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uvr_cli.py
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uvr_cli.py
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import argparse
import logging
import json
import sys
def main():
"""Main entry point for the CLI."""
logger = logging.getLogger(__name__)
parser = argparse.ArgumentParser(
description="Separate audio file into different stems.",
formatter_class=lambda prog: argparse.RawTextHelpFormatter(
prog, max_help_position=60
),
)
parser.add_argument(
"--audio_file",
nargs="?",
help="The audio file path to separate, in any common format.",
default=argparse.SUPPRESS,
)
debug_help = "Enable debug logging, equivalent to --log_level=debug."
env_info_help = "Print environment information and exit."
list_models_help = "List all supported models and exit."
log_level_help = "Log level, e.g. info, debug, warning (default: %(default)s)."
info_params = parser.add_argument_group("Info and Debugging")
info_params.add_argument("-d", "--debug", action="store_true", help=debug_help)
info_params.add_argument(
"-e", "--env_info", action="store_true", help=env_info_help
)
info_params.add_argument(
"-l", "--list_models", action="store_true", help=list_models_help
)
info_params.add_argument("--log_level", default="info", help=log_level_help)
model_filename_help = (
"model to use for separation (default: %(default)s). Example: -m 2_HP-UVR.pth"
)
output_format_help = "output format for separated files, any common format (default: %(default)s). Example: --output_format=MP3"
output_dir_help = "directory to write output files (default: <current dir>). Example: --output_dir=/app/separated"
model_file_dir_help = "model files directory (default: %(default)s). Example: --model_file_dir=/app/models"
io_params = parser.add_argument_group("Separation I/O Params")
io_params.add_argument(
"-m",
"--model_filename",
default="model_mel_band_roformer_ep_3005_sdr_11.4360.ckpt",
help=model_filename_help,
)
io_params.add_argument("--output_format", default="WAV", help=output_format_help)
io_params.add_argument("--output_dir", default=None, help=output_dir_help)
io_params.add_argument(
"--model_file_dir",
default="uvr/tmp/audio-separator-models/",
help=model_file_dir_help,
)
invert_spect_help = "invert secondary stem using spectogram (default: %(default)s). Example: --invert_spect"
normalization_help = "max peak amplitude to normalize input and output audio to (default: %(default)s). Example: --normalization=0.7"
single_stem_help = "output only single stem, e.g. Instrumental, Vocals, Drums, Bass, Guitar, Piano, Other. Example: --single_stem=Instrumental"
sample_rate_help = "modify the sample rate of the output audio (default: %(default)s). Example: --sample_rate=44100"
common_params = parser.add_argument_group("Common Separation Parameters")
common_params.add_argument(
"--invert_spect", action="store_true", help=invert_spect_help
)
common_params.add_argument(
"--normalization", type=float, default=0.9, help=normalization_help
)
common_params.add_argument("--single_stem", default=None, help=single_stem_help)
common_params.add_argument(
"--sample_rate", type=int, default=44100, help=sample_rate_help
)
mdx_segment_size_help = "larger consumes more resources, but may give better results (default: %(default)s). Example: --mdx_segment_size=256"
mdx_overlap_help = "amount of overlap between prediction windows, 0.001-0.999. higher is better but slower (default: %(default)s). Example: --mdx_overlap=0.25"
mdx_batch_size_help = "larger consumes more RAM but may process slightly faster (default: %(default)s). Example: --mdx_batch_size=4"
mdx_hop_length_help = "usually called stride in neural networks, only change if you know what you're doing (default: %(default)s). Example: --mdx_hop_length=1024"
mdx_enable_denoise_help = "enable denoising during separation (default: %(default)s). Example: --mdx_enable_denoise"
mdx_params = parser.add_argument_group("MDX Architecture Parameters")
mdx_params.add_argument(
"--mdx_segment_size", type=int, default=256, help=mdx_segment_size_help
)
mdx_params.add_argument(
"--mdx_overlap", type=float, default=0.25, help=mdx_overlap_help
)
mdx_params.add_argument(
"--mdx_batch_size", type=int, default=1, help=mdx_batch_size_help
)
mdx_params.add_argument(
"--mdx_hop_length", type=int, default=1024, help=mdx_hop_length_help
)
mdx_params.add_argument(
"--mdx_enable_denoise", action="store_true", help=mdx_enable_denoise_help
)
vr_batch_size_help = "number of batches to process at a time. higher = more RAM, slightly faster processing (default: %(default)s). Example: --vr_batch_size=16"
vr_window_size_help = "balance quality and speed. 1024 = fast but lower, 320 = slower but better quality. (default: %(default)s). Example: --vr_window_size=320"
vr_aggression_help = "intensity of primary stem extraction, -100 - 100. typically 5 for vocals & instrumentals (default: %(default)s). Example: --vr_aggression=2"
vr_enable_tta_help = "enable Test-Time-Augmentation; slow but improves quality (default: %(default)s). Example: --vr_enable_tta"
vr_high_end_process_help = "mirror the missing frequency range of the output (default: %(default)s). Example: --vr_high_end_process"
vr_enable_post_process_help = "identify leftover artifacts within vocal output; may improve separation for some songs (default: %(default)s). Example: --vr_enable_post_process"
