87 lines
2.6 KiB
Python
87 lines
2.6 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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Author: C0ffymachyne
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License: GPLv3
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Version: 1.0.0
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Description:
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Varios normalizatin techqniues node
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"""
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import torch
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from typing import Dict, Any, Tuple, Union
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from ..core.io import audio_to_comfy_3d, audio_from_comfy_2d
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from ..core.loudness import (
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rms_normalization,
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lufs_normalization,
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peak_normalization,
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automatic_gain_control,
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)
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class SignalProcessingNormalizer:
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@classmethod
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def INPUT_TYPES(cls) -> Dict[str, Any]:
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return {
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"required": {
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"audio_input": ("AUDIO",),
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"mode": (["lufs", "rms", "peak", "auto"],),
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"target_rms": (
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"FLOAT",
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{"default": 0.1, "min": 0, "max": 10.0, "step": 0.1},
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),
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"target_lufs_db": (
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"FLOAT",
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{"default": -14.0, "min": -100, "max": 100.0, "step": 0.1},
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),
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"target_peak": (
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"FLOAT",
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{"default": 0.9, "min": 0.0, "max": 1.0, "step": 0.1},
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),
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"target_auto": (
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"FLOAT",
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{"default": 0.7, "min": 0.0, "max": 1.0, "step": 0.1},
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),
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"target_auto_alpha": (
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"FLOAT",
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{"default": 0.1, "min": 0.0, "max": 10.0, "step": 0.1},
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),
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},
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}
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RETURN_TYPES = ("AUDIO",)
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RETURN_NAMES = ("processed_audio",)
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CATEGORY = "Signal Processing"
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FUNCTION = "process"
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def process(
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self,
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audio_input: Dict[str, Union[torch.Tensor, int]],
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mode: str,
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target_rms: float,
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target_lufs_db: float,
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target_peak: float,
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target_auto: float,
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target_auto_alpha: float,
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) -> Tuple[Dict[str, torch.Tensor]]:
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waveform, sample_rate = audio_from_comfy_2d(audio_input, try_gpu=True)
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if mode == "rms":
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processed_waveform = rms_normalization(waveform, target_rms)
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elif mode == "lufs":
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processed_waveform = lufs_normalization(
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waveform, sample_rate, target_lufs_db
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)
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elif mode == "peak":
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processed_waveform = peak_normalization(waveform, target_peak)
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elif mode == "auto":
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processed_waveform = automatic_gain_control(
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waveform, target_auto, target_auto_alpha
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)
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else:
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processed_waveform = waveform
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return audio_to_comfy_3d(processed_waveform, sample_rate)
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