Add new audio nodes (#9908)

* Add new audio nodes

- TrimAudioDuration
- SplitAudioChannels
- AudioConcat
- AudioMerge
- AudioAdjustVolume

* Update nodes_audio.py

* Add EmptyAudio -node

* Change duration to Float (allows sub seconds)
This commit is contained in:
Jukka Seppänen 2025-09-25 01:59:29 +03:00 committed by GitHub
parent 341b4adefd
commit fd79d32f38
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194

View File

@ -11,6 +11,7 @@ import json
import random
import hashlib
import node_helpers
import logging
from comfy.cli_args import args
from comfy.comfy_types import FileLocator
@ -364,6 +365,216 @@ class RecordAudio:
return (audio, )
class TrimAudioDuration:
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"audio": ("AUDIO",),
"start_index": ("FLOAT", {"default": 0.0, "min": -0xffffffffffffffff, "max": 0xffffffffffffffff, "step": 0.01, "tooltip": "Start time in seconds, can be negative to count from the end (supports sub-seconds)."}),
"duration": ("FLOAT", {"default": 60.0, "min": 0.0, "step": 0.01, "tooltip": "Duration in seconds"}),
},
}
FUNCTION = "trim"
RETURN_TYPES = ("AUDIO",)
CATEGORY = "audio"
DESCRIPTION = "Trim audio tensor into chosen time range."
def trim(self, audio, start_index, duration):
waveform = audio["waveform"]
sample_rate = audio["sample_rate"]
audio_length = waveform.shape[-1]
if start_index < 0:
start_frame = audio_length + int(round(start_index * sample_rate))
else:
start_frame = int(round(start_index * sample_rate))
start_frame = max(0, min(start_frame, audio_length - 1))
end_frame = start_frame + int(round(duration * sample_rate))
end_frame = max(0, min(end_frame, audio_length))
if start_frame >= end_frame:
raise ValueError("AudioTrim: Start time must be less than end time and be within the audio length.")
return ({"waveform": waveform[..., start_frame:end_frame], "sample_rate": sample_rate},)
class SplitAudioChannels:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"audio": ("AUDIO",),
}}
RETURN_TYPES = ("AUDIO", "AUDIO")
RETURN_NAMES = ("left", "right")
FUNCTION = "separate"
CATEGORY = "audio"
DESCRIPTION = "Separates the audio into left and right channels."
def separate(self, audio):
waveform = audio["waveform"]
sample_rate = audio["sample_rate"]
if waveform.shape[1] != 2:
raise ValueError("AudioSplit: Input audio has only one channel.")
left_channel = waveform[..., 0:1, :]
right_channel = waveform[..., 1:2, :]
return ({"waveform": left_channel, "sample_rate": sample_rate}, {"waveform": right_channel, "sample_rate": sample_rate})
def match_audio_sample_rates(waveform_1, sample_rate_1, waveform_2, sample_rate_2):
if sample_rate_1 != sample_rate_2:
if sample_rate_1 > sample_rate_2:
waveform_2 = torchaudio.functional.resample(waveform_2, sample_rate_2, sample_rate_1)
output_sample_rate = sample_rate_1
logging.info(f"Resampling audio2 from {sample_rate_2}Hz to {sample_rate_1}Hz for merging.")
else:
waveform_1 = torchaudio.functional.resample(waveform_1, sample_rate_1, sample_rate_2)
output_sample_rate = sample_rate_2
logging.info(f"Resampling audio1 from {sample_rate_1}Hz to {sample_rate_2}Hz for merging.")
else:
output_sample_rate = sample_rate_1
return waveform_1, waveform_2, output_sample_rate
class AudioConcat:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"audio1": ("AUDIO",),
"audio2": ("AUDIO",),
"direction": (['after', 'before'], {"default": 'after', "tooltip": "Whether to append audio2 after or before audio1."}),
}}
RETURN_TYPES = ("AUDIO",)
FUNCTION = "concat"
CATEGORY = "audio"
DESCRIPTION = "Concatenates the audio1 to audio2 in the specified direction."
def concat(self, audio1, audio2, direction):
waveform_1 = audio1["waveform"]
waveform_2 = audio2["waveform"]
sample_rate_1 = audio1["sample_rate"]
sample_rate_2 = audio2["sample_rate"]
if waveform_1.shape[1] == 1:
waveform_1 = waveform_1.repeat(1, 2, 1)
logging.info("AudioConcat: Converted mono audio1 to stereo by duplicating the channel.")
if waveform_2.shape[1] == 1:
waveform_2 = waveform_2.repeat(1, 2, 1)
logging.info("AudioConcat: Converted mono audio2 to stereo by duplicating the channel.")
waveform_1, waveform_2, output_sample_rate = match_audio_sample_rates(waveform_1, sample_rate_1, waveform_2, sample_rate_2)
if direction == 'after':
concatenated_audio = torch.cat((waveform_1, waveform_2), dim=2)
elif direction == 'before':
concatenated_audio = torch.cat((waveform_2, waveform_1), dim=2)
return ({"waveform": concatenated_audio, "sample_rate": output_sample_rate},)
class AudioMerge:
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"audio1": ("AUDIO",),
"audio2": ("AUDIO",),
"merge_method": (["add", "mean", "subtract", "multiply"], {"tooltip": "The method used to combine the audio waveforms."}),
},
}
FUNCTION = "merge"
RETURN_TYPES = ("AUDIO",)
CATEGORY = "audio"
DESCRIPTION = "Combine two audio tracks by overlaying their waveforms."
def merge(self, audio1, audio2, merge_method):
waveform_1 = audio1["waveform"]
waveform_2 = audio2["waveform"]
sample_rate_1 = audio1["sample_rate"]
sample_rate_2 = audio2["sample_rate"]
waveform_1, waveform_2, output_sample_rate = match_audio_sample_rates(waveform_1, sample_rate_1, waveform_2, sample_rate_2)
length_1 = waveform_1.shape[-1]
length_2 = waveform_2.shape[-1]
if length_2 > length_1:
logging.info(f"AudioMerge: Trimming audio2 from {length_2} to {length_1} samples to match audio1 length.")
waveform_2 = waveform_2[..., :length_1]
elif length_2 < length_1:
logging.info(f"AudioMerge: Padding audio2 from {length_2} to {length_1} samples to match audio1 length.")
pad_shape = list(waveform_2.shape)
pad_shape[-1] = length_1 - length_2
pad_tensor = torch.zeros(pad_shape, dtype=waveform_2.dtype, device=waveform_2.device)
waveform_2 = torch.cat((waveform_2, pad_tensor), dim=-1)
if merge_method == "add":
waveform = waveform_1 + waveform_2
elif merge_method == "subtract":
waveform = waveform_1 - waveform_2
elif merge_method == "multiply":
waveform = waveform_1 * waveform_2
elif merge_method == "mean":
waveform = (waveform_1 + waveform_2) / 2
max_val = waveform.abs().max()
if max_val > 1.0:
waveform = waveform / max_val
return ({"waveform": waveform, "sample_rate": output_sample_rate},)
class AudioAdjustVolume:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"audio": ("AUDIO",),
"volume": ("INT", {"default": 1.0, "min": -100, "max": 100, "tooltip": "Volume adjustment in decibels (dB). 0 = no change, +6 = double, -6 = half, etc"}),
}}
RETURN_TYPES = ("AUDIO",)
FUNCTION = "adjust_volume"
CATEGORY = "audio"
def adjust_volume(self, audio, volume):
if volume == 0:
return (audio,)
waveform = audio["waveform"]
sample_rate = audio["sample_rate"]
gain = 10 ** (volume / 20)
waveform = waveform * gain
return ({"waveform": waveform, "sample_rate": sample_rate},)
class EmptyAudio:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"duration": ("FLOAT", {"default": 60.0, "min": 0.0, "max": 0xffffffffffffffff, "step": 0.01, "tooltip": "Duration of the empty audio clip in seconds"}),
"sample_rate": ("INT", {"default": 44100, "tooltip": "Sample rate of the empty audio clip."}),
"channels": ("INT", {"default": 2, "min": 1, "max": 2, "tooltip": "Number of audio channels (1 for mono, 2 for stereo)."}),
}}
RETURN_TYPES = ("AUDIO",)
FUNCTION = "create_empty_audio"
CATEGORY = "audio"
def create_empty_audio(self, duration, sample_rate, channels):
num_samples = int(round(duration * sample_rate))
waveform = torch.zeros((1, channels, num_samples), dtype=torch.float32)
return ({"waveform": waveform, "sample_rate": sample_rate},)
NODE_CLASS_MAPPINGS = {
"EmptyLatentAudio": EmptyLatentAudio,
"VAEEncodeAudio": VAEEncodeAudio,
@ -375,6 +586,12 @@ NODE_CLASS_MAPPINGS = {
"PreviewAudio": PreviewAudio,
"ConditioningStableAudio": ConditioningStableAudio,
"RecordAudio": RecordAudio,
"TrimAudioDuration": TrimAudioDuration,
"SplitAudioChannels": SplitAudioChannels,
"AudioConcat": AudioConcat,
"AudioMerge": AudioMerge,
"AudioAdjustVolume": AudioAdjustVolume,
"EmptyAudio": EmptyAudio,
}
NODE_DISPLAY_NAME_MAPPINGS = {
@ -387,4 +604,10 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"SaveAudioMP3": "Save Audio (MP3)",
"SaveAudioOpus": "Save Audio (Opus)",
"RecordAudio": "Record Audio",
"TrimAudioDuration": "Trim Audio Duration",
"SplitAudioChannels": "Split Audio Channels",
"AudioConcat": "Audio Concat",
"AudioMerge": "Audio Merge",
"AudioAdjustVolume": "Audio Adjust Volume",
"EmptyAudio": "Empty Audio",
}