mirror of
https://git.datalinker.icu/comfyanonymous/ComfyUI
synced 2025-12-09 05:54:24 +08:00
convert nodes_audio.py to V3 schema (#10798)
This commit is contained in:
Alexander Piskun
GitHub
parent
440268d394
commit
dce518c2b4
@ -319,9 +319,10 @@ class AudioSaveHelper:
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for key, value in metadata.items():
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output_container.metadata[key] = value
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layout = "mono" if waveform.shape[0] == 1 else "stereo"
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# Set up the output stream with appropriate properties
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if format == "opus":
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out_stream = output_container.add_stream("libopus", rate=sample_rate)
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out_stream = output_container.add_stream("libopus", rate=sample_rate, layout=layout)
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if quality == "64k":
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out_stream.bit_rate = 64000
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elif quality == "96k":
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@ -333,7 +334,7 @@ class AudioSaveHelper:
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elif quality == "320k":
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out_stream.bit_rate = 320000
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elif format == "mp3":
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out_stream = output_container.add_stream("libmp3lame", rate=sample_rate)
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out_stream = output_container.add_stream("libmp3lame", rate=sample_rate, layout=layout)
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if quality == "V0":
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# TODO i would really love to support V3 and V5 but there doesn't seem to be a way to set the qscale level, the property below is a bool
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out_stream.codec_context.qscale = 1
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@ -342,12 +343,12 @@ class AudioSaveHelper:
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elif quality == "320k":
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out_stream.bit_rate = 320000
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else: # format == "flac":
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out_stream = output_container.add_stream("flac", rate=sample_rate)
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out_stream = output_container.add_stream("flac", rate=sample_rate, layout=layout)
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frame = av.AudioFrame.from_ndarray(
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waveform.movedim(0, 1).reshape(1, -1).float().numpy(),
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format="flt",
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layout="mono" if waveform.shape[0] == 1 else "stereo",
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layout=layout,
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)
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frame.sample_rate = sample_rate
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frame.pts = 0
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@ -6,65 +6,80 @@ import torch
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import comfy.model_management
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import folder_paths
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import os
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import io
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import json
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import random
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import hashlib
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import node_helpers
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import logging
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from comfy.cli_args import args
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from comfy.comfy_types import FileLocator
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from typing_extensions import override
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from comfy_api.latest import ComfyExtension, IO, UI
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class EmptyLatentAudio:
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def __init__(self):
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self.device = comfy.model_management.intermediate_device()
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class EmptyLatentAudio(IO.ComfyNode):
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@classmethod
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def define_schema(cls):
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return IO.Schema(
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node_id="EmptyLatentAudio",
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display_name="Empty Latent Audio",
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category="latent/audio",
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inputs=[
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IO.Float.Input("seconds", default=47.6, min=1.0, max=1000.0, step=0.1),
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IO.Int.Input(
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"batch_size", default=1, min=1, max=4096, tooltip="The number of latent images in the batch."
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),
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],
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outputs=[IO.Latent.Output()],
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)
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@classmethod
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def INPUT_TYPES(s):
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return {"required": {"seconds": ("FLOAT", {"default": 47.6, "min": 1.0, "max": 1000.0, "step": 0.1}),
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"batch_size": ("INT", {"default": 1, "min": 1, "max": 4096, "tooltip": "The number of latent images in the batch."}),
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}}
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RETURN_TYPES = ("LATENT",)
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FUNCTION = "generate"
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CATEGORY = "latent/audio"
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def generate(self, seconds, batch_size):
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def execute(cls, seconds, batch_size) -> IO.NodeOutput:
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length = round((seconds * 44100 / 2048) / 2) * 2
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latent = torch.zeros([batch_size, 64, length], device=self.device)
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return ({"samples":latent, "type": "audio"}, )
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latent = torch.zeros([batch_size, 64, length], device=comfy.model_management.intermediate_device())
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return IO.NodeOutput({"samples":latent, "type": "audio"})
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class ConditioningStableAudio:
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generate = execute # TODO: remove
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class ConditioningStableAudio(IO.ComfyNode):
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@classmethod
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def INPUT_TYPES(s):
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return {"required": {"positive": ("CONDITIONING", ),
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"negative": ("CONDITIONING", ),
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"seconds_start": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1000.0, "step": 0.1}),
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"seconds_total": ("FLOAT", {"default": 47.0, "min": 0.0, "max": 1000.0, "step": 0.1}),
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}}
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def define_schema(cls):
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return IO.Schema(
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node_id="ConditioningStableAudio",
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category="conditioning",