vr_post_process_threshold_help = "threshold for post_process feature: 0.1-0.3 (default: %(default)s). Example: --vr_post_process_threshold=0.1"
vr_params = parser.add_argument_group("VR Architecture Parameters")
vr_params.add_argument(
"--vr_batch_size", type=int, default=4, help=vr_batch_size_help
)
vr_params.add_argument(
"--vr_window_size", type=int, default=512, help=vr_window_size_help
)
vr_params.add_argument(
"--vr_aggression", type=int, default=5, help=vr_aggression_help
)
vr_params.add_argument(
"--vr_enable_tta", action="store_true", help=vr_enable_tta_help
)
vr_params.add_argument(
"--vr_high_end_process", action="store_true", help=vr_high_end_process_help
)
vr_params.add_argument(
"--vr_enable_post_process",
action="store_true",
help=vr_enable_post_process_help,
)
vr_params.add_argument(
"--vr_post_process_threshold",
type=float,
default=0.2,
help=vr_post_process_threshold_help,
)
demucs_segment_size_help = "size of segments into which the audio is split, 1-100. higher = slower but better quality (default: %(default)s). Example: --demucs_segment_size=256"
demucs_shifts_help = "number of predictions with random shifts, higher = slower but better quality (default: %(default)s). Example: --demucs_shifts=4"
demucs_overlap_help = "overlap between prediction windows, 0.001-0.999. higher = slower but better quality (default: %(default)s). Example: --demucs_overlap=0.25"
demucs_segments_enabled_help = "enable segment-wise processing (default: %(default)s). Example: --demucs_segments_enabled=False"
demucs_params = parser.add_argument_group("Demucs Architecture Parameters")
demucs_params.add_argument(
"--demucs_segment_size",
type=str,
default="Default",
help=demucs_segment_size_help,
)
demucs_params.add_argument(
"--demucs_shifts", type=int, default=2, help=demucs_shifts_help
)
demucs_params.add_argument(
"--demucs_overlap", type=float, default=0.25, help=demucs_overlap_help
)
demucs_params.add_argument(
"--demucs_segments_enabled",
type=bool,
default=True,
help=demucs_segments_enabled_help,
)
mdxc_segment_size_help = "larger consumes more resources, but may give better results (default: %(default)s). Example: --mdxc_segment_size=256"
mdxc_override_model_segment_size_help = "override model default segment size instead of using the model default value. Example: --mdxc_override_model_segment_size"
mdxc_overlap_help = "amount of overlap between prediction windows, 2-50. higher is better but slower (default: %(default)s). Example: --mdxc_overlap=8"
mdxc_batch_size_help = "larger consumes more RAM but may process slightly faster (default: %(default)s). Example: --mdxc_batch_size=4"
mdxc_pitch_shift_help = "shift audio pitch by a number of semitones while processing. may improve output for deep/high vocals. (default: %(default)s). Example: --mdxc_pitch_shift=2"
mdxc_params = parser.add_argument_group("MDXC Architecture Parameters")
mdxc_params.add_argument(
"--mdxc_segment_size", type=int, default=256, help=mdxc_segment_size_help
)
mdxc_params.add_argument(
"--mdxc_override_model_segment_size",
action="store_true",
help=mdxc_override_model_segment_size_help,
)
mdxc_params.add_argument(
"--mdxc_overlap", type=int, default=8, help=mdxc_overlap_help
)
mdxc_params.add_argument(
"--mdxc_batch_size", type=int, default=1, help=mdxc_batch_size_help
)
mdxc_params.add_argument(
"--mdxc_pitch_shift", type=int, default=0, help=mdxc_pitch_shift_help
)
args = parser.parse_args()
if args.debug:
log_level = logging.DEBUG
else:
log_level = getattr(logging, args.log_level.upper())
logger.setLevel(log_level)
from uvr.separator import Separator
if args.env_info:
separator = Separator()
sys.exit(0)
if args.list_models:
separator = Separator()
print(
json.dumps(separator.list_supported_model_files(), indent=4, sort_keys=True)
)
sys.exit(0)
if not hasattr(args, "audio_file"):
parser.print_help()
sys.exit(1)
separator = Separator(
log_level=log_level,
model_file_dir=args.model_file_dir,
output_dir=args.output_dir,
output_format=args.output_format,
normalization_threshold=args.normalization,
output_single_stem=args.single_stem,
invert_using_spec=args.invert_spect,
sample_rate=args.sample_rate,
mdx_params={
"hop_length": args.mdx_hop_length,
"segment_size": args.mdx_segment_size,
"overlap": args.mdx_overlap,
"batch_size": args.mdx_batch_size,
"enable_denoise": args.mdx_enable_denoise,
},
vr_params={
"batch_size": args.vr_batch_size,
"window_size": args.vr_window_size,
"aggression": args.vr_aggression,
"enable_tta": args.vr_enable_tta,
"enable_post_process": args.vr_enable_post_process,
"post_process_threshold": args.vr_post_process_threshold,
"high_end_process": args.vr_high_end_process,
},
demucs_params={
"segment_size": args.demucs_segment_size,
"shifts": args.demucs_shifts,
"overlap": args.demucs_overlap,
"segments_enabled": args.demucs_segments_enabled,
},
mdxc_params={
"segment_size": args.mdxc_segment_size,
"batch_size": args.mdxc_batch_size,
"overlap": args.mdxc_overlap,
"override_model_segment_size": args.mdxc_override_model_segment_size,
"pitch_shift": args.mdxc_pitch_shift,
},
)
separator.load_model(model_filename=args.model_filename)
output_files = separator.separate(args.audio_file)
logger.info(f"Separation complete! Output file(s): {' '.join(output_files)}")
if __name__ == "__main__":
main()