', value=5,interactive=True)
total_epoch11 = gr.Slider(minimum=0, maximum=100, step=1, label='总训练轮数total_epoch', value=10,interactive=True)
batch_size12 = gr.Slider(minimum=0, maximum=32, step=1, label='batch_size', value=4,interactive=True)
total_epoch11 = gr.Slider(minimum=0, maximum=1000, step=1, label='总训练轮数total_epoch', value=20,interactive=True)
batch_size12 = gr.Slider(minimum=0, maximum=32, step=1, label='每张显卡的batch_size', value=4,interactive=True)
if_save_latest13 = gr.Radio(label="是否仅保存最新的ckpt文件以节省硬盘空间", choices=["是", "否"], value="否", interactive=True)
if_cache_gpu17 = gr.Radio(label="是否缓存所有训练集至显存。10min以下小数据可缓存以加速训练，大数据缓存会炸显存也加不了多少速", choices=["是", "否"], value="否", interactive=True)
with gr.Row():