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Retrieval-based-Voice-Conversion-WebUI
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total_fea not needed now 

total_fea not needed now
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RVC-Boss 2023-04-26 19:12:47 +08:00 committed by GitHub
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commit a21f7ec11f
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1 changed files with 48 additions and 38 deletions
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infer-web.py
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@ -126,7 +126,7 @@ def vc_single(
f0_file, f0_file,
f0_method, f0_method,
file_index, file_index,
file_big_npy, # file_big_npy,
index_rate, index_rate,
): # spk_item, input_audio0, vc_transform0,f0_file,f0method0 ): # spk_item, input_audio0, vc_transform0,f0_file,f0method0
global tgt_sr, net_g, vc, hubert_model global tgt_sr, net_g, vc, hubert_model
@ -147,9 +147,9 @@ def vc_single(
.strip(" ") .strip(" ")
.replace("trained", "added") .replace("trained", "added")
) # 防止小白写错，自动帮他替换掉 ) # 防止小白写错，自动帮他替换掉
file_big_npy = ( # file_big_npy = (
file_big_npy.strip(" ").strip('"').strip("\n").strip('"').strip(" ") # file_big_npy.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
) # )
audio_opt = vc.pipeline( audio_opt = vc.pipeline(
hubert_model, hubert_model,
net_g, net_g,
@ -159,7 +159,7 @@ def vc_single(
f0_up_key, f0_up_key,
f0_method, f0_method,
file_index, file_index,
file_big_npy, # file_big_npy,
index_rate, index_rate,
if_f0, if_f0,
f0_file=f0_file, f0_file=f0_file,
@ -182,7 +182,7 @@ def vc_multi(
f0_up_key, f0_up_key,
f0_method, f0_method,
file_index, file_index,
file_big_npy, # file_big_npy,
index_rate, index_rate,
): ):
try: try:
@ -200,6 +200,14 @@ def vc_multi(
traceback.print_exc() traceback.print_exc()
paths = [path.name for path in paths] paths = [path.name for path in paths]
infos = [] infos = []
file_index = (
file_index.strip(" ")
.strip('"')
.strip("\n")
.strip('"')
.strip(" ")
.replace("trained", "added")
) # 防止小白写错，自动帮他替换掉
for path in paths: for path in paths:
info, opt = vc_single( info, opt = vc_single(
sid, sid,
@ -208,7 +216,7 @@ def vc_multi(
None, None,
f0_method, f0_method,
file_index, file_index,
file_big_npy, # file_big_npy,
index_rate, index_rate,
) )
if info == "Success": if info == "Success":
@ -629,29 +637,29 @@ def train_index(exp_dir1):
phone = np.load("%s/%s" % (feature_dir, name)) phone = np.load("%s/%s" % (feature_dir, name))
npys.append(phone) npys.append(phone)
big_npy = np.concatenate(npys, 0) big_npy = np.concatenate(npys, 0)
np.save("%s/total_fea.npy" % exp_dir, big_npy) # np.save("%s/total_fea.npy" % exp_dir, big_npy)
n_ivf = big_npy.shape[0] // 39 # n_ivf = big_npy.shape[0] // 39
infos = [] n_ivf = min(int(16 * np.sqrt(big_npy.shape[0])),big_npy.shape[0]// 39)
infos.append("%s,%s" % (big_npy.shape, n_ivf)) infos=[]
infos.append("%s,%s"%(big_npy.shape,n_ivf))
yield "\n".join(infos) yield "\n".join(infos)
index = faiss.index_factory(256, "IVF%s,Flat" % n_ivf) index = faiss.index_factory(256, "IVF%s,Flat"%n_ivf)
# index = faiss.index_factory(256, "IVF%s,PQ128x4fs,RFlat"%n_ivf)
infos.append("training") infos.append("training")
yield "\n".join(infos) yield "\n".join(infos)
index_ivf = faiss.extract_index_ivf(index) # index_ivf = faiss.extract_index_ivf(index) #
index_ivf.nprobe = int(np.power(n_ivf, 0.3)) # index_ivf.nprobe = int(np.power(n_ivf,0.3))
index_ivf.nprobe = 1
index.train(big_npy) index.train(big_npy)
faiss.write_index( faiss.write_index(index, '%s/trained_IVF%s_Flat_nprobe_%s.index'%(exp_dir,n_ivf,index_ivf.nprobe))
index, # faiss.write_index(index, '%s/trained_IVF%s_Flat_FastScan.index'%(exp_dir,n_ivf))
"%s/trained_IVF%s_Flat_nprobe_%s.index" % (exp_dir, n_ivf, index_ivf.nprobe),
)
infos.append("adding") infos.append("adding")
