From ac05d9a5fadeedc6270b531054b1112f0960f6f6 Mon Sep 17 00:00:00 2001 From: bigcat88 Date: Sun, 13 Jul 2025 08:28:50 +0300 Subject: [PATCH 1/3] V3 Nodes: LoadAudio and PreviewAudio --- comfy_api/v3/ui.py | 109 +++++++++++++++++++++++++++++++++ comfy_extras/v3/nodes_audio.py | 78 +++++++++++++++++++++++ 2 files changed, 187 insertions(+) create mode 100644 comfy_extras/v3/nodes_audio.py diff --git a/comfy_api/v3/ui.py b/comfy_api/v3/ui.py index a4b624f0b..976202244 100644 --- a/comfy_api/v3/ui.py +++ b/comfy_api/v3/ui.py @@ -1,5 +1,9 @@ from __future__ import annotations +from abc import ABC, abstractmethod +from io import BytesIO +import av +import torchaudio from comfy_api.v3.io import Image, FolderType, _UIOutput, ComfyNodeV3 # used for image preview from comfy.cli_args import args @@ -119,6 +123,111 @@ class PreviewAudio(_UIOutput): def __init__(self, values: list[SavedResult | dict], **kwargs): self.values = values + def __init__(self, audio, cls: ComfyNodeV3=None, **kwargs): + output_dir = folder_paths.get_temp_directory() + type = "temp" + prefix_append = "_temp_" + ''.join(random.choice("abcdefghijklmnopqrstupvxyz") for x in range(5)) + filename_prefix = "ComfyUI" + quality = "128k" + format = "flac" + + filename_prefix += prefix_append + full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path( + filename_prefix, output_dir + ) + + # Prepare metadata dictionary + metadata = {} + if not args.disable_metadata and cls is not None: + if cls.hidden.prompt is not None: + metadata["prompt"] = json.dumps(cls.hidden.prompt) + if cls.hidden.extra_pnginfo is not None: + for x in cls.hidden.extra_pnginfo: + metadata[x] = json.dumps(cls.hidden.extra_pnginfo[x]) + + # Opus supported sample rates + OPUS_RATES = [8000, 12000, 16000, 24000, 48000] + results = [] + for (batch_number, waveform) in enumerate(audio["waveform"].cpu()): + filename_with_batch_num = filename.replace("%batch_num%", str(batch_number)) + file = f"{filename_with_batch_num}_{counter:05}_.{format}" + output_path = os.path.join(full_output_folder, file) + + # Use original sample rate initially + sample_rate = audio["sample_rate"] + + # Handle Opus sample rate requirements + if format == "opus": + if sample_rate > 48000: + sample_rate = 48000 + elif sample_rate not in OPUS_RATES: + # Find the next highest supported rate + for rate in sorted(OPUS_RATES): + if rate > sample_rate: + sample_rate = rate + break + if sample_rate not in OPUS_RATES: # Fallback if still not supported + sample_rate = 48000 + + # Resample if necessary + if sample_rate != audio["sample_rate"]: + waveform = torchaudio.functional.resample(waveform, audio["sample_rate"], sample_rate) + + # Create output with specified format + output_buffer = BytesIO() + output_container = av.open(output_buffer, mode='w', format=format) + + # Set metadata on the container + for key, value in metadata.items(): + output_container.metadata[key] = value + + # Set up the output stream with appropriate properties + if format == "opus": + out_stream = output_container.add_stream("libopus", rate=sample_rate) + if quality == "64k": + out_stream.bit_rate = 64000 + elif quality == "96k": + out_stream.bit_rate = 96000 + elif quality == "128k": + out_stream.bit_rate = 128000 + elif quality == "192k": + out_stream.bit_rate = 192000 + elif quality == "320k": + out_stream.bit_rate = 320000 + elif format == "mp3": + out_stream = output_container.add_stream("libmp3lame", rate=sample_rate) + if quality == "V0": + # 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 + out_stream.codec_context.qscale = 1 + elif quality == "128k": + out_stream.bit_rate = 128000 + elif quality == "320k": + out_stream.bit_rate = 320000 + else: # format == "flac": + out_stream = output_container.add_stream("flac", rate=sample_rate) + + frame = av.AudioFrame.from_ndarray(waveform.movedim(0, 1).reshape(1, -1).float().numpy(), format='flt', + layout='mono' if waveform.shape[0] == 1 else 'stereo') + frame.sample_rate = sample_rate + frame.pts = 0 + output_container.mux(out_stream.encode(frame)) + + # Flush encoder + output_container.mux(out_stream.encode(None)) + + # Close containers + output_container.close() + + # Write the output to file + output_buffer.seek(0) + with open(output_path, 'wb') as f: + f.write(output_buffer.getbuffer()) + + results.append(SavedResult(file, subfolder, type)) + counter += 1 + + self.values = results + def as_dict(self): return {"audio": self.values} diff --git a/comfy_extras/v3/nodes_audio.py b/comfy_extras/v3/nodes_audio.py new file mode 100644 index 000000000..ae20a1da9 --- /dev/null +++ b/comfy_extras/v3/nodes_audio.py @@ -0,0 +1,78 @@ +from __future__ import annotations + +import torchaudio +import folder_paths +import os +import io +import hashlib +from comfy_api.v3 import io, ui + + +class PreviewAudio_V3(io.ComfyNodeV3): + @classmethod + def DEFINE_SCHEMA(cls): + return io.SchemaV3( + node_id="PreviewAudio_V3", + display_name="Preview Audio _V3", + category="audio", + inputs=[ + io.Audio.Input("audio"), + ], + hidden=[io.Hidden.prompt, io.Hidden.extra_pnginfo], + is_output_node=True, + ) + + @classmethod + def execute(cls, audio): + return io.NodeOutput(ui=ui.PreviewAudio(audio, cls=cls)) + + +class