From 6f8d02954f74f5d20cb775a3edeb9ffe8497f322 Mon Sep 17 00:00:00 2001 From: Ftps Date: Mon, 27 Nov 2023 17:01:43 +0900 Subject: [PATCH] uvr5 --- rvc/modules/uvr5/mdxnet.py | 4 +-- rvc/modules/uvr5/modules.py | 2 +- rvc/modules/uvr5/vr.py | 53 +++++++++++++++++-------------------- 3 files changed, 27 insertions(+), 32 deletions(-) diff --git a/rvc/modules/uvr5/mdxnet.py b/rvc/modules/uvr5/mdxnet.py index cddedb6..443bf36 100644 --- a/rvc/modules/uvr5/mdxnet.py +++ b/rvc/modules/uvr5/mdxnet.py @@ -9,7 +9,7 @@ from tqdm import tqdm cpu = torch.device("cpu") -logger = logging.getLogger(__name__) +logger: logging.Logger = logging.getLogger(__name__) class ConvTDFNetTrim: @@ -158,7 +158,7 @@ class Predictor: mix_waves = [] i = 0 while i < n_sample + pad: - waves = np.array(mix_p[:, i: i + model.chunk_size]) + waves = np.array(mix_p[:, i : i + model.chunk_size]) mix_waves.append(waves) i += gen_size mix_waves = torch.tensor(mix_waves, dtype=torch.float32).to(cpu) diff --git a/rvc/modules/uvr5/modules.py b/rvc/modules/uvr5/modules.py index 3f82686..ab4fe02 100644 --- a/rvc/modules/uvr5/modules.py +++ b/rvc/modules/uvr5/modules.py @@ -9,7 +9,7 @@ from rvc.configs.config import Config from rvc.modules.uvr5.mdxnet import MDXNetDereverb from rvc.modules.uvr5.vr import AudioPre, AudioPreDeEcho -logger = logging.getLogger(__name__) +logger: logging.Logger = logging.getLogger(__name__) config = Config() diff --git a/rvc/modules/uvr5/vr.py b/rvc/modules/uvr5/vr.py index f95b16a..6d99f69 100644 --- a/rvc/modules/uvr5/vr.py +++ b/rvc/modules/uvr5/vr.py @@ -27,7 +27,7 @@ class AudioPre: "agg": agg, "high_end_process": "mirroring", } - mp = ModelParameters("infer/lib/uvr5_pack/lib_v5/modelparams/4band_v2.json") + mp = ModelParameters("rvc/lib/uvr5_pack/lib_v5/modelparams/4band_v2.json") model = Nets.CascadedASPPNet(mp.param["bins"] * 2) cpk = torch.load(model_path, map_location="cpu") model.load_state_dict(cpk) @@ -43,23 +43,24 @@ class AudioPre: def _path_audio_( self, music_file, ins_root=None, vocal_root=None, format="flac", is_hp3=False ): - if ins_root is None and vocal_root is None: - return "No save root." name = os.path.basename(music_file) - if ins_root is not None: + if (ins_root and vocal_root) is None: + return "No save root." + else: os.makedirs(ins_root, exist_ok=True) - if vocal_root is not None: os.makedirs(vocal_root, exist_ok=True) + X_wave, y_wave, X_spec_s, y_spec_s = {}, {}, {}, {} bands_n = len(self.mp.param["band"]) # print(bands_n) for d in range(bands_n, 0, -1): bp = self.mp.param["band"][d] if d == bands_n: # high-end band + # librosa loading may be buggy for some audio. ffmpeg will solve this, but it's a pain ( X_wave[d], _, - ) = librosa.core.load( # 理论上librosa读取可能对某些音频有bug，应该上ffmpeg读取，但是太麻烦了弃坑 + ) = librosa.core.load( music_file, bp["sr"], False, @@ -121,7 +122,7 @@ class AudioPre: else: wav_instrument = spec_utils.cmb_spectrogram_to_wave(y_spec_m, self.mp) logger.info("%s instruments done" % name) - if is_hp3 == True: + if is_hp3: head = "vocal_" else: head = "instrument_" @@ -129,15 +130,13 @@ class AudioPre: sf.write( os.path.join( ins_root, - head + "{}_{}.