yield "\n".join(infos) yield "\n".join(infos)
index.add(big_npy) index.add(big_npy)
faiss.write_index( faiss.write_index(index, '%s/added_IVF%s_Flat_nprobe_%s.index'%(exp_dir,n_ivf,index_ivf.nprobe))
index, infos.append("成功构建索引，added_IVF%s_Flat_nprobe_%s.index"%(n_ivf,index_ivf.nprobe))
"%s/added_IVF%s_Flat_nprobe_%s.index" % (exp_dir, n_ivf, index_ivf.nprobe), # faiss.write_index(index, '%s/added_IVF%s_Flat_FastScan.index'%(exp_dir,n_ivf))
) # infos.append("成功构建索引，added_IVF%s_Flat_FastScan.index"%(n_ivf))
infos.append("成功构建索引, added_IVF%s_Flat_nprobe_%s.index" % (n_ivf, index_ivf.nprobe))
yield "\n".join(infos) yield "\n".join(infos)
@ -842,13 +850,15 @@ def train1key(
phone = np.load("%s/%s" % (feature_dir, name)) phone = np.load("%s/%s" % (feature_dir, name))
npys.append(phone) npys.append(phone)
big_npy = np.concatenate(npys, 0) big_npy = np.concatenate(npys, 0)
np.save("%s/total_fea.npy" % exp_dir, big_npy) # np.save("%s/total_fea.npy" % exp_dir, big_npy)
n_ivf = big_npy.shape[0] // 39 # n_ivf = big_npy.shape[0] // 39
n_ivf = min(int(16 * np.sqrt(big_npy.shape[0])),big_npy.shape[0]// 39)
yield get_info_str("%s,%s" % (big_npy.shape, n_ivf)) yield get_info_str("%s,%s" % (big_npy.shape, n_ivf))
index = faiss.index_factory(256, "IVF%s,Flat" % n_ivf) index = faiss.index_factory(256, "IVF%s,Flat" % n_ivf)
yield get_info_str("training index") yield get_info_str("training index")
index_ivf = faiss.extract_index_ivf(index) # index_ivf = faiss.extract_index_ivf(index) #
index_ivf.nprobe = int(np.power(n_ivf, 0.3)) # index_ivf.nprobe = int(np.power(n_ivf,0.3))
index_ivf.nprobe = 1
index.train(big_npy) index.train(big_npy)
faiss.write_index( faiss.write_index(
index, index,
@ -1022,16 +1032,16 @@ with gr.Blocks() as app:
value="E:\\codes\\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\added_IVF677_Flat_nprobe_7.index", value="E:\\codes\\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\added_IVF677_Flat_nprobe_7.index",
interactive=True, interactive=True,
) )
file_big_npy1 = gr.Textbox( # file_big_npy1 = gr.Textbox(
label=i18n("特征文件路径"), # label=i18n("特征文件路径"),
value="E:\\codes\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\total_fea.npy", # value="E:\\codes\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\total_fea.npy",
interactive=True, # interactive=True,
) # )
index_rate1 = gr.Slider( index_rate1 = gr.Slider(
minimum=0, minimum=0,
maximum=1, maximum=1,
label="检索特征占比", label="检索特征占比",
value=0.6, value=0.65,
interactive=True, interactive=True,
) )
f0_file = gr.File(label=i18n("F0曲线文件, 可选, 一行一个音高, 代替默认F0及升降调")) f0_file = gr.File(label=i18n("F0曲线文件, 可选, 一行一个音高, 代替默认F0及升降调"))
@ -1048,7 +1058,7 @@ with gr.Blocks() as app:
f0_file, f0_file,
f0method0, f0method0,
file_index1, file_index1,
file_big_npy1, # file_big_npy1,
index_rate1, index_rate1,
], ],
[vc_output1, vc_output2], [vc_output1, vc_output2],
@ -1075,11 +1085,11 @@ with gr.Blocks() as app:
value="E:\\codes\\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\added_IVF677_Flat_nprobe_7.index", value="E:\\codes\\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\added_IVF677_Flat_nprobe_7.index",
interactive=True, interactive=True,
) )
file_big_npy2 = gr.Textbox( # file_big_npy2 = gr.Textbox(
label=i18n("特征文件路径"), # label=i18n("特征文件路径"),
value="E:\\codes\\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\total_fea.npy", # value="E:\\codes\\py39\\vits_vc_gpu_train\\logs\\mi-test-1key\\total_fea.npy",
interactive=True, # interactive=True,
) # )
index_rate2 = gr.Slider( index_rate2 = gr.Slider(
minimum=0, minimum=0,
maximum=1, maximum=1,
@ -1107,7 +1117,7 @@ with gr.Blocks() as app:
vc_transform1, vc_transform1,
f0method1, f0method1,
file_index2, file_index2,
file_big_npy2, # file_big_npy2,
index_rate2, index_rate2,
], ],
[vc_output3], [vc_output3],