LoadAudio_V3(io.ComfyNodeV3): + @classmethod + def DEFINE_SCHEMA(cls): + return io.SchemaV3( + node_id="LoadAudio_V3", + display_name="Load Audio _V3", + category="audio", + inputs=[ + io.Combo.Input("audio", upload=io.UploadType.audio, options=cls.get_files_options()), + ], + outputs=[io.Audio.Output()], + ) + + @classmethod + def get_files_options(cls) -> list[str]: + input_dir = folder_paths.get_input_directory() + return sorted(folder_paths.filter_files_content_types(os.listdir(input_dir), ["audio", "video"])) + + @classmethod + def execute(cls, audio) -> io.NodeOutput: + waveform, sample_rate = torchaudio.load(folder_paths.get_annotated_filepath(audio)) + return io.NodeOutput({"waveform": waveform.unsqueeze(0), "sample_rate": sample_rate}) + + @classmethod + def fingerprint_inputs(s, audio): + image_path = folder_paths.get_annotated_filepath(audio) + m = hashlib.sha256() + with open(image_path, "rb") as f: + m.update(f.read()) + return m.digest().hex() + + @classmethod + def validate_inputs(s, audio): + if not folder_paths.exists_annotated_filepath(audio): + return "Invalid audio file: {}".format(audio) + return True + + +NODES_LIST: list[type[io.ComfyNodeV3]] = [ + # EmptyLatentAudio_V3, + # VAEEncodeAudio_V3, + # VAEDecodeAudio_V3, + # SaveAudio_V3, + # SaveAudioMP3_V3, + # SaveAudioOpus_V3, + LoadAudio_V3, + PreviewAudio_V3, + # ConditioningStableAudio_V3, +] From b17cc99c1eb47d71436c3d71da22acebff40c7b7 Mon Sep 17 00:00:00 2001 From: bigcat88 Date: Tue, 15 Jul 2025 13:11:50 +0300 Subject: [PATCH 2/3] V3 Nodes: Load,Save,Vae audio nodes; sort imports; ruff --- comfy_api/v3/__init__.py | 0 comfy_api/v3/helpers.py | 2 +- comfy_api/v3/io.py | 125 ++++++------- comfy_api/v3/ui.py | 38 ++-- comfy_extras/v3/nodes_audio.py | 313 ++++++++++++++++++++++++++++++--- nodes.py | 1 + 6 files changed, 376 insertions(+), 103 deletions(-) create mode 100644 comfy_api/v3/__init__.py diff --git a/comfy_api/v3/__init__.py b/comfy_api/v3/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/comfy_api/v3/helpers.py b/comfy_api/v3/helpers.py index 019c725f4..c58a1b357 100644 --- a/comfy_api/v3/helpers.py +++ b/comfy_api/v3/helpers.py @@ -1,4 +1,4 @@ -from typing import Optional, Callable +from typing import Callable, Optional def first_real_override(cls: type, name: str, *, base: type) -> Optional[Callable]: diff --git a/comfy_api/v3/io.py b/comfy_api/v3/io.py index c2733bf14..9a9daeec8 100644 --- a/comfy_api/v3/io.py +++ b/comfy_api/v3/io.py @@ -1,26 +1,29 @@ from __future__ import annotations -from typing import Any, Literal, TypeVar, Callable, TypedDict -from typing_extensions import NotRequired -from enum import Enum -from abc import ABC, abstractmethod -from dataclasses import dataclass, asdict -from collections import Counter -from comfy_execution.graph import ExecutionBlocker -from comfy_api.v3.resources import Resources, ResourcesLocal + import copy +from abc import ABC, abstractmethod +from collections import Counter +from dataclasses import asdict, dataclass +from enum import Enum +from typing import Any, Callable, Literal, TypedDict, TypeVar + # used for type hinting import torch from spandrel import ImageModelDescriptor -from comfy.model_patcher import ModelPatcher -from comfy.samplers import Sampler, CFGGuider -from comfy.sd import CLIP -from comfy.controlnet import ControlNet -from comfy.sd import VAE -from comfy.sd import StyleModel as StyleModel_ +from typing_extensions import NotRequired + from comfy.clip_vision import ClipVisionModel from comfy.clip_vision import Output as ClipVisionOutput_ -from comfy_api.input import VideoInput +from comfy.controlnet import ControlNet from comfy.hooks import HookGroup, HookKeyframeGroup +from comfy.model_patcher import ModelPatcher +from comfy.samplers import CFGGuider, Sampler +from comfy.sd import CLIP, VAE +from comfy.sd import StyleModel as StyleModel_ +from comfy_api.input import VideoInput +from comfy_api.v3.resources import Resources, ResourcesLocal +from comfy_execution.graph import ExecutionBlocker + # from comfy_extras.nodes_images import SVG as SVG_ # NOTE: needs to be moved before can be imported due to circular reference @@ -1137,7 +1140,7 @@ class ComfyNodeV3: @classmethod def GET_NODE_INFO_V3(cls) -> dict[str, Any]: - schema = cls.GET_SCHEMA() + # schema = cls.GET_SCHEMA() # TODO: finish return None @@ -1183,84 +1186,84 @@ class ComfyNodeV3: #-------------------------------------------- _DESCRIPTION = None @classproperty - def DESCRIPTION(cls): + def DESCRIPTION(cls): # noqa if cls._DESCRIPTION is None: cls.GET_SCHEMA() return cls._DESCRIPTION _CATEGORY = None @classproperty - def CATEGORY(cls): + def CATEGORY(cls): # noqa if cls._CATEGORY is None: cls.GET_SCHEMA() return cls._CATEGORY _EXPERIMENTAL = None @classproperty - def EXPERIMENTAL(cls): + def EXPERIMENTAL(cls): # noqa if cls._EXPERIMENTAL is None: cls.GET_SCHEMA() return cls._EXPERIMENTAL _DEPRECATED = None @classproperty - def DEPRECATED(cls): + def DEPRECATED(cls): # noqa if cls._DEPRECATED is None: cls.GET_SCHEMA() return cls._DEPRECATED _API_NODE = None @classproperty - def API_NODE(cls): + def API_NODE(cls): # noqa if cls._API_NODE is