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https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI.git
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Format code (#522)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
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'''
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"""
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v1
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v1
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runtime\python.exe myinfer-v2-0528.py 0 "E:\codes\py39\RVC-beta\todo-songs" "E:\codes\py39\logs\mi-test\added_IVF677_Flat_nprobe_7.index" harvest "E:\codes\py39\RVC-beta\output" "E:\codes\py39\test-20230416b\weights\mi-test.pth" 0.66 cuda:0 True 3 0 1 0.33
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runtime\python.exe myinfer-v2-0528.py 0 "E:\codes\py39\RVC-beta\todo-songs" "E:\codes\py39\logs\mi-test\added_IVF677_Flat_nprobe_7.index" harvest "E:\codes\py39\RVC-beta\output" "E:\codes\py39\test-20230416b\weights\mi-test.pth" 0.66 cuda:0 True 3 0 1 0.33
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v2
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v2
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runtime\python.exe myinfer-v2-0528.py 0 "E:\codes\py39\RVC-beta\todo-songs" "E:\codes\py39\test-20230416b\logs\mi-test-v2\aadded_IVF677_Flat_nprobe_1_v2.index" harvest "E:\codes\py39\RVC-beta\output_v2" "E:\codes\py39\test-20230416b\weights\mi-test-v2.pth" 0.66 cuda:0 True 3 0 1 0.33
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runtime\python.exe myinfer-v2-0528.py 0 "E:\codes\py39\RVC-beta\todo-songs" "E:\codes\py39\test-20230416b\logs\mi-test-v2\aadded_IVF677_Flat_nprobe_1_v2.index" harvest "E:\codes\py39\RVC-beta\output_v2" "E:\codes\py39\test-20230416b\weights\mi-test-v2.pth" 0.66 cuda:0 True 3 0 1 0.33
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'''
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"""
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import os, sys, pdb, torch
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import os, sys, pdb, torch
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now_dir = os.getcwd()
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now_dir = os.getcwd()
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sys.path.append(now_dir)
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sys.path.append(now_dir)
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import argparse
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import argparse
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@ -13,6 +14,8 @@ import sys
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import torch
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import torch
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import tqdm as tq
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import tqdm as tq
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from multiprocessing import cpu_count
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from multiprocessing import cpu_count
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class Config:
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class Config:
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def __init__(self, device, is_half):
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def __init__(self, device, is_half):
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self.device = device
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self.device = device
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@ -90,6 +93,7 @@ class Config:
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return x_pad, x_query, x_center, x_max
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return x_pad, x_query, x_center, x_max
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f0up_key = sys.argv[1]
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f0up_key = sys.argv[1]
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input_path = sys.argv[2]
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input_path = sys.argv[2]
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index_path = sys.argv[3]
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index_path = sys.argv[3]
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@ -119,25 +123,54 @@ from fairseq import checkpoint_utils
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from scipy.io import wavfile
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from scipy.io import wavfile
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hubert_model = None
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hubert_model = None
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def load_hubert():
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def load_hubert():
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global hubert_model
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global hubert_model
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models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task(["hubert_base.pt"],suffix="",)
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models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task(
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["hubert_base.pt"],
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suffix="",
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)
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hubert_model = models[0]
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hubert_model = models[0]
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hubert_model = hubert_model.to(device)
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hubert_model = hubert_model.to(device)
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if(is_half):hubert_model = hubert_model.half()
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if is_half:
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else:hubert_model = hubert_model.float()
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hubert_model = hubert_model.half()
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else:
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hubert_model = hubert_model.float()
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hubert_model.eval()
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hubert_model.eval()
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def vc_single(sid, input_audio, f0_up_key, f0_file, f0_method, file_index, index_rate):
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def vc_single(sid, input_audio, f0_up_key, f0_file, f0_method, file_index, index_rate):
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global tgt_sr, net_g, vc, hubert_model, version
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global tgt_sr, net_g, vc, hubert_model, version
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if input_audio is None:return "You need to upload an audio", None
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if input_audio is None:
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return "You need to upload an audio", None
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f0_up_key = int(f0_up_key)
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f0_up_key = int(f0_up_key)
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audio = load_audio(input_audio, 16000)
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audio = load_audio(input_audio, 16000)
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times = [0, 0, 0]
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times = [0, 0, 0]
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if(hubert_model==None):load_hubert()
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if hubert_model == None:
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load_hubert()
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if_f0 = cpt.get("f0", 1)
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if_f0 = cpt.get("f0", 1)
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# audio_opt=vc.pipeline(hubert_model,net_g,sid,audio,times,f0_up_key,f0_method,file_index,file_big_npy,index_rate,if_f0,f0_file=f0_file)
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# audio_opt=vc.pipeline(hubert_model,net_g,sid,audio,times,f0_up_key,f0_method,file_index,file_big_npy,index_rate,if_f0,f0_file=f0_file)
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audio_opt=vc.pipeline(hubert_model,net_g,sid,audio,input_audio,times,f0_up_key,f0_method,file_index,index_rate,if_f0,filter_radius,tgt_sr,resample_sr,rms_mix_rate,version,protect,f0_file=f0_file)
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audio_opt = vc.pipeline(
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hubert_model,
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net_g,
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sid,
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audio,
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input_audio,
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times,
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f0_up_key,
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f0_method,
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file_index,
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index_rate,
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if_f0,
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filter_radius,
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tgt_sr,
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resample_sr,
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rms_mix_rate,
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version,
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protect,
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f0_file=f0_file,
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)
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print(times)
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print(times)
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return audio_opt
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return audio_opt
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@ -163,8 +196,10 @@ def get_vc(model_path):
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del net_g.enc_q
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del net_g.enc_q
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print(net_g.load_state_dict(cpt["weight"], strict=False)) # 不加这一行清不干净,真奇葩
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print(net_g.load_state_dict(cpt["weight"], strict=False)) # 不加这一行清不干净,真奇葩
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net_g.eval().to(device)
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net_g.eval().to(device)
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if (is_half):net_g = net_g.half()
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if is_half:
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else:net_g = net_g.float()
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net_g = net_g.half()
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else:
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net_g = net_g.float()
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vc = VC(tgt_sr, config)
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vc = VC(tgt_sr, config)
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n_spk = cpt["config"][-3]
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n_spk = cpt["config"][-3]
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# return {"visible": True,"maximum": n_spk, "__type__": "update"}
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# return {"visible": True,"maximum": n_spk, "__type__": "update"}
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@ -173,9 +208,10 @@ def get_vc(model_path):
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get_vc(model_path)
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get_vc(model_path)
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audios = os.listdir(input_path)
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audios = os.listdir(input_path)
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for file in tq.tqdm(audios):
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for file in tq.tqdm(audios):
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if file.endswith('.wav'):
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if file.endswith(".wav"):
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file_path = input_path + '/' + file
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file_path = input_path + "/" + file
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wav_opt=vc_single(0,file_path,f0up_key,None,f0method,index_path,index_rate)
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wav_opt = vc_single(
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out_path = opt_path + '/' + file
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0, file_path, f0up_key, None, f0method, index_path, index_rate
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)
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out_path = opt_path + "/" + file
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wavfile.write(out_path, tgt_sr, wav_opt)
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wavfile.write(out_path, tgt_sr, wav_opt)
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