Format code (#877)
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@ -79,9 +79,7 @@ class FeatureInput(object):
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from lib.rmvpe import RMVPE
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print("loading rmvpe model")
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self.model_rmvpe = RMVPE(
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"rmvpe.pt", is_half=False, device="cpu"
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)
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self.model_rmvpe = RMVPE("rmvpe.pt", is_half=False, device="cpu")
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f0 = self.model_rmvpe.infer_from_audio(x, thred=0.03)
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return f0
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@ -23,7 +23,6 @@ def printt(strr):
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f.flush()
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class FeatureInput(object):
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def __init__(self, samplerate=16000, hop_size=160):
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self.fs = samplerate
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@ -38,14 +37,12 @@ class FeatureInput(object):
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def compute_f0(self, path, f0_method):
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x = load_audio(path, self.fs)
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p_len = x.shape[0] // self.hop
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if(f0_method=="rmvpe"):
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if f0_method == "rmvpe":
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if hasattr(self, "model_rmvpe") == False:
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from lib.rmvpe import RMVPE
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print("loading rmvpe model")
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self.model_rmvpe = RMVPE(
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"rmvpe.pt", is_half=True, device="cuda"
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)
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self.model_rmvpe = RMVPE("rmvpe.pt", is_half=True, device="cuda")
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f0 = self.model_rmvpe.infer_from_audio(x, thred=0.03)
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return f0
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@ -117,7 +114,7 @@ if __name__ == "__main__":
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opt_path2 = "%s/%s" % (opt_root2, name)
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paths.append([inp_path, opt_path1, opt_path2])
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try:
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featureInput.go(paths[i_part::n_part],"rmvpe")
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featureInput.go(paths[i_part::n_part], "rmvpe")
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except:
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printt("f0_all_fail-%s" % (traceback.format_exc()))
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# ps = []
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87
infer-web.py
87
infer-web.py
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@ -43,9 +43,7 @@ logging.getLogger("numba").setLevel(logging.WARNING)
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now_dir = os.getcwd()
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tmp = os.path.join(now_dir, "TEMP")
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shutil.rmtree(tmp, ignore_errors=True)
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shutil.rmtree(
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"%s/runtime/Lib/site-packages/infer_pack" % (now_dir), ignore_errors=True
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)
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shutil.rmtree("%s/runtime/Lib/site-packages/infer_pack" % (now_dir), ignore_errors=True)
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shutil.rmtree("%s/runtime/Lib/site-packages/uvr5_pack" % (now_dir), ignore_errors=True)
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os.makedirs(tmp, exist_ok=True)
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os.makedirs(os.path.join(now_dir, "logs"), exist_ok=True)
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@ -570,13 +568,13 @@ def preprocess_dataset(trainset_dir, exp_dir, sr, n_p):
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# but2.click(extract_f0,[gpus6,np7,f0method8,if_f0_3,trainset_dir4],[info2])
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def extract_f0_feature(gpus, n_p, f0method, if_f0, exp_dir, version19,gpus_rmvpe):
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def extract_f0_feature(gpus, n_p, f0method, if_f0, exp_dir, version19, gpus_rmvpe):
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gpus = gpus.split("-")
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os.makedirs("%s/logs/%s" % (now_dir, exp_dir), exist_ok=True)
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f = open("%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "w")
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f.close()
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if if_f0:
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if(f0method!="rmvpe_gpu"):
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if f0method != "rmvpe_gpu":
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cmd = config.python_cmd + ' extract_f0_print.py "%s/logs/%s" %s %s' % (
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now_dir,
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exp_dir,
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@ -584,7 +582,9 @@ def extract_f0_feature(gpus, n_p, f0method, if_f0, exp_dir, version19,gpus_rmvpe
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f0method,
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)
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print(cmd)
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p = Popen(cmd, shell=True, cwd=now_dir) # , stdin=PIPE, stdout=PIPE,stderr=PIPE
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p = Popen(
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cmd, shell=True, cwd=now_dir
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) # , stdin=PIPE, stdout=PIPE,stderr=PIPE
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###煞笔gr, popen read都非得全跑完了再一次性读取, 不用gr就正常读一句输出一句;只能额外弄出一个文本流定时读
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done = [False]
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threading.Thread(
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@ -602,7 +602,9 @@ def extract_f0_feature(gpus, n_p, f0method, if_f0, exp_dir, version19,gpus_rmvpe
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sleep(1)
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if done[0]:
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break
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with open("%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r") as f:
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with open(
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"%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r"
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) as f:
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log = f.read()
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print(log)