None: cls.GET_SCHEMA() return cls._API_NODE _OUTPUT_NODE = None @classproperty - def OUTPUT_NODE(cls): + def OUTPUT_NODE(cls): # noqa if cls._OUTPUT_NODE is None: cls.GET_SCHEMA() return cls._OUTPUT_NODE _INPUT_IS_LIST = None @classproperty - def INPUT_IS_LIST(cls): + def INPUT_IS_LIST(cls): # noqa if cls._INPUT_IS_LIST is None: cls.GET_SCHEMA() return cls._INPUT_IS_LIST _OUTPUT_IS_LIST = None @classproperty - def OUTPUT_IS_LIST(cls): + def OUTPUT_IS_LIST(cls): # noqa if cls._OUTPUT_IS_LIST is None: cls.GET_SCHEMA() return cls._OUTPUT_IS_LIST _RETURN_TYPES = None @classproperty - def RETURN_TYPES(cls): + def RETURN_TYPES(cls): # noqa if cls._RETURN_TYPES is None: cls.GET_SCHEMA() return cls._RETURN_TYPES _RETURN_NAMES = None @classproperty - def RETURN_NAMES(cls): + def RETURN_NAMES(cls): # noqa if cls._RETURN_NAMES is None: cls.GET_SCHEMA() return cls._RETURN_NAMES _OUTPUT_TOOLTIPS = None @classproperty - def OUTPUT_TOOLTIPS(cls): + def OUTPUT_TOOLTIPS(cls): # noqa if cls._OUTPUT_TOOLTIPS is None: cls.GET_SCHEMA() return cls._OUTPUT_TOOLTIPS _NOT_IDEMPOTENT = None @classproperty - def NOT_IDEMPOTENT(cls): + def NOT_IDEMPOTENT(cls): # noqa if cls._NOT_IDEMPOTENT is None: cls.GET_SCHEMA() return cls._NOT_IDEMPOTENT @@ -1440,36 +1443,36 @@ class TestNode(ComfyNodeV3): def execute(cls, **kwargs): pass -if __name__ == "__main__": - print("hello there") - inputs: list[InputV3] = [ - Int.Input("tessfes", widgetType=String.io_type), - Int.Input("my_int"), - Custom("XYZ").Input("xyz"), - Custom("MODEL_M").Input("model1"), - Image.Input("my_image"), - Float.Input("my_float"), - MultiType.Input("my_inputs", [String, Custom("MODEL_M"), Custom("XYZ")]), - ] - Custom("XYZ").Input() - outputs: list[OutputV3] = [ - Image.Output("image"), - Custom("XYZ").Output("xyz"), - ] - - for c in inputs: - if isinstance(c, MultiType): - print(f"{c}, {type(c)}, {type(c).io_type}, {c.id}, {[x.io_type for x in c.io_types]}") - print(c.get_io_type_V1()) - else: - print(f"{c}, {type(c)}, {type(c).io_type}, {c.id}") - - for c in outputs: - print(f"{c}, {type(c)}, {type(c).io_type}, {c.id}") - - zz = TestNode() - print(zz.GET_NODE_INFO_V1()) - - # aa = NodeInfoV1() - # print(asdict(aa)) - # print(as_pruned_dict(aa)) +# if __name__ == "__main__": +# print("hello there") +# inputs: list[InputV3] = [ +# Int.Input("tessfes", widgetType=String.io_type), +# Int.Input("my_int"), +# Custom("XYZ").Input("xyz"), +# Custom("MODEL_M").Input("model1"), +# Image.Input("my_image"), +# Float.Input("my_float"), +# MultiType.Input("my_inputs", [String, Custom("MODEL_M"), Custom("XYZ")]), +# ] +# Custom("XYZ").Input() +# outputs: list[OutputV3] = [ +# Image.Output("image"), +# Custom("XYZ").Output("xyz"), +# ] +# +# for c in inputs: +# if isinstance(c, MultiType): +# print(f"{c}, {type(c)}, {type(c).io_type}, {c.id}, {[x.io_type for x in c.io_types]}") +# print(c.get_io_type_V1()) +# else: +# print(f"{c}, {type(c)}, {type(c).io_type}, {c.id}") +# +# for c in outputs: +# print(f"{c}, {type(c)}, {type(c).io_type}, {c.id}") +# +# zz = TestNode() +# print(zz.GET_NODE_INFO_V1()) +# +# # aa = NodeInfoV1() +# # print(asdict(aa)) +# # print(as_pruned_dict(aa)) diff --git a/comfy_api/v3/ui.py b/comfy_api/v3/ui.py index 976202244..390b986d4 100644 --- a/comfy_api/v3/ui.py +++ b/comfy_api/v3/ui.py @@ -1,19 +1,21 @@ from __future__ import annotations -from abc import ABC, abstractmethod + +import json +import os +import random from io import BytesIO import av +import numpy as np import torchaudio -from comfy_api.v3.io import Image, FolderType, _UIOutput, ComfyNodeV3 -# used for image preview -from comfy.cli_args import args -import folder_paths -import random from PIL import Image as PILImage from PIL.PngImagePlugin import PngInfo -import os -import json -import numpy as np + +import folder_paths + +# used for image preview +from comfy.cli_args import args +from comfy_api.v3.io import ComfyNodeV3, FolderType, Image, _UIOutput class SavedResult(dict): @@ -67,11 +69,13 @@ class PreviewImage(_UIOutput): "animated": (self.animated,) } + class PreviewMask(PreviewImage): def __init__(self, mask: PreviewMask.Type, animated: bool=False, cls: ComfyNodeV3=None, **kwargs): preview = mask.reshape((-1, 1, mask.shape[-2], mask.shape[-1])).movedim(1, -1).expand(-1, -1, -1, 3) super().__init__(preview, animated, cls, **kwargs) + # class UILatent(_UIOutput): # def __init__(self, values: list[SavedResult | dict], **kwargs): # output_dir = folder_paths.get_temp_directory() @@ -119,21 +123,15 @@ class PreviewMask(PreviewImage): # "latents": self.values, # } -class PreviewAudio(_UIOutput): - def __init__(self, values: list[SavedResult | dict], **kwargs): - self.values = values +class PreviewAudio(_UIOutput): def __init__(self, audio, cls: ComfyNodeV3=None, **kwargs): - output_dir = folder_paths.get_temp_directory() - type = "temp" - prefix_append = "_temp_" + ''.join(random.choice("abcdefghijklmnopqrstupvxyz") for x in range(5)) - filename_prefix = "ComfyUI" quality = "128k" format = "flac" - filename_prefix += prefix_append + filename_prefix = "ComfyUI_temp_" + ''.join(random.choice("abcdefghijklmnopqrstupvxyz") for x in