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inputs=[
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IO.Conditioning.Input("positive"),
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IO.Conditioning.Input("negative"),
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IO.Float.Input("seconds_start", default=0.0, min=0.0, max=1000.0, step=0.1),
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IO.Float.Input("seconds_total", default=47.0, min=0.0, max=1000.0, step=0.1),
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],
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outputs=[
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IO.Conditioning.Output(display_name="positive"),
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IO.Conditioning.Output(display_name="negative"),
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],
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)
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RETURN_TYPES = ("CONDITIONING","CONDITIONING")
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RETURN_NAMES = ("positive", "negative")
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FUNCTION = "append"
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CATEGORY = "conditioning"
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def append(self, positive, negative, seconds_start, seconds_total):
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@classmethod
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def execute(cls, positive, negative, seconds_start, seconds_total) -> IO.NodeOutput:
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positive = node_helpers.conditioning_set_values(positive, {"seconds_start": seconds_start, "seconds_total": seconds_total})
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negative = node_helpers.conditioning_set_values(negative, {"seconds_start": seconds_start, "seconds_total": seconds_total})
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return (positive, negative)
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return IO.NodeOutput(positive, negative)
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class VAEEncodeAudio:
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append = execute # TODO: remove
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class VAEEncodeAudio(IO.ComfyNode):
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@classmethod
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def INPUT_TYPES(s):
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return {"required": { "audio": ("AUDIO", ), "vae": ("VAE", )}}
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RETURN_TYPES = ("LATENT",)
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FUNCTION = "encode"
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def define_schema(cls):
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return IO.Schema(
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node_id="VAEEncodeAudio",
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display_name="VAE Encode Audio",
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category="latent/audio",
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inputs=[
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IO.Audio.Input("audio"),
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IO.Vae.Input("vae"),
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],
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outputs=[IO.Latent.Output()],
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)
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CATEGORY = "latent/audio"
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def encode(self, vae, audio):
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@classmethod
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def execute(cls, vae, audio) -> IO.NodeOutput:
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sample_rate = audio["sample_rate"]
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if 44100 != sample_rate:
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waveform = torchaudio.functional.resample(audio["waveform"], sample_rate, 44100)
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@ -72,213 +87,134 @@ class VAEEncodeAudio:
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waveform = audio["waveform"]
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t = vae.encode(waveform.movedim(1, -1))
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return ({"samples":t}, )
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return IO.NodeOutput({"samples":t})
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class VAEDecodeAudio:
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encode = execute # TODO: remove
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class VAEDecodeAudio(IO.ComfyNode):
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@classmethod
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def INPUT_TYPES(s):
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return {"required": { "samples": ("LATENT", ), "vae": ("VAE", )}}
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RETURN_TYPES = ("AUDIO",)
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FUNCTION = "decode"
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def define_schema(cls):
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return IO.Schema(
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node_id="VAEDecodeAudio",
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display_name="VAE Decode Audio",
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category="latent/audio",
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inputs=[
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IO.Latent.Input("samples"),
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IO.Vae.Input("vae"),
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],
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outputs=[IO.Audio.Output()],
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)
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CATEGORY = "latent/audio"
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def decode(self, vae, samples):
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@classmethod
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def execute(cls, vae, samples) -> IO.NodeOutput:
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audio = vae.decode(samples["samples"]).movedim(-1, 1)
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std = torch.std(audio, dim=[1,2], keepdim=True) * 5.0
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std[std < 1.0] = 1.0
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audio /= std
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return ({"waveform": audio, "sample_rate": 44100}, )
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return IO.NodeOutput({"waveform": audio, "sample_rate": 44100})
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decode = execute # TODO: remove
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def save_audio(self, audio, filename_prefix="ComfyUI", format="flac", prompt=None, extra_pnginfo=None, quality="128k"):
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filename_prefix += self.prefix_append
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full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir)
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results: list[FileLocator] = []
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# Prepare metadata dictionary
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metadata = {}
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if not args.disable_metadata:
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if prompt is not None:
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metadata["prompt"] = json.dumps(prompt)
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if extra_pnginfo is not None:
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for x in extra_pnginfo:
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metadata[x] = json.dumps(extra_pnginfo[x])
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# Opus supported sample rates
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OPUS_RATES = [8000, 12000, 16000, 24000, 48000]
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for (batch_number, waveform) in enumerate(audio["waveform"].cpu()):
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filename_with_batch_num = filename.replace("%batch_num%", str(batch_number))
