From f9d9abd8709c7c560e06eea1adce00bc8dbe83ff Mon Sep 17 00:00:00 2001 From: "Codename;0" <139770129+codename0og@users.noreply.github.com> Date: Sat, 11 Jan 2025 07:28:45 +0100 Subject: [PATCH] update --- rvc/train/preprocess/preprocess.py | 32 +++++++++++++++--------------- 1 file changed, 16 insertions(+), 16 deletions(-) diff --git a/rvc/train/preprocess/preprocess.py b/rvc/train/preprocess/preprocess.py index edc02f8..efd563a 100644 --- a/rvc/train/preprocess/preprocess.py +++ b/rvc/train/preprocess/preprocess.py @@ -26,6 +26,7 @@ logging.getLogger("numba.core.interpreter").setLevel(logging.WARNING) OVERLAP = 0.3 +PERCENTAGE = 3.0 MAX_AMPLITUDE = 0.9 ALPHA = 0.75 HIGH_PASS_CUTOFF = 48 @@ -34,7 +35,7 @@ class PreProcess: - def __init__(self, sr: int, exp_dir: str, per: float): + def __init__(self, sr: int, exp_dir: str): self.slicer = Slicer( sr=sr, threshold=-42, @@ -47,7 +48,6 @@ def __init__(self, sr: int, exp_dir: str, per: float): self.b_high, self.a_high = signal.butter( N=5, Wn=HIGH_PASS_CUTOFF, btype="high", fs=self.sr ) - self.per = per self.exp_dir = exp_dir self.device = "cpu" self.gt_wavs_dir = os.path.join(exp_dir, "sliced_audios") @@ -166,11 +166,14 @@ def process_audio( for audio_segment in self.slicer.slice(audio): i = 0 while True: - start = int(self.sr * (self.per - OVERLAP) * i) + start = int(self.sr * (PERCENTAGE - OVERLAP) * i) i += 1 - if len(audio_segment[start:]) > (self.per + OVERLAP) * self.sr: + if ( + len(audio_segment[start:]) + > (PERCENTAGE + OVERLAP) * self.sr + ): tmp_audio = audio_segment[ - start : start + int(self.per * self.sr) + start : start + int(PERCENTAGE * self.sr) ] self.process_audio_segment( tmp_audio, @@ -250,7 +253,6 @@ def preprocess_training_set( sr: int, num_processes: int, exp_dir: str, - per: float, cut_preprocess: str, process_effects: bool, noise_reduction: bool, @@ -259,7 +261,7 @@ def preprocess_training_set( overlap_len: float, ): start_time = time.time() - pp = PreProcess(sr, exp_dir, per) + pp = PreProcess(sr, exp_dir) print(f"Starting preprocess with {num_processes} processes...") files = [] @@ -317,25 +319,23 @@ def preprocess_training_set( experiment_directory = str(sys.argv[1]) input_root = str(sys.argv[2]) sample_rate = int(sys.argv[3]) - percentage = float(sys.argv[4]) - num_processes = sys.argv[5] + num_processes = sys.argv[4] if num_processes.lower() == "none": num_processes = multiprocessing.cpu_count() else: num_processes = int(num_processes) - cut_preprocess = str(sys.argv[6]) - process_effects = strtobool(sys.argv[7]) - noise_reduction = strtobool(sys.argv[8]) - reduction_strength = float(sys.argv[9]) - chunk_len = float(sys.argv[10]) - overlap_len = float(sys.argv[11]) + cut_preprocess = str(sys.argv[5]) + process_effects = strtobool(sys.argv[6]) + noise_reduction = strtobool(sys.argv[7]) + reduction_strength = float(sys.argv[8]) + chunk_len = float(sys.argv[9]) + overlap_len = float(sys.argv[10]) preprocess_training_set( input_root, sample_rate, num_processes, experiment_directory, - percentage, cut_preprocess, process_effects, noise_reduction,