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yield log
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@ -612,16 +614,9 @@ def extract_f0_feature(gpus, n_p, f0method, if_f0, exp_dir, version19,gpus_rmvpe
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ps = []
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for idx, n_g in enumerate(gpus_rmvpe):
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cmd = (
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config.python_cmd
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+ ' extract_f0_rmvpe.py %s %s %s "%s/logs/%s" %s '
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% (
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leng,
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idx,
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n_g,
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now_dir,
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exp_dir,
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config.is_half
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)
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config.python_cmd
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+ ' extract_f0_rmvpe.py %s %s %s "%s/logs/%s" %s '
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% (leng, idx, n_g, now_dir, exp_dir, config.is_half)
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)
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print(cmd)
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p = Popen(
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@ -638,12 +633,16 @@ def extract_f0_feature(gpus, n_p, f0method, if_f0, exp_dir, version19,gpus_rmvpe
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),
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).start()
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while 1:
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with open("%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r") as f:
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with open(
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"%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r"
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) as f:
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yield (f.read())
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sleep(1)
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if done[0]:
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break
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with open("%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r") as f:
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with open(
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"%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir), "r"
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) as f:
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log = f.read()
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print(log)
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yield log
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@ -1037,7 +1036,8 @@ def train1key(
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gpus16,
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if_cache_gpu17,
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if_save_every_weights18,
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version19,gpus_rmvpe
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version19,
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gpus_rmvpe,
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):
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infos = []
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@ -1074,7 +1074,7 @@ def train1key(
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open(extract_f0_feature_log_path, "w")
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if if_f0_3:
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yield get_info_str("step2a:正在提取音高")
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if(f0method8!="rmvpe_gpu"):
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if f0method8 != "rmvpe_gpu":
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cmd = config.python_cmd + ' extract_f0_print.py "%s" %s %s' % (
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model_log_dir,
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np7,
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@ -1088,16 +1088,12 @@ def train1key(
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leng = len(gpus_rmvpe)
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ps = []
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for idx, n_g in enumerate(gpus_rmvpe):
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cmd = (
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config.python_cmd
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+ ' extract_f0_rmvpe.py %s %s %s "%s" %s '
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% (
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leng,
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idx,
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n_g,
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model_log_dir,
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config.is_half
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)
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cmd = config.python_cmd + ' extract_f0_rmvpe.py %s %s %s "%s" %s ' % (
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leng,
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idx,
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n_g,
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model_log_dir,
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config.is_half,
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)
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yield get_info_str(cmd)
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p = Popen(
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@ -1318,11 +1314,15 @@ def change_info_(ckpt_path):
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traceback.print_exc()
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return {"__type__": "update"}, {"__type__": "update"}, {"__type__": "update"}
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def change_f0_method(f0method8):
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if(f0method8=="rmvpe_gpu"):visible=True
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else:visible=False
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if f0method8 == "rmvpe_gpu":
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visible = True
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else:
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visible = False
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return {"visible": visible, "__type__": "update"}
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def export_onnx(ModelPath, ExportedPath):
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global cpt
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cpt = torch.load(ModelPath, map_location="cpu")
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@ -1755,10 +1755,12 @@ with gr.Blocks(title="RVC WebUI") as app:
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interactive=True,
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)
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gpus_rmvpe = gr.Textbox(
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label=i18n("rmvpe卡号配置：以-分隔输入使用的不同进程卡号,例如0-0-1使用在卡0上跑2个进程并在卡1上跑1个进程"),