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file = f"{filename_with_batch_num}_{counter:05}_.{format}"
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output_path = os.path.join(full_output_folder, file)
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# Use original sample rate initially
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sample_rate = audio["sample_rate"]
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# Handle Opus sample rate requirements
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if format == "opus":
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if sample_rate > 48000:
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sample_rate = 48000
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elif sample_rate not in OPUS_RATES:
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# Find the next highest supported rate
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for rate in sorted(OPUS_RATES):
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if rate > sample_rate:
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sample_rate = rate
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break
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if sample_rate not in OPUS_RATES: # Fallback if still not supported
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sample_rate = 48000
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# Resample if necessary
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if sample_rate != audio["sample_rate"]:
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waveform = torchaudio.functional.resample(waveform, audio["sample_rate"], sample_rate)
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# Create output with specified format
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output_buffer = io.BytesIO()
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output_container = av.open(output_buffer, mode='w', format=format)
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# Set metadata on the container
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for key, value in metadata.items():
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output_container.metadata[key] = value
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layout = 'mono' if waveform.shape[0] == 1 else 'stereo'
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# Set up the output stream with appropriate properties
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if format == "opus":
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out_stream = output_container.add_stream("libopus", rate=sample_rate, layout=layout)
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if quality == "64k":
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out_stream.bit_rate = 64000
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elif quality == "96k":
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out_stream.bit_rate = 96000
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elif quality == "128k":
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out_stream.bit_rate = 128000
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elif quality == "192k":
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out_stream.bit_rate = 192000
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elif quality == "320k":
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out_stream.bit_rate = 320000
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elif format == "mp3":
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out_stream = output_container.add_stream("libmp3lame", rate=sample_rate, layout=layout)
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if quality == "V0":
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#TODO i would really love to support V3 and V5 but there doesn't seem to be a way to set the qscale level, the property below is a bool
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out_stream.codec_context.qscale = 1
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elif quality == "128k":
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out_stream.bit_rate = 128000
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elif quality == "320k":
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out_stream.bit_rate = 320000
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else: #format == "flac":
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out_stream = output_container.add_stream("flac", rate=sample_rate, layout=layout)
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frame = av.AudioFrame.from_ndarray(waveform.movedim(0, 1).reshape(1, -1).float().numpy(), format='flt', layout=layout)
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frame.sample_rate = sample_rate
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frame.pts = 0
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output_container.mux(out_stream.encode(frame))
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# Flush encoder
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output_container.mux(out_stream.encode(None))
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# Close containers
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output_container.close()
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# Write the output to file
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output_buffer.seek(0)
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with open(output_path, 'wb') as f:
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f.write(output_buffer.getbuffer())
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results.append({
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"filename": file,
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"subfolder": subfolder,
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"type": self.type
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})
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counter += 1
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return { "ui": { "audio": results } }
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class SaveAudio:
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def __init__(self):
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self.output_dir = folder_paths.get_output_directory()
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self.type = "output"
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self.prefix_append = ""
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class SaveAudio(IO.ComfyNode):
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@classmethod
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def define_schema(cls):
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return IO.Schema(
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node_id="SaveAudio",
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display_name="Save Audio (FLAC)",
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category="audio",
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inputs=[
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IO.Audio.Input("audio"),
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IO.String.Input("filename_prefix", default="audio/ComfyUI"),
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],
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hidden=[IO.Hidden.prompt, IO.Hidden.extra_pnginfo],
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is_output_node=True,
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)
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@classmethod
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def INPUT_TYPES(s):
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return {"required": { "audio": ("AUDIO", ),
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"filename_prefix": ("STRING", {"default": "audio/ComfyUI"}),
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},
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"hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
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}
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def execute(cls, audio, filename_prefix="ComfyUI", format="flac") -> IO.NodeOutput:
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return IO.NodeOutput(
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ui=UI.AudioSaveHelper.get_save_audio_ui(audio, filename_prefix=filename_prefix, cls=cls, format=format)
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)
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RETURN_TYPES = ()
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FUNCTION = "save_flac"