range(5)) full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path( - filename_prefix, output_dir + filename_prefix, folder_paths.get_temp_directory() ) # Prepare metadata dictionary @@ -223,7 +221,7 @@ class PreviewAudio(_UIOutput): with open(output_path, 'wb') as f: f.write(output_buffer.getbuffer()) - results.append(SavedResult(file, subfolder, type)) + results.append(SavedResult(file, subfolder, FolderType.temp)) counter += 1 self.values = results @@ -231,6 +229,7 @@ class PreviewAudio(_UIOutput): def as_dict(self): return {"audio": self.values} + class PreviewUI3D(_UIOutput): def __init__(self, values: list[SavedResult | dict], **kwargs): self.values = values @@ -238,6 +237,7 @@ class PreviewUI3D(_UIOutput): def as_dict(self): return {"3d": self.values} + class PreviewText(_UIOutput): def __init__(self, value: str, **kwargs): self.value = value diff --git a/comfy_extras/v3/nodes_audio.py b/comfy_extras/v3/nodes_audio.py index ae20a1da9..fc6d5a3b4 100644 --- a/comfy_extras/v3/nodes_audio.py +++ b/comfy_extras/v3/nodes_audio.py @@ -1,38 +1,79 @@ from __future__ import annotations -import torchaudio -import folder_paths -import os -import io import hashlib +import json +import os +from io import BytesIO + +import av +import torch +import torchaudio + +import comfy.model_management +import folder_paths +import node_helpers +from comfy.cli_args import args from comfy_api.v3 import io, ui -class PreviewAudio_V3(io.ComfyNodeV3): +class ConditioningStableAudio_V3(io.ComfyNodeV3): @classmethod def DEFINE_SCHEMA(cls): return io.SchemaV3( - node_id="PreviewAudio_V3", - display_name="Preview Audio _V3", - category="audio", + node_id="ConditioningStableAudio_V3", + category="conditioning", inputs=[ - io.Audio.Input("audio"), + io.Conditioning.Input(id="positive"), + io.Conditioning.Input(id="negative"), + io.Float.Input(id="seconds_start", default=0.0, min=0.0, max=1000.0, step=0.1), + io.Float.Input(id="seconds_total", default=47.0, min=0.0, max=1000.0, step=0.1), + ], + outputs=[ + io.Conditioning.Output(id="positive_out", display_name="positive"), + io.Conditioning.Output(id="negative_out", display_name="negative"), ], - hidden=[io.Hidden.prompt, io.Hidden.extra_pnginfo], - is_output_node=True, ) @classmethod - def execute(cls, audio): - return io.NodeOutput(ui=ui.PreviewAudio(audio, cls=cls)) + def execute(cls, positive, negative, seconds_start, seconds_total) -> io.NodeOutput: + return io.NodeOutput( + node_helpers.conditioning_set_values( + positive, {"seconds_start": seconds_start, "seconds_total": seconds_total} + ), + node_helpers.conditioning_set_values( + negative, {"seconds_start": seconds_start, "seconds_total": seconds_total} + ), + ) + + +class EmptyLatentAudio_V3(io.ComfyNodeV3): + @classmethod + def DEFINE_SCHEMA(cls): + return io.SchemaV3( + node_id="EmptyLatentAudio_V3", + category="latent/audio", + inputs=[ + io.Float.Input(id="seconds", default=47.6, min=1.0, max=1000.0, step=0.1), + io.Int.Input( + id="batch_size", default=1, min=1, max=4096, tooltip="The number of latent images in the batch." + ), + ], + outputs=[io.Latent.Output()], + ) + + @classmethod + def execute(cls, seconds, batch_size) -> io.NodeOutput: + length = round((seconds * 44100 / 2048) / 2) * 2 + latent = torch.zeros([batch_size, 64, length], device=comfy.model_management.intermediate_device()) + return io.NodeOutput({"samples":latent, "type": "audio"}) class LoadAudio_V3(io.ComfyNodeV3): @classmethod def DEFINE_SCHEMA(cls): return io.SchemaV3( - node_id="LoadAudio_V3", - display_name="Load Audio _V3", + node_id="LoadAudio_V3", # frontend expects "LoadAudio" to work + display_name="Load Audio _V3", # frontend ignores "display_name" for this node category="audio", inputs=[ io.Combo.Input("audio", upload=io.UploadType.audio, options=cls.get_files_options()), @@ -65,14 +106,242 @@ class LoadAudio_V3(io.ComfyNodeV3): return True +class PreviewAudio_V3(io.ComfyNodeV3): + @classmethod + def DEFINE_SCHEMA(cls): + return io.SchemaV3( + node_id="PreviewAudio_V3", # frontend expects "PreviewAudio" to work + display_name="Preview Audio _V3", # frontend ignores "display_name" for this node + category="audio", + inputs=[ + io.Audio.Input("audio"), + ], + hidden=[io.Hidden.prompt, io.Hidden.extra_pnginfo], + is_output_node=True, + ) + + @classmethod + def execute(cls, audio) -> io.NodeOutput: + return io.NodeOutput(ui=ui.PreviewAudio(audio, cls=cls)) + + +class SaveAudioMP3_V3(io.ComfyNodeV3): + @classmethod + def DEFINE_SCHEMA(cls): + return io.SchemaV3( + node_id="SaveAudioMP3_V3", # frontend expects "SaveAudioMP3" to work + display_name="Save Audio(MP3) _V3", # frontend ignores "display_name" for this node + category="audio", + inputs=[ + io.Audio.Input("audio"), + io.String.Input("filename_prefix", default="audio/ComfyUI"), + io.Combo.Input("quality", options=["V0", "128k", "320k"], default="V0"), + ], + hidden=[io.Hidden.prompt, io.Hidden.extra_pnginfo], + is_output_node=True, + ) + + @classmethod + def execute(self, audio, filename_prefix="ComfyUI", format="mp3", quality="V0") -> io.NodeOutput: + return _save_audio(self, audio, filename_prefix, format, quality) + + +class SaveAudioOpus_V3(io.ComfyNodeV3): + @classmethod + def DEFINE_SCHEMA(cls): + return