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value="%s-%s"%(gpus,gpus),
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label=i18n(
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"rmvpe卡号配置：以-分隔输入使用的不同进程卡号,例如0-0-1使用在卡0上跑2个进程并在卡1上跑1个进程"
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),
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value="%s-%s" % (gpus, gpus),
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interactive=True,
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visible=True
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visible=True,
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)
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but2 = gr.Button(i18n("特征提取"), variant="primary")
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info2 = gr.Textbox(label=i18n("输出信息"), value="", max_lines=8)
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@ -1769,7 +1771,15 @@ with gr.Blocks(title="RVC WebUI") as app:
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)
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but2.click(
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extract_f0_feature,
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[gpus6, np7, f0method8, if_f0_3, exp_dir1, version19,gpus_rmvpe],
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[
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gpus6,
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np7,
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f0method8,
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if_f0_3,
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exp_dir1,
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version19,
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gpus_rmvpe,
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],
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[info2],
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)
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with gr.Group():
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@ -1894,7 +1904,8 @@ with gr.Blocks(title="RVC WebUI") as app:
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gpus16,
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if_cache_gpu17,
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if_save_every_weights18,
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version19,gpus_rmvpe
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version19,
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gpus_rmvpe,
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],
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info3,
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)
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119
infer_cli.py
119
infer_cli.py
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@ -1,4 +1,5 @@
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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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sys.path.append(now_dir)
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import argparse
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@ -9,35 +10,36 @@ import numpy as np
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from multiprocessing import cpu_count
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####
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#USAGE
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# USAGE
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#
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#In your Terminal or CMD or whatever
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#python infer_cli.py [TRANSPOSE_VALUE] "[INPUT_PATH]" "[OUTPUT_PATH]" "[MODEL_PATH]" "[INDEX_FILE_PATH]" "[INFERENCE_DEVICE]" "[METHOD]"
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# In your Terminal or CMD or whatever
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# python infer_cli.py [TRANSPOSE_VALUE] "[INPUT_PATH]" "[OUTPUT_PATH]" "[MODEL_PATH]" "[INDEX_FILE_PATH]" "[INFERENCE_DEVICE]" "[METHOD]"
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using_cli = False
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device = "cuda:0"
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is_half = False
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if(len(sys.argv) > 0):
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f0_up_key=int(sys.argv[1]) #transpose value
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input_path=sys.argv[2]
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output_path=sys.argv[3]
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model_path=sys.argv[4]
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file_index=sys.argv[5] #.index file
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device=sys.argv[6]
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f0_method=sys.argv[7] #pm or harvest or crepe
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if len(sys.argv) > 0:
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f0_up_key = int(sys.argv[1]) # transpose value
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input_path = sys.argv[2]
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output_path = sys.argv[3]
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model_path = sys.argv[4]
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file_index = sys.argv[5] # .index file
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device = sys.argv[6]
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f0_method = sys.argv[7] # pm or harvest or crepe
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using_cli = True
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#file_index2=sys.argv[8]
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#index_rate=float(sys.argv[10]) #search feature ratio
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#filter_radius=float(sys.argv[11]) #median filter
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#resample_sr=float(sys.argv[12]) #resample audio in post processing
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#rms_mix_rate=float(sys.argv[13]) #search feature
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# file_index2=sys.argv[8]
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# index_rate=float(sys.argv[10]) #search feature ratio
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# filter_radius=float(sys.argv[11]) #median filter
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# resample_sr=float(sys.argv[12]) #resample audio in post processing
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# rms_mix_rate=float(sys.argv[13]) #search feature
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print(sys.argv)
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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.is_half = is_half
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self.n_cpu = 0
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@ -113,8 +115,9 @@ class Config:
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return x_pad, x_query, x_center, x_max
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config=Config(device,is_half)
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now_dir=os.getcwd()
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config = Config(device, is_half)
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now_dir = os.getcwd()
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sys.path.append(now_dir)
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from vc_infer_pipeline import VC
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from infer_pack.models import SynthesizerTrnMs256NSFsid, SynthesizerTrnMs256NSFsid_nono
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@ -122,7 +125,9 @@ from my_utils import load_audio
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from fairseq import checkpoint_utils
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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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global hubert_model
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models, _, _ = checkpoint_utils.load_model_ensemble_and_task(
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@ -137,41 +142,42 @@ def load_hubert():
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hubert_model = hubert_model.float()
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hubert_model.eval()
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def vc_single(
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sid=0,
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input_audio_path=None,
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f0_up_key=0,
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f0_up_key=0,
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f0_file=None,
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f0_method="pm",
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file_index="", #.index file
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f0_method="pm",
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file_index="", # .index file
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file_index2="",
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# file_big_npy,
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index_rate=1.0,
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filter_radius=3,
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resample_sr=0,
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rms_mix_rate=1.0,
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index_rate=1.0,
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filter_radius=3,
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resample_sr=0,
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rms_mix_rate=1.0,
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model_path="",
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output_path="",
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protect=0.33
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protect=0.33,
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):
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global tgt_sr, net_g, vc, hubert_model, version
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get_vc(model_path)
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if input_audio_path is None:
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return "You need to upload an audio file", None
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f0_up_key = int(f0_up_key)
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audio = load_audio(input_audio_path, 16000)
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audio_max = np.abs(audio).max() / 0.95
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if audio_max > 1:
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audio /= audio_max
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times = [0, 0, 0]
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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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file_index = (
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(
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file_index.strip(" ")
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@ -184,7 +190,7 @@ def vc_single(
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if file_index != ""
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else file_index2
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)
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audio_opt = vc.pipeline(
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hubert_model,
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net_g,
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@ -204,32 +210,49 @@ def vc_single(
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rms_mix_rate,
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version,
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f0_file=f0_file,
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protect=protect
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protect=protect,
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)
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wavfile.write(output_path, tgt_sr, audio_opt)
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return('processed')
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return "processed"
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def get_vc(model_path):
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global n_spk,tgt_sr,net_g,vc,cpt,device,is_half, version
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print("loading pth %s"%model_path)
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global n_spk, tgt_sr, net_g, vc, cpt, device, is_half, version
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print("loading pth %s" % model_path)
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cpt = torch.load(model_path, map_location="cpu")
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tgt_sr = cpt["config"][-1]
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cpt["config"][-3]=cpt["weight"]["emb_g.weight"].shape[0]#n_spk
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if_f0=cpt.get("f0",1)
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cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0] # n_spk
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if_f0 = cpt.get("f0", 1)
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version = cpt.get("version", "v1")
|
||||
if(if_f0==1):
|
||||
if if_f0 == 1:
|
||||
net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=is_half)
|
||||
else:
|
||||
net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
|
||||
del net_g.enc_q
|
||||
print(net_g.load_state_dict(cpt["weight"], strict=False))
|
||||
net_g.eval().to(device)
|
||||
if (is_half):net_g = net_g.half()
|
||||
else:net_g = net_g.float()
|
||||
if is_half:
|
||||
net_g = net_g.half()
|
||||
else:
|
||||
net_g = net_g.float()
|
||||
vc = VC(tgt_sr, config)
|
||||
n_spk=cpt["config"][-3]
|
||||
n_spk = cpt["config"][-3]
|
||||
# return {"visible": True,"maximum": n_spk, "__type__": "update"}
|
||||
|
||||
if(using_cli):
|
||||
vc_single(sid=0,input_audio_path=input_path,f0_up_key=f0_up_key,f0_file=None,f0_method=f0_method,file_index=file_index,file_index2="",index_rate=1,filter_radius=3,resample_sr=0,rms_mix_rate=0,model_path=model_path,output_path=output_path)
|
||||
|
||||
if using_cli:
|
||||
vc_single(
|
||||
sid=0,
|
||||
input_audio_path=input_path,
|
||||
f0_up_key=f0_up_key,
|
||||
f0_file=None,
|
||||
f0_method=f0_method,
|
||||
file_index=file_index,
|
||||
file_index2="",
|
||||
index_rate=1,
|
||||
filter_radius=3,
|
||||
resample_sr=0,
|
||||
rms_mix_rate=0,
|
||||
model_path=model_path,
|
||||
output_path=output_path,
|
||||
)
|
||||
|
|
|
|||
|
|
@ -1,4 +1,5 @@
|
|||
import os,sys
|
||||
import os, sys
|
||||
|
||||
now_dir = os.getcwd()
|
||||
sys.path.append(os.path.join(now_dir))
|
||||
sys.path.append(os.path.join(now_dir, "train"))
|
||||
|
|
|
|||
Loading…
Reference in New Issue