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save_flac = execute # TODO: remove
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OUTPUT_NODE = True
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CATEGORY = "audio"
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def save_flac(self, audio, filename_prefix="ComfyUI", format="flac", prompt=None, extra_pnginfo=None):
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return save_audio(self, audio, filename_prefix, format, prompt, extra_pnginfo)
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class SaveAudioMP3:
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def __init__(self):
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self.output_dir = folder_paths.get_output_directory()
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self.type = "output"
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self.prefix_append = ""
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class SaveAudioMP3(IO.ComfyNode):
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@classmethod
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def define_schema(cls):
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return IO.Schema(
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node_id="SaveAudioMP3",
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display_name="Save Audio (MP3)",
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category="audio",
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inputs=[
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IO.Audio.Input("audio"),
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IO.String.Input("filename_prefix", default="audio/ComfyUI"),
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IO.Combo.Input("quality", options=["V0", "128k", "320k"], default="V0"),
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],
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hidden=[IO.Hidden.prompt, IO.Hidden.extra_pnginfo],
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is_output_node=True,
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)
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@classmethod
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def INPUT_TYPES(s):
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return {"required": { "audio": ("AUDIO", ),
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"filename_prefix": ("STRING", {"default": "audio/ComfyUI"}),
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"quality": (["V0", "128k", "320k"], {"default": "V0"}),
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},
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"hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
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}
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def execute(cls, audio, filename_prefix="ComfyUI", format="mp3", quality="128k") -> IO.NodeOutput:
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return IO.NodeOutput(
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ui=UI.AudioSaveHelper.get_save_audio_ui(
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audio, filename_prefix=filename_prefix, cls=cls, format=format, quality=quality
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)
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)
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RETURN_TYPES = ()
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FUNCTION = "save_mp3"
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save_mp3 = execute # TODO: remove
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OUTPUT_NODE = True
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CATEGORY = "audio"
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def save_mp3(self, audio, filename_prefix="ComfyUI", format="mp3", prompt=None, extra_pnginfo=None, quality="128k"):
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return save_audio(self, audio, filename_prefix, format, prompt, extra_pnginfo, quality)
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class SaveAudioOpus:
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def __init__(self):
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self.output_dir = folder_paths.get_output_directory()
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self.type = "output"
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self.prefix_append = ""
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class SaveAudioOpus(IO.ComfyNode):
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@classmethod
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def define_schema(cls):
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return IO.Schema(
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node_id="SaveAudioOpus",
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display_name="Save Audio (Opus)",
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category="audio",
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inputs=[
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IO.Audio.Input("audio"),
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IO.String.Input("filename_prefix", default="audio/ComfyUI"),
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IO.Combo.Input("quality", options=["64k", "96k", "128k", "192k", "320k"], default="128k"),
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],
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hidden=[IO.Hidden.prompt, IO.Hidden.extra_pnginfo],
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is_output_node=True,
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)
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@classmethod
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def INPUT_TYPES(s):
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return {"required": { "audio": ("AUDIO", ),
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"filename_prefix": ("STRING", {"default": "audio/ComfyUI"}),
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"quality": (["64k", "96k", "128k", "192k", "320k"], {"default": "128k"}),
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},
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"hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
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}
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def execute(cls, audio, filename_prefix="ComfyUI", format="opus", quality="V3") -> IO.NodeOutput:
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return IO.NodeOutput(
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ui=UI.AudioSaveHelper.get_save_audio_ui(
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audio, filename_prefix=filename_prefix, cls=cls, format=format, quality=quality
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)
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)
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RETURN_TYPES = ()
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FUNCTION = "save_opus"
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save_opus = execute # TODO: remove
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OUTPUT_NODE = True
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CATEGORY = "audio"
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def save_opus(self, audio, filename_prefix="ComfyUI", format="opus", prompt=None, extra_pnginfo=None, quality="V3"):
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return save_audio(self, audio, filename_prefix, format, prompt, extra_pnginfo, quality)
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|
||||
class PreviewAudio(SaveAudio):
|
||||
def __init__(self):
|
||||
self.output_dir = folder_paths.get_temp_directory()
|
||||
self.type = "temp"
|
||||
self.prefix_append = "_temp_" + ''.join(random.choice("abcdefghijklmnopqrstupvxyz") for x in range(5))
|
||||
class PreviewAudio(IO.ComfyNode):
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="PreviewAudio",
|
||||
display_name="Preview Audio",
|
||||
category="audio",
|
||||
inputs=[
|
||||
IO.Audio.Input("audio"),
|
||||
],
|
||||
hidden=[IO.Hidden.prompt, IO.Hidden.extra_pnginfo],
|
||||
is_output_node=True,
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {"required":
|
||||
{"audio": ("AUDIO", ), },
|
||||
"hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
|
||||
}
|
||||
def execute(cls, audio) -> IO.NodeOutput:
|
||||
return IO.NodeOutput(ui=UI.PreviewAudio(audio, cls=cls))
|
||||
|
||||
save_flac = execute # TODO: remove
|
||||
|
||||
|
||||
def f32_pcm(wav: torch.Tensor) -> torch.Tensor:
|
||||
"""Convert audio to float 32 bits PCM format."""