io.SchemaV3( + node_id="SaveAudioOpus_V3", # frontend expects "SaveAudioOpus" to work + display_name="Save Audio(Opus) _V3", # frontend ignores "display_name" for this node + category="audio", + inputs=[ + io.Audio.Input("audio"), + io.String.Input("filename_prefix", default="audio/ComfyUI"), + io.Combo.Input("quality", options=["64k", "96k", "128k", "192k", "320k"], default="128k"), + ], + hidden=[io.Hidden.prompt, io.Hidden.extra_pnginfo], + is_output_node=True, + ) + + @classmethod + def execute(self, audio, filename_prefix="ComfyUI", format="opus", quality="128k") -> io.NodeOutput: + return _save_audio(self, audio, filename_prefix, format, quality) + + +class SaveAudio_V3(io.ComfyNodeV3): + @classmethod + def DEFINE_SCHEMA(cls): + return io.SchemaV3( + node_id="SaveAudio_V3", # frontend expects "SaveAudio" to work + display_name="Save Audio _V3", # frontend ignores "display_name" for this node + category="audio", + inputs=[ + io.Audio.Input("audio"), + io.String.Input("filename_prefix", default="audio/ComfyUI"), + ], + hidden=[io.Hidden.prompt, io.Hidden.extra_pnginfo], + is_output_node=True, + ) + + @classmethod + def execute(cls, audio, filename_prefix="ComfyUI", format="flac") -> io.NodeOutput: + return _save_audio(cls, audio, filename_prefix, format) + + +class VAEDecodeAudio_V3(io.ComfyNodeV3): + @classmethod + def DEFINE_SCHEMA(cls): + return io.SchemaV3( + node_id="VAEDecodeAudio_V3", + category="latent/audio", + inputs=[ + io.Latent.Input(id="samples"), + io.Vae.Input(id="vae"), + ], + outputs=[io.Audio.Output()], + ) + + @classmethod + def execute(cls, vae, samples) -> io.NodeOutput: + audio = vae.decode(samples["samples"]).movedim(-1, 1) + std = torch.std(audio, dim=[1,2], keepdim=True) * 5.0 + std[std < 1.0] = 1.0 + audio /= std + return io.NodeOutput({"waveform": audio, "sample_rate": 44100}) + + +class VAEEncodeAudio_V3(io.ComfyNodeV3): + @classmethod + def DEFINE_SCHEMA(cls): + return io.SchemaV3( + node_id="VAEEncodeAudio_V3", + category="latent/audio", + inputs=[ + io.Audio.Input(id="audio"), + io.Vae.Input(id="vae"), + ], + outputs=[io.Latent.Output()], + ) + + @classmethod + def execute(cls, vae, audio) -> io.NodeOutput: + sample_rate = audio["sample_rate"] + if 44100 != sample_rate: + waveform = torchaudio.functional.resample(audio["waveform"], sample_rate, 44100) + else: + waveform = audio["waveform"] + return io.NodeOutput({"samples": vae.encode(waveform.movedim(1, -1))}) + + +def _save_audio(cls, audio, filename_prefix="ComfyUI", format="flac", quality="128k") -> io.NodeOutput: + full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path( + filename_prefix, folder_paths.get_output_directory() + ) + + # Prepare metadata dictionary + metadata = {} + if not args.disable_metadata: + if cls.hidden.prompt is not None: + metadata["prompt"] = json.dumps(cls.hidden.prompt) + if cls.hidden.extra_pnginfo is not None: + for x in cls.hidden.extra_pnginfo: + metadata[x] = json.dumps(cls.hidden.extra_pnginfo[x]) + + # Opus supported sample rates + OPUS_RATES = [8000, 12000, 16000, 24000, 48000] + + results = [] + for (batch_number, waveform) in enumerate(audio["waveform"].cpu()): + filename_with_batch_num = filename.replace("%batch_num%", str(batch_number)) + file = f"{filename_with_batch_num}_{counter:05}_.{format}" + output_path = os.path.join(full_output_folder, file) + + # Use original sample rate initially + sample_rate = audio["sample_rate"] + + # Handle Opus sample rate requirements + if format == "opus": + if sample_rate > 48000: + sample_rate = 48000 + elif sample_rate not in OPUS_RATES: + # Find the next highest supported rate + for rate in sorted(OPUS_RATES): + if rate > sample_rate: + sample_rate = rate + break + if sample_rate not in OPUS_RATES: # Fallback if still not supported + sample_rate = 48000 + + # Resample if necessary + if sample_rate != audio["sample_rate"]: + waveform = torchaudio.functional.resample(waveform, audio["sample_rate"], sample_rate) + + # Create output with specified format + output_buffer = BytesIO() + output_container = av.open(output_buffer, mode='w', format=format) + + # Set metadata on the container + for key, value in metadata.items(): + output_container.metadata[key] = value + + # Set up the output stream with appropriate properties + if format == "opus": + out_stream = output_container.add_stream("libopus", rate=sample_rate) + if quality == "64k": + out_stream.bit_rate = 64000 + elif quality == "96k": + out_stream.bit_rate = 96000 + elif quality == "128k": + out_stream.bit_rate = 128000 + elif quality == "192k": + out_stream.bit_rate = 192000 + elif quality == "320k": + out_stream.bit_rate = 320000 + elif format == "mp3": + out_stream = output_container.add_stream("libmp3lame", rate=sample_rate) + if quality == "V0": + #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 + out_stream.codec_context.qscale = 1 + elif quality == "128k": + out_stream.bit_rate = 128000 + elif quality == "320k": + out_stream.bit_rate = 320000 + else: # format == "flac": + out_stream = output_container.add_stream("flac", rate=sample_rate) + + frame = av.AudioFrame.from_ndarray( + waveform.movedim(0, 1).reshape(1, -1).float().numpy(), + format='flt', + layout='mono' if