{}".format(name, self.data["agg"], format), + head + f"{name}_{self.data['agg']}.{format}", ), (np.array(wav_instrument) * 32768).astype("int16"), self.mp.param["sr"], ) # else: - path = os.path.join( - ins_root, head + "{}_{}.wav".format(name, self.data["agg"]) - ) + path = os.path.join(ins_root, head + f"{name}_{self.data['agg']}.wav") sf.write( path, (np.array(wav_instrument) * 32768).astype("int16"), @@ -149,13 +148,10 @@ class AudioPre: if os.path.exists(opt_format_path): try: os.remove(path) - except: + except Exception: pass if vocal_root is not None: - if is_hp3 == True: - head = "instrument_" - else: - head = "vocal_" + head = "instrument_" if is_hp3 else "vocal_" if self.data["high_end_process"].startswith("mirroring"): input_high_end_ = spec_utils.mirroring( self.data["high_end_process"], v_spec_m, input_high_end, self.mp @@ -165,28 +161,26 @@ class AudioPre: ) else: wav_vocals = spec_utils.cmb_spectrogram_to_wave(v_spec_m, self.mp) - logger.info("%s vocals done" % name) + logger.info(f"{name} vocals done") if format in ["wav", "flac"]: sf.write( os.path.join( vocal_root, - head + "{}_{}.{}".format(name, self.data["agg"], format), + head + f"{name}_{self.data['agg']}.{format}", ), (np.array(wav_vocals) * 32768).astype("int16"), self.mp.param["sr"], ) else: - path = os.path.join( - vocal_root, head + "{}_{}.wav".format(name, self.data["agg"]) - ) + path = os.path.join(vocal_root, head + f"{name}_{self.data['agg']}.wav") sf.write( path, (np.array(wav_vocals) * 32768).astype("int16"), self.mp.param["sr"], ) if os.path.exists(path): - opt_format_path = path[:-4] + ".%s" % format - os.system("ffmpeg -i %s -vn %s -q:a 2 -y" % (path, opt_format_path)) + opt_format_path = path[:-4] + f".{format}" + os.system(f"ffmpeg -i {path} -vn {opt_format_path} -q:a 2 -y") if os.path.exists(opt_format_path): try: os.remove(path) @@ -207,7 +201,7 @@ class AudioPreDeEcho: "agg": agg, "high_end_process": "mirroring", } - mp = ModelParameters("infer/lib/uvr5_pack/lib_v5/modelparams/4band_v3.json") + mp = ModelParameters("rvc/lib/uvr5_pack/lib_v5/modelparams/4band_v3.json") nout = 64 if "DeReverb" in model_path else 48 model = CascadedNet(mp.param["bins"] * 2, nout) cpk = torch.load(model_path, map_location="cpu") @@ -224,23 +218,24 @@ class AudioPreDeEcho: def _path_audio_( self, music_file, vocal_root=None, ins_root=None, format="flac", is_hp3=False ): # 3个VR模型vocal和ins是反的 - if ins_root is None and vocal_root is None: - return "No save root." name = os.path.basename(music_file) - if ins_root is not None: + if (ins_root and vocal_root) is None: + return "No save root." + else: os.makedirs(ins_root, exist_ok=True) - if vocal_root is not None: os.makedirs(vocal_root, exist_ok=True) + X_wave, y_wave, X_spec_s, y_spec_s = {}, {}, {}, {} bands_n = len(self.mp.param["band"]) # print(bands_n) for d in range(bands_n, 0, -1): bp = self.mp.param["band"][d] if d == bands_n: # high-end band + # librosa loading may be buggy for some audio. ffmpeg will solve this, but it's a pain ( X_wave[d], _, - ) = librosa.core.load( # 理论上librosa读取可能对某些音频有bug，应该上ffmpeg读取，但是太麻烦了弃坑 + ) = librosa.core.load( music_file, bp["sr"], False,