|
||||
@ -316,26 +252,30 @@ def load(filepath: str) -> tuple[torch.Tensor, int]:
|
||||
wav = f32_pcm(wav)
|
||||
return wav, sr
|
||||
|
||||
class LoadAudio:
|
||||
class LoadAudio(IO.ComfyNode):
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
def define_schema(cls):
|
||||
input_dir = folder_paths.get_input_directory()
|
||||
files = folder_paths.filter_files_content_types(os.listdir(input_dir), ["audio", "video"])
|
||||
return {"required": {"audio": (sorted(files), {"audio_upload": True})}}
|
||||
return IO.Schema(
|
||||
node_id="LoadAudio",
|
||||
display_name="Load Audio",
|
||||
category="audio",
|
||||
inputs=[
|
||||
IO.Combo.Input("audio", upload=IO.UploadType.audio, options=sorted(files)),
|
||||
],
|
||||
outputs=[IO.Audio.Output()],
|
||||
)
|
||||
|
||||
CATEGORY = "audio"
|
||||
|
||||
RETURN_TYPES = ("AUDIO", )
|
||||
FUNCTION = "load"
|
||||
|
||||
def load(self, audio):
|
||||
@classmethod
|
||||
def execute(cls, audio) -> IO.NodeOutput:
|
||||
audio_path = folder_paths.get_annotated_filepath(audio)
|
||||
waveform, sample_rate = load(audio_path)
|
||||
audio = {"waveform": waveform.unsqueeze(0), "sample_rate": sample_rate}
|
||||
return (audio, )
|
||||
return IO.NodeOutput(audio)
|
||||
|
||||
@classmethod
|
||||
def IS_CHANGED(s, audio):
|
||||
def fingerprint_inputs(cls, audio):
|
||||
image_path = folder_paths.get_annotated_filepath(audio)
|
||||
m = hashlib.sha256()
|
||||
with open(image_path, 'rb') as f:
|
||||
@ -343,46 +283,69 @@ class LoadAudio:
|
||||
return m.digest().hex()
|
||||
|
||||
@classmethod
|
||||
def VALIDATE_INPUTS(s, audio):
|
||||
def validate_inputs(cls, audio):
|
||||
if not folder_paths.exists_annotated_filepath(audio):
|
||||
return "Invalid audio file: {}".format(audio)
|
||||
return True
|
||||
|
||||
class RecordAudio:
|
||||
load = execute # TODO: remove
|
||||
|
||||
|
||||
class RecordAudio(IO.ComfyNode):
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {"required": {"audio": ("AUDIO_RECORD", {})}}
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="RecordAudio",
|
||||
display_name="Record Audio",
|
||||
category="audio",
|
||||
inputs=[
|
||||
IO.Custom("AUDIO_RECORD").Input("audio"),
|
||||
],
|
||||
outputs=[IO.Audio.Output()],
|
||||
)
|
||||
|
||||
CATEGORY = "audio"
|
||||
|
||||
RETURN_TYPES = ("AUDIO", )
|
||||
FUNCTION = "load"
|
||||
|
||||
def load(self, audio):
|
||||
@classmethod
|
||||
def execute(cls, audio) -> IO.NodeOutput:
|
||||
audio_path = folder_paths.get_annotated_filepath(audio)
|
||||
|
||||
waveform, sample_rate = load(audio_path)
|
||||
audio = {"waveform": waveform.unsqueeze(0), "sample_rate": sample_rate}
|
||||
return (audio, )
|
||||
return IO.NodeOutput(audio)
|
||||
|
||||
load = execute # TODO: remove
|
||||
|
||||
|
||||
class TrimAudioDuration:
|
||||
class TrimAudioDuration(IO.ComfyNode):
|
||||
@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"}),
|
||||
},
|
||||
}
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="TrimAudioDuration",
|
||||
display_name="Trim Audio Duration",
|
||||
description="Trim audio tensor into chosen time range.",
|
||||
category="audio",
|
||||
inputs=[
|
||||
IO.Audio.Input("audio"),
|
||||
IO.Float.Input(
|
||||
"start_index",
|
||||
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).",
|
||||
),
|
||||
IO.Float.Input(
|
||||
"duration",
|
||||
default=60.0,
|
||||
min=0.0,
|
||||
step=0.01,
|
||||
tooltip="Duration in seconds",
|
||||
),
|
||||
],
|
||||
outputs=[IO.Audio.Output()],
|
||||
)
|
||||
|
||||
FUNCTION = "trim"
|
||||
RETURN_TYPES = ("AUDIO",)
|
||||
CATEGORY = "audio"
|
||||
DESCRIPTION = "Trim audio tensor into chosen time range."