waveform.shape[0] == 1 else 'stereo', + ) + frame.sample_rate = sample_rate + frame.pts = 0 + output_container.mux(out_stream.encode(frame)) + + # Flush encoder + output_container.mux(out_stream.encode(None)) + + # Close containers + output_container.close() + + # Write the output to file + output_buffer.seek(0) + with open(output_path, 'wb') as f: + f.write(output_buffer.getbuffer()) + + results.append(ui.SavedResult(file, subfolder, io.FolderType.output)) + counter += 1 + + return io.NodeOutput(ui={"audio": results}) + + NODES_LIST: list[type[io.ComfyNodeV3]] = [ - # EmptyLatentAudio_V3, - # VAEEncodeAudio_V3, - # VAEDecodeAudio_V3, - # SaveAudio_V3, - # SaveAudioMP3_V3, - # SaveAudioOpus_V3, + ConditioningStableAudio_V3, + EmptyLatentAudio_V3, LoadAudio_V3, PreviewAudio_V3, - # ConditioningStableAudio_V3, + SaveAudioMP3_V3, + SaveAudioOpus_V3, + SaveAudio_V3, + VAEDecodeAudio_V3, + VAEEncodeAudio_V3, ] diff --git a/nodes.py b/nodes.py index 90d20e6a6..d38f2e810 100644 --- a/nodes.py +++ b/nodes.py @@ -2299,6 +2299,7 @@ def init_builtin_extra_nodes(): "nodes_tcfg.py", "nodes_v3_test.py", "nodes_v1_test.py", + "v3/nodes_audio.py", "v3/nodes_controlnet.py", "v3/nodes_images.py", "v3/nodes_mask.py", From c196dd5d0fc0c97ef6106c12bcde0981ccc97ee4 Mon Sep 17 00:00:00 2001 From: bigcat88 Date: Tue, 15 Jul 2025 17:40:15 +0300 Subject: [PATCH 3/3] V3: primitive nodes; additional ruff rules for V3 nodes --- comfy_extras/v3/nodes_audio.py | 28 +++---- comfy_extras/v3/nodes_controlnet.py | 34 ++++++-- comfy_extras/v3/nodes_images.py | 99 +++++++++++++--------- comfy_extras/v3/nodes_primitive.py | 104 ++++++++++++++++++++++++ comfy_extras/v3/nodes_stable_cascade.py | 40 ++++----- comfy_extras/v3/nodes_webcam.py | 25 +++--- nodes.py | 1 + pyproject.toml | 7 ++ 8 files changed, 242 insertions(+), 96 deletions(-) create mode 100644 comfy_extras/v3/nodes_primitive.py diff --git a/comfy_extras/v3/nodes_audio.py b/comfy_extras/v3/nodes_audio.py index fc6d5a3b4..72c4b6c65 100644 --- a/comfy_extras/v3/nodes_audio.py +++ b/comfy_extras/v3/nodes_audio.py @@ -65,14 +65,14 @@ class EmptyLatentAudio_V3(io.ComfyNodeV3): def execute(cls, seconds, batch_size) -> io.NodeOutput: length = round((seconds * 44100 / 2048) / 2) * 2 latent = torch.zeros([batch_size, 64, length], device=comfy.model_management.intermediate_device()) - return io.NodeOutput({"samples":latent, "type": "audio"}) + return io.NodeOutput({"samples": latent, "type": "audio"}) class LoadAudio_V3(io.ComfyNodeV3): @classmethod def DEFINE_SCHEMA(cls): return io.SchemaV3( - node_id="LoadAudio_V3", # frontend expects "LoadAudio" to work + node_id="LoadAudio_V3", # frontend expects "LoadAudio" to work display_name="Load Audio _V3", # frontend ignores "display_name" for this node category="audio", inputs=[ @@ -110,7 +110,7 @@ class PreviewAudio_V3(io.ComfyNodeV3): @classmethod def DEFINE_SCHEMA(cls): return io.SchemaV3( - node_id="PreviewAudio_V3", # frontend expects "PreviewAudio" to work + node_id="PreviewAudio_V3", # frontend expects "PreviewAudio" to work display_name="Preview Audio _V3", # frontend ignores "display_name" for this node category="audio", inputs=[ @@ -129,7 +129,7 @@ class SaveAudioMP3_V3(io.ComfyNodeV3): @classmethod def DEFINE_SCHEMA(cls): return io.SchemaV3( - node_id="SaveAudioMP3_V3", # frontend expects "SaveAudioMP3" to work + node_id="SaveAudioMP3_V3", # frontend expects "SaveAudioMP3" to work display_name="Save Audio(MP3) _V3", # frontend ignores "display_name" for this node category="audio", inputs=[ @@ -150,7 +150,7 @@ class SaveAudioOpus_V3(io.ComfyNodeV3): @classmethod def DEFINE_SCHEMA(cls): return io.SchemaV3( - node_id="SaveAudioOpus_V3", # frontend expects "SaveAudioOpus" to work + node_id="SaveAudioOpus_V3", # frontend expects "SaveAudioOpus" to work display_name="Save Audio(Opus) _V3", # frontend ignores "display_name" for this node category="audio", inputs=[ @@ -171,7 +171,7 @@ class SaveAudio_V3(io.ComfyNodeV3): @classmethod def DEFINE_SCHEMA(cls): return io.SchemaV3( - node_id="SaveAudio_V3", # frontend expects "SaveAudio" to work + node_id="SaveAudio_V3", # frontend expects "SaveAudio" to work display_name="Save Audio _V3", # frontend ignores "display_name" for this node category="audio", inputs=[ @@ -203,7 +203,7 @@ class VAEDecodeAudio_V3(io.ComfyNodeV3): @classmethod def execute(cls, vae, samples) -> io.NodeOutput: audio = vae.decode(samples["samples"]).movedim(-1, 1) - std = torch.std(audio, dim=[1,2], keepdim=True) * 5.0 + std = torch.std(audio, dim=[1, 2], keepdim=True) * 5.0 std[std < 1.0] = 1.0 audio /= std return io.NodeOutput({"waveform": audio, "sample_rate": 44100}) @@ -250,7 +250,7 @@ def _save_audio(cls, audio, filename_prefix="ComfyUI", format="flac", quality="1 OPUS_RATES = [8000, 12000, 16000, 24000, 48000] results = [] - for (batch_number, waveform) in enumerate(audio["waveform"].cpu()): + for batch_number, waveform in enumerate(audio["waveform"].cpu()): filename_with_batch_num = filename.replace("%batch_num%", str(batch_number)) file = f"{filename_with_batch_num}_{counter:05}_.{format}" output_path = os.path.join(full_output_folder, file) @@ -277,7 +277,7 @@ def _save_audio(cls, audio, filename_prefix="ComfyUI", format="flac", quality="1 # Create output with specified format output_buffer = BytesIO() - output_container = av.open(output_buffer, mode='w', format=format) + output_container = av.open(output_buffer, mode="w", format=format) # Set metadata on the container for key, value in metadata.items(): @@ -299,19 +299,19 @@ def _save_audio(cls, audio, filename_prefix="ComfyUI", format="flac", quality="1 elif format == "mp3": out_stream = output_container.add_stream("libmp3lame", rate=sample_rate) if quality == "V0": - #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 + # 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 out_stream.codec_context.qscale = 1 elif quality == "128k": out_stream.bit_rate = 128000 elif quality == "320k": out_stream.bit_rate = 320000 - else: # format == "flac": + else: # format == "flac": out_stream = output_container.add_stream("flac", rate=sample_rate) frame = av.AudioFrame.from_ndarray( waveform.movedim(0, 1).reshape(1, -1).float().numpy(), - format='flt', - layout='mono' if waveform.shape[0] == 1 else 'stereo', + format="flt", + layout="mono" if waveform.shape[0] == 1 else "stereo", ) frame.sample_rate = sample_rate frame.pts = 0 @@ -325,7 +325,7 @@ def _save_audio(cls, audio, filename_prefix="ComfyUI", format="flac", quality="1 # Write the output to file output_buffer.seek(0) - with open(output_path, 'wb') as f: + with open(output_path, "wb") as f: f.write(output_buffer.getbuffer()) results.append(ui.SavedResult(file, subfolder, io.FolderType.output)) diff --git a/comfy_extras/v3/nodes_controlnet.py b/comfy_extras/v3/nodes_controlnet.py index 12d91a1ce..528acf0fe 100644 --- a/comfy_extras/v3/nodes_controlnet.py +++ b/comfy_extras/v3/nodes_controlnet.py @@ -1,5 +1,5 @@ -from comfy.cldm.control_types import UNION_CONTROLNET_TYPES import comfy.utils +from comfy.cldm.control_types import UNION_CONTROLNET_TYPES from comfy_api.v3 import io @@ -27,11 +27,13 @@ class ControlNetApplyAdvanced_V3(io.ComfyNodeV3): ) @classmethod - def execute(cls, positive, negative, control_net, image, strength, start_percent, end_percent, vae=None, extra_concat=[]) -> io.NodeOutput: + def execute( + cls, positive, negative, control_net, image, strength, start_percent, end_percent, vae=None, extra_concat=[] + ) -> io.NodeOutput: if strength == 0: return io.NodeOutput(positive, negative) - control_hint = image.movedim(-1,1) + control_hint = image.movedim(-1, 1) cnets = {} out = [] @@ -40,16 +42,18 @@ class ControlNetApplyAdvanced_V3(io.ComfyNodeV3): for t in conditioning: d = t[1].copy() - prev_cnet = d.get('control', None) + prev_cnet = d.get("control", None) if prev_cnet in cnets: c_net = cnets[prev_cnet] else: - c_net = control_net.copy().set_cond_hint(control_hint, strength, (start_percent, end_percent), vae=vae, extra_concat=extra_concat) + c_net = control_net.copy().set_cond_hint( + control_hint, strength, (start_percent, end_percent), vae=vae, extra_concat=extra_concat + ) c_net.set_previous_controlnet(prev_cnet) cnets[prev_cnet] = c_net - d['control'] = c_net - d['control_apply_to_uncond'] = False + d["control"] = c_net + d["control_apply_to_uncond"] = False n = [t[0], d] c.append(n) out.append(c) @@ -107,7 +111,9 @@ class ControlNetInpaintingAliMamaApply_V3(ControlNetApplyAdvanced_V3): ) @classmethod - def execute(cls, positive, negative, control_net, vae, image, mask, strength, start_percent, end_percent) -> io.NodeOutput: + def execute( + cls, positive, negative, control_net, vae, image, mask, strength, start_percent, end_percent + ) -> io.NodeOutput: extra_concat = [] if control_net.concat_mask: mask = 1.0 - mask.reshape((-1, 1, mask.shape[-2], mask.shape[-1])) @@ -115,7 +121,17 @@ class ControlNetInpaintingAliMamaApply_V3(ControlNetApplyAdvanced_V3): image = image * mask_apply.movedim(1, -1).repeat(1, 1, 1, image.shape[3]) extra_concat = [mask] - return super().execute(positive, negative, control_net, image, strength, start_percent, end_percent, vae=vae, extra_concat=extra_concat) + return super().execute( + positive, + negative, + control_net, + image, + strength, + start_percent, + end_percent, + vae=vae, + extra_concat=extra_concat, + ) NODES_LIST: list[type[io.ComfyNodeV3]] = [ diff --git a/comfy_extras/v3/nodes_images.py b/comfy_extras/v3/nodes_images.py index 81790001e..a13be8a80 100644 --- a/comfy_extras/v3/nodes_images.py +++ b/comfy_extras/v3/nodes_images.py @@ -1,16 +1,16 @@ +import hashlib import json import os -import torch -import hashlib import numpy as np +import torch from PIL import Image, ImageOps, ImageSequence from PIL.PngImagePlugin import PngInfo -from comfy_api.v3 import io, ui -from comfy.cli_args import args import folder_paths import node_helpers +from comfy.cli_args import args +from comfy_api.v3 import io, ui class SaveImage_V3(io.ComfyNodeV3): @@ -29,7 +29,8 @@ class SaveImage_V3(io.ComfyNodeV3): io.String.Input( "filename_prefix", default="ComfyUI", - tooltip="The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes.", + tooltip="The prefix for the file to save. This may include formatting information " + "such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes.", ), ], hidden=[io.Hidden.prompt, io.Hidden.extra_pnginfo], @@ -42,8 +43,8 @@ class SaveImage_V3(io.ComfyNodeV3): filename_prefix, folder_paths.get_output_directory(), images[0].shape[1], images[0].shape[0] ) results = [] - for (batch_number, image) in enumerate(images): - i = 255. * image.cpu().numpy() + for batch_number, image in enumerate(images): + i = 255.0 * image.cpu().numpy() img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8)) metadata = None if not args.disable_metadata: @@ -82,13 +83,13 @@ class SaveAnimatedPNG_V3(io.ComfyNodeV3): @classmethod def execute(cls, images, fps, compress_level, filename_prefix="ComfyUI") -> io.NodeOutput: - full_output_folder, filename, counter, subfolder, filename_prefix = ( - folder_paths.get_save_image_path(filename_prefix, folder_paths.get_output_directory(), images[0].shape[1], images[0].shape[0]) + full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path( + filename_prefix, folder_paths.get_output_directory(), images[0].shape[1], images[0].shape[0] ) results = [] pil_images = [] for image in images: - img = Image.fromarray(np.clip(255. * image.cpu().numpy(), 0, 255).astype(np.uint8)) + img = Image.fromarray(np.clip(255.0 * image.cpu().numpy(), 0, 255).astype(np.uint8)) pil_images.append(img) metadata = None @@ -96,19 +97,34 @@ class SaveAnimatedPNG_V3(io.ComfyNodeV3): metadata = PngInfo() if cls.hidden.prompt is not None: metadata.add( - b"comf", "prompt".encode("latin-1", "strict") + b"\0" + json.dumps(cls.hidden.prompt).encode("latin-1", "strict"), after_idat=True + b"comf", + "prompt".encode("latin-1", "strict") + + b"\0" + + json.dumps(cls.hidden.prompt).encode("latin-1", "strict"), + after_idat=True, ) if cls.hidden.extra_pnginfo is not None: for x in cls.hidden.extra_pnginfo: metadata.add( - b"comf", x.encode("latin-1", "strict") + b"\0" + json.dumps(cls.hidden.extra_pnginfo[x]).encode("latin-1", "strict"), after_idat=True + b"comf", + x.encode("latin-1", "strict") + + b"\0" + + json.dumps(cls.hidden.extra_pnginfo[x]).encode("latin-1", "strict"), + after_idat=True, ) file = f"{filename}_{counter:05}_.png" - pil_images[0].save(os.path.join(full_output_folder, file), pnginfo=metadata, compress_level=compress_level, save_all=True, duration=int(1000.0/fps), append_images=pil_images[1:]) + pil_images[0].save( + os.path.join(full_output_folder, file), + pnginfo=metadata, + compress_level=compress_level, + save_all=True, + duration=int(1000.0 / fps), + append_images=pil_images[1:], + ) results.append(ui.SavedResult(file, subfolder, io.FolderType.output)) - return io.NodeOutput(ui={"images": results, "animated": (True,) }) + return io.NodeOutput(ui={"images": results, "animated": (True,)}) class SaveAnimatedWEBP_V3(io.ComfyNodeV3): @@ -136,11 +152,13 @@ class SaveAnimatedWEBP_V3(io.ComfyNodeV3): @classmethod def execute(cls, images, fps, filename_prefix, lossless, quality, method, num_frames=0) -> io.NodeOutput: method = cls.COMPRESS_METHODS.get(method) - full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, folder_paths.get_output_directory(), images[0].shape[1], images[0].shape[0]) + full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path( + filename_prefix, folder_paths.get_output_directory(), images[0].shape[1], images[0].shape[0] + ) results = [] pil_images = [] for image in images: - img = Image.fromarray(np.clip(255. * image.cpu().numpy(), 0, 255).astype(np.uint8)) + img = Image.fromarray(np.clip(255.0 * image.cpu().numpy(), 0, 255).astype(np.uint8)) pil_images.append(img) metadata = pil_images[0].getexif() @@ -148,7 +166,7 @@ class SaveAnimatedWEBP_V3(io.ComfyNodeV3): if cls.hidden.prompt is not None: metadata[0x0110] = "prompt:{}".format(json.dumps(cls.hidden.prompt)) if cls.hidden.extra_pnginfo is not None: - inital_exif = 0x010f + inital_exif = 0x010F for x in cls.hidden.extra_pnginfo: metadata[inital_exif] = "{}:{}".format(x, json.dumps(cls.hidden.extra_pnginfo[x])) inital_exif -= 1 @@ -160,8 +178,9 @@ class SaveAnimatedWEBP_V3(io.ComfyNodeV3): file = f"{filename}_{counter:05}_.webp" pil_images[i].save( os.path.join(full_output_folder, file), - save_all=True, duration=int(1000.0/fps), - append_images=pil_images[i + 1:i + num_frames], + save_all=True, + duration=int(1000.0 / fps), + append_images=pil_images[i + 1 : i + num_frames], exif=metadata, lossless=lossless, quality=quality, @@ -228,12 +247,12 @@ class LoadImage_V3(io.ComfyNodeV3): output_masks = [] w, h = None, None - excluded_formats = ['MPO'] + excluded_formats = ["MPO"] for i in ImageSequence.Iterator(img): i = node_helpers.pillow(ImageOps.exif_transpose, i) - if i.mode == 'I': + if i.mode == "I": i = i.point(lambda i: i * (1 / 255)) image = i.convert("RGB") @@ -246,14 +265,14 @@ class LoadImage_V3(io.ComfyNodeV3): image = np.array(image).astype(np.float32) / 255.0 image = torch.from_numpy(image)[None,] - if 'A' in i.getbands(): - mask = np.array(i.getchannel('A')).astype(np.float32) / 255.0 - mask = 1. - torch.from_numpy(mask) - elif i.mode == 'P' and 'transparency' in i.info: - mask = np.array(i.convert('RGBA').getchannel('A')).astype(np.float32) / 255.0 - mask = 1. - torch.from_numpy(mask) + if "A" in i.getbands(): + mask = np.array(i.getchannel("A")).astype(np.float32) / