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https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI.git
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Format code (#455)
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52c97ed464
15
MDXNet.py
15
MDXNet.py
@ -206,25 +206,28 @@ class Predictor:
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mix = mix.T
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sources = self.demix(mix.T)
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opt = sources[0].T
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if(format in ["wav", "flac"]):
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sf.write("%s/%s_main_vocal.%s" % (vocal_root, basename, format), mix - opt, rate)
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if format in ["wav", "flac"]:
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sf.write(
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"%s/%s_main_vocal.%s" % (vocal_root, basename, format), mix - opt, rate
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)
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sf.write("%s/%s_others.%s" % (others_root, basename, format), opt, rate)
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else:
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path_vocal="%s/%s_main_vocal.wav" % (vocal_root, basename)
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path_other="%s/%s_others.wav" % (others_root, basename)
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path_vocal = "%s/%s_main_vocal.wav" % (vocal_root, basename)
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path_other = "%s/%s_others.wav" % (others_root, basename)
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sf.write(path_vocal, mix - opt, rate)
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sf.write(path_other, opt, rate)
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if (os.path.exists(path_vocal)):
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if os.path.exists(path_vocal):
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os.system(
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"ffmpeg -i %s -vn %s -q:a 2 -y"
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% (path_vocal, path_vocal[:-4] + ".%s" % format)
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)
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if (os.path.exists(path_other)):
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if os.path.exists(path_other):
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os.system(
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"ffmpeg -i %s -vn %s -q:a 2 -y"
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% (path_other, path_other[:-4] + ".%s" % format)
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)
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class MDXNetDereverb:
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def __init__(self, chunks):
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self.onnx = "uvr5_weights/onnx_dereverb_By_FoxJoy"
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8
gui.py
8
gui.py
@ -584,10 +584,14 @@ class GUI:
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if d["max_output_channels"] > 0
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]
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input_devices_indices = [
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d["index"] if "index" in d else d["name"] for d in devices if d["max_input_channels"] > 0
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d["index"] if "index" in d else d["name"]
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for d in devices
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if d["max_input_channels"] > 0
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]
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output_devices_indices = [
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d["index"] if "index" in d else d["name"] for d in devices if d["max_output_channels"] > 0
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d["index"] if "index" in d else d["name"]
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for d in devices
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if d["max_output_channels"] > 0
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]
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return (
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input_devices,
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@ -272,20 +272,20 @@ def vc_multi(
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if "Success" in info:
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try:
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tgt_sr, audio_opt = opt
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if (format1 in ["wav", "flac"]):
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if format1 in ["wav", "flac"]:
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sf.write(
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"%s/%s.%s" % (opt_root, os.path.basename(path), format1),
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audio_opt,
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tgt_sr,
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)
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else:
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path="%s/%s.wav" % (opt_root, os.path.basename(path))
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path = "%s/%s.wav" % (opt_root, os.path.basename(path))
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sf.write(
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path,
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audio_opt,
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tgt_sr,
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)
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if (os.path.exists(path)):
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if os.path.exists(path):
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os.system(
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"ffmpeg -i %s -vn %s -q:a 2 -y"
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% (path, path[:-4] + ".%s" % format1)
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@ -123,7 +123,7 @@ class _audio_pre_:
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else:
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wav_instrument = spec_utils.cmb_spectrogram_to_wave(y_spec_m, self.mp)
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print("%s instruments done" % name)
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if(format in ["wav","flac"]):
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if format in ["wav", "flac"]:
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sf.write(
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os.path.join(
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ins_root,
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@ -133,18 +133,18 @@ class _audio_pre_:
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self.mp.param["sr"],
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) #
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else:
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path=os.path.join(
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ins_root, "instrument_{}_{}.wav".format(name, self.data["agg"])
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)
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path = os.path.join(
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ins_root, "instrument_{}_{}.wav".format(name, self.data["agg"])
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)
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sf.write(
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path ,
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path,
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(np.array(wav_instrument) * 32768).astype("int16"),
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self.mp.param["sr"],
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)
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if(os.path.exists(path)):
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if os.path.exists(path):
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os.system(
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"ffmpeg -i %s -vn %s -q:a 2 -y"
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% (path, path[:-4]+".%s"%format)
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% (path, path[:-4] + ".%s" % format)
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)
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if vocal_root is not None:
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if self.data["high_end_process"].startswith("mirroring"):
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@ -157,29 +157,31 @@ class _audio_pre_:
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else:
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wav_vocals = spec_utils.cmb_spectrogram_to_wave(v_spec_m, self.mp)
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print("%s vocals done" % name)
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if(format in ["wav","flac"]):
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if format in ["wav", "flac"]:
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sf.write(
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os.path.join(
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vocal_root, "vocal_{}_{}.{}".format(name, self.data["agg"], format)
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vocal_root,
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"vocal_{}_{}.{}".format(name, self.data["agg"], format),
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),
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(np.array(wav_vocals) * 32768).astype("int16"),
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self.mp.param["sr"],
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)
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else:
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path=os.path.join(
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vocal_root, "vocal_{}_{}.wav".format(name, self.data["agg"])
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)
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path = os.path.join(
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vocal_root, "vocal_{}_{}.wav".format(name, self.data["agg"])
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)
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sf.write(
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path ,
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path,
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(np.array(wav_vocals) * 32768).astype("int16"),
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self.mp.param["sr"],
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)
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if(os.path.exists(path)):
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if os.path.exists(path):
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os.system(
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"ffmpeg -i %s -vn %s -q:a 2 -y"
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% (path, path[:-4]+".%s"%format)
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% (path, path[:-4] + ".%s" % format)
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)
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class _audio_pre_new:
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def __init__(self, agg, model_path, device, is_half):
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self.model_path = model_path
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@ -288,7 +290,7 @@ class _audio_pre_new:
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else:
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wav_instrument = spec_utils.cmb_spectrogram_to_wave(y_spec_m, self.mp)
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print("%s instruments done" % name)
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if(format in ["wav","flac"]):
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if format in ["wav", "flac"]:
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sf.write(
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os.path.join(
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ins_root,
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@ -298,18 +300,18 @@ class _audio_pre_new:
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self.mp.param["sr"],
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) #
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else:
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path=os.path.join(
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ins_root, "instrument_{}_{}.wav".format(name, self.data["agg"])
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)
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path = os.path.join(
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ins_root, "instrument_{}_{}.wav".format(name, self.data["agg"])
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)
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sf.write(
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path ,
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path,
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(np.array(wav_instrument) * 32768).astype("int16"),
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self.mp.param["sr"],
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)
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if(os.path.exists(path)):
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if os.path.exists(path):
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os.system(
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"ffmpeg -i %s -vn %s -q:a 2 -y"
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% (path, path[:-4]+".%s"%format)
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% (path, path[:-4] + ".%s" % format)
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)
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if vocal_root is not None:
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if self.data["high_end_process"].startswith("mirroring"):
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@ -322,29 +324,31 @@ class _audio_pre_new:
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else:
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wav_vocals = spec_utils.cmb_spectrogram_to_wave(v_spec_m, self.mp)
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print("%s vocals done" % name)
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if(format in ["wav","flac"]):
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if format in ["wav", "flac"]:
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sf.write(
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os.path.join(
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vocal_root, "vocal_{}_{}.{}".format(name, self.data["agg"], format)
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vocal_root,
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"vocal_{}_{}.{}".format(name, self.data["agg"], format),
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),
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(np.array(wav_vocals) * 32768).astype("int16"),
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self.mp.param["sr"],
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)
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else:
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path=os.path.join(
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vocal_root, "vocal_{}_{}.wav".format(name, self.data["agg"])
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)
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path = os.path.join(
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vocal_root, "vocal_{}_{}.wav".format(name, self.data["agg"])
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)
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sf.write(
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path ,
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path,
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(np.array(wav_vocals) * 32768).astype("int16"),
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self.mp.param["sr"],
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)
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if(os.path.exists(path)):
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if os.path.exists(path):
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os.system(
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"ffmpeg -i %s -vn %s -q:a 2 -y"
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% (path, path[:-4]+".%s"%format)
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% (path, path[:-4] + ".%s" % format)
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)
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if __name__ == "__main__":
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device = "cuda"
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is_half = True
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@ -8,7 +8,7 @@ from i18n import I18nAuto
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i18n = I18nAuto()
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def savee(ckpt, sr, if_f0, name, epoch, version,hps):
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def savee(ckpt, sr, if_f0, name, epoch, version, hps):
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try:
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opt = OrderedDict()
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opt["weight"] = {}
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@ -16,8 +16,8 @@ def savee(ckpt, sr, if_f0, name, epoch, version,hps):
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if "enc_q" in key:
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continue
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opt["weight"][key] = ckpt[key].half()
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opt["config"]=[
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hpt.data.filter_length//2+1,
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opt["config"] = [
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hpt.data.filter_length // 2 + 1,
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32,
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hpt.model.inter_channels,
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hpt.model.hidden_channels,
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@ -34,7 +34,7 @@ def savee(ckpt, sr, if_f0, name, epoch, version,hps):
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hpt.model.upsample_kernel_sizes,
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hpt.model.spk_embed_dim,
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hpt.model.gin_channels,
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hpt.data.sampling_rate
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hpt.data.sampling_rate,
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]
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opt["info"] = "%sepoch" % epoch
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opt["sr"] = sr
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@ -559,7 +559,8 @@ def train_and_evaluate(
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hps.if_f0,
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hps.name + "_e%s" % epoch,
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epoch,
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hps.version,hps
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hps.version,
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hps,
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),
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)
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)
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@ -575,7 +576,11 @@ def train_and_evaluate(
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ckpt = net_g.state_dict()
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logger.info(
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"saving final ckpt:%s"
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% (savee(ckpt, hps.sample_rate, hps.if_f0, hps.name, epoch, hps.version,hps))
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% (
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savee(
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ckpt, hps.sample_rate, hps.if_f0, hps.name, epoch, hps.version, hps
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)
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)
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)
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sleep(1)
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os._exit(2333333)
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