|
||||
|
||||
def trim(self, audio, start_index, duration):
|
||||
@classmethod
|
||||
def execute(cls, audio, start_index, duration) -> IO.NodeOutput:
|
||||
waveform = audio["waveform"]
|
||||
sample_rate = audio["sample_rate"]
|
||||
audio_length = waveform.shape[-1]
|
||||
@ -399,23 +362,30 @@ class TrimAudioDuration:
|
||||
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},)
|
||||
return IO.NodeOutput({"waveform": waveform[..., start_frame:end_frame], "sample_rate": sample_rate})
|
||||
|
||||
trim = execute # TODO: remove
|
||||
|
||||
|
||||
class SplitAudioChannels:
|
||||
class SplitAudioChannels(IO.ComfyNode):
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {"required": {
|
||||
"audio": ("AUDIO",),
|
||||
}}
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="SplitAudioChannels",
|
||||
display_name="Split Audio Channels",
|
||||
description="Separates the audio into left and right channels.",
|
||||
category="audio",
|
||||
inputs=[
|
||||
IO.Audio.Input("audio"),
|
||||
],
|
||||
outputs=[
|
||||
IO.Audio.Output(display_name="left"),
|
||||
IO.Audio.Output(display_name="right"),
|
||||
],
|
||||
)
|
||||
|
||||
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):
|
||||
@classmethod
|
||||
def execute(cls, audio) -> IO.NodeOutput:
|
||||
waveform = audio["waveform"]
|
||||
sample_rate = audio["sample_rate"]
|
||||
|
||||
@ -425,7 +395,9 @@ class SplitAudioChannels:
|
||||
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})
|
||||
return IO.NodeOutput({"waveform": left_channel, "sample_rate": sample_rate}, {"waveform": right_channel, "sample_rate": sample_rate})
|
||||
|
||||
separate = execute # TODO: remove
|
||||
|
||||
|
||||
def match_audio_sample_rates(waveform_1, sample_rate_1, waveform_2, sample_rate_2):
|
||||
@ -443,21 +415,29 @@ def match_audio_sample_rates(waveform_1, sample_rate_1, waveform_2, sample_rate_
|
||||
return waveform_1, waveform_2, output_sample_rate
|
||||
|
||||
|
||||
class AudioConcat:
|
||||
class AudioConcat(IO.ComfyNode):
|
||||
@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."}),
|
||||
}}
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="AudioConcat",
|
||||
display_name="Audio Concat",
|
||||
description="Concatenates the audio1 to audio2 in the specified direction.",
|
||||
category="audio",
|
||||
inputs=[
|
||||
IO.Audio.Input("audio1"),
|
||||
IO.Audio.Input("audio2"),
|
||||
IO.Combo.Input(
|
||||
"direction",
|
||||
options=['after', 'before'],
|
||||
default="after",
|
||||
tooltip="Whether to append audio2 after or before audio1.",
|
||||
)
|
||||
],
|
||||
outputs=[IO.Audio.Output()],
|
||||
)
|
||||
|
||||
RETURN_TYPES = ("AUDIO",)
|
||||
FUNCTION = "concat"
|
||||
CATEGORY = "audio"
|
||||
DESCRIPTION = "Concatenates the audio1 to audio2 in the specified direction."
|
||||
|
||||
def concat(self, audio1, audio2, direction):
|
||||
@classmethod
|
||||
def execute(cls, audio1, audio2, direction) -> IO.NodeOutput:
|
||||
waveform_1 = audio1["waveform"]
|
||||
waveform_2 = audio2["waveform"]
|
||||
sample_rate_1 = audio1["sample_rate"]
|
||||
@ -477,26 +457,33 @@ class AudioConcat:
|
||||
elif direction == 'before':
|
||||
concatenated_audio = torch.cat((waveform_2, waveform_1), dim=2)
|
||||
|
||||
return ({"waveform": concatenated_audio, "sample_rate": output_sample_rate},)
|
||||
return IO.NodeOutput({"waveform": concatenated_audio, "sample_rate": output_sample_rate})
|
||||
|
||||
concat = execute # TODO: remove
|
||||
|
||||
|
||||
class AudioMerge:
|
||||
class AudioMerge(IO.ComfyNode):
|
||||
@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."}),
|
||||
},
|
||||
}
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="AudioMerge",
|
||||
display_name="Audio Merge",
|
||||
description="Combine two audio tracks by overlaying their waveforms.",
|
||||
category="audio",
|
||||
inputs=[
|
||||
IO.Audio.Input("audio1"),
|
||||
IO.Audio.Input("audio2"),
|
||||
IO.Combo.Input(
|
||||
"merge_method",
|
||||
options=["add", "mean", "subtract", "multiply"],
|
||||
tooltip="The method used to combine the audio waveforms.",
|
||||
)
|
||||
],
|
||||
outputs=[IO.Audio.Output()],
|
||||
)
|
||||
|
||||
FUNCTION = "merge"
|
||||
RETURN_TYPES = ("AUDIO",)
|
||||
CATEGORY = "audio"
|
||||
DESCRIPTION = "Combine two audio tracks by overlaying their waveforms."
|
||||
|
||||
def merge(self, audio1, audio2, merge_method):
|
||||
@classmethod
|
||||
def execute(cls, audio1, audio2, merge_method) -> IO.NodeOutput:
|
||||
waveform_1 = audio1["waveform"]
|
||||
waveform_2 = audio2["waveform"]
|
||||
sample_rate_1 = audio1["sample_rate"]
|
||||
@ -530,85 +517,108 @@ class AudioMerge:
|
||||
if max_val > 1.0:
|
||||
waveform = waveform / max_val
|
||||
|
||||
return ({"waveform": waveform, "sample_rate": output_sample_rate},)
|
||||
return IO.NodeOutput({"waveform": waveform, "sample_rate": output_sample_rate})
|
||||
|
||||
merge = execute # TODO: remove
|
||||
|
||||
|
||||
class AudioAdjustVolume:
|
||||
class AudioAdjustVolume(IO.ComfyNode):
|
||||
@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"}),
|
||||
}}
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="AudioAdjustVolume",
|
||||
display_name="Audio Adjust Volume",
|
||||
category="audio",
|
||||
inputs=[
|
||||
IO.Audio.Input("audio"),
|
||||
IO.Int.Input(
|
||||
"volume",
|
||||
default=1,
|
||||
min=-100,
|
||||
max=100,
|
||||
tooltip="Volume adjustment in decibels (dB). 0 = no change, +6 = double, -6 = half, etc",
|
||||
)
|
||||
],
|
||||
outputs=[IO.Audio.Output()],
|
||||
)
|
||||
|
||||
RETURN_TYPES = ("AUDIO",)
|
||||
FUNCTION = "adjust_volume"
|
||||
CATEGORY = "audio"
|
||||
|
||||
def adjust_volume(self, audio, volume):
|
||||
@classmethod
|
||||
def execute(cls, audio, volume) -> IO.NodeOutput:
|
||||
if volume == 0:
|
||||
return (audio,)
|
||||
return IO.NodeOutput(audio)
|
||||
waveform = audio["waveform"]
|
||||
sample_rate = audio["sample_rate"]
|
||||
|
||||
gain = 10 ** (volume / 20)
|
||||
waveform = waveform * gain
|
||||
|
||||
return ({"waveform": waveform, "sample_rate": sample_rate},)
|
||||
return IO.NodeOutput({"waveform": waveform, "sample_rate": sample_rate})
|
||||
|
||||
adjust_volume = execute # TODO: remove
|
||||
|
||||
|
||||
class EmptyAudio:
|
||||
class EmptyAudio(IO.ComfyNode):
|
||||
@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)."}),
|
||||
}}
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="EmptyAudio",
|
||||
display_name="Empty Audio",
|
||||
category="audio",
|
||||
inputs=[
|
||||
IO.Float.Input(
|
||||
"duration",
|
||||
default=60.0,
|
||||
min=0.0,
|
||||
max=0xffffffffffffffff,
|
||||
step=0.01,
|
||||
tooltip="Duration of the empty audio clip in seconds",
|
||||
),
|
||||
IO.Float.Input(
|
||||
"sample_rate",
|
||||
default=44100,
|
||||
tooltip="Sample rate of the empty audio clip.",
|
||||
),
|
||||
IO.Float.Input(
|
||||
"channels",
|
||||
default=2,
|
||||
min=1,
|
||||
max=2,
|
||||
tooltip="Number of audio channels (1 for mono, 2 for stereo).",
|
||||
),
|
||||
],
|
||||
outputs=[IO.Audio.Output()],
|
||||
)
|
||||
|
||||
RETURN_TYPES = ("AUDIO",)
|
||||
FUNCTION = "create_empty_audio"
|
||||
CATEGORY = "audio"
|
||||
|
||||
def create_empty_audio(self, duration, sample_rate, channels):
|
||||
@classmethod
|
||||
def execute(cls, duration, sample_rate, channels) -> IO.NodeOutput:
|
||||
num_samples = int(round(duration * sample_rate))
|
||||
waveform = torch.zeros((1, channels, num_samples), dtype=torch.float32)
|
||||
return ({"waveform": waveform, "sample_rate": sample_rate},)
|
||||
return IO.NodeOutput({"waveform": waveform, "sample_rate": sample_rate})
|
||||
|
||||
create_empty_audio = execute # TODO: remove
|
||||
|
||||
|
||||
NODE_CLASS_MAPPINGS = {
|
||||
"EmptyLatentAudio": EmptyLatentAudio,
|
||||
"VAEEncodeAudio": VAEEncodeAudio,
|
||||
"VAEDecodeAudio": VAEDecodeAudio,
|
||||
"SaveAudio": SaveAudio,
|
||||
"SaveAudioMP3": SaveAudioMP3,
|
||||
"SaveAudioOpus": SaveAudioOpus,
|
||||
"LoadAudio": LoadAudio,
|
||||
"PreviewAudio": PreviewAudio,
|
||||
"ConditioningStableAudio": ConditioningStableAudio,
|
||||
"RecordAudio": RecordAudio,
|
||||
"TrimAudioDuration": TrimAudioDuration,
|
||||
"SplitAudioChannels": SplitAudioChannels,
|
||||
"AudioConcat": AudioConcat,
|
||||
"AudioMerge": AudioMerge,
|
||||
"AudioAdjustVolume": AudioAdjustVolume,
|
||||
"EmptyAudio": EmptyAudio,
|
||||
}
|
||||
class AudioExtension(ComfyExtension):
|
||||
@override
|
||||
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
|
||||
return [
|
||||
EmptyLatentAudio,
|
||||
VAEEncodeAudio,
|
||||
VAEDecodeAudio,
|
||||
SaveAudio,
|
||||
SaveAudioMP3,
|
||||
SaveAudioOpus,
|
||||
LoadAudio,
|
||||
PreviewAudio,
|
||||
ConditioningStableAudio,
|
||||
RecordAudio,
|
||||
TrimAudioDuration,
|
||||
SplitAudioChannels,
|
||||
AudioConcat,
|
||||
AudioMerge,
|
||||
AudioAdjustVolume,
|
||||
EmptyAudio,
|
||||
]
|
||||
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
"EmptyLatentAudio": "Empty Latent Audio",
|
||||
"VAEEncodeAudio": "VAE Encode Audio",
|
||||
"VAEDecodeAudio": "VAE Decode Audio",
|
||||
"PreviewAudio": "Preview Audio",
|
||||
"LoadAudio": "Load Audio",
|
||||
"SaveAudio": "Save Audio (FLAC)",
|
||||
"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",
|
||||
}
|
||||
async def comfy_entrypoint() -> AudioExtension:
|
||||
return AudioExtension()
|
||||
|
||||
Loading…
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Reference in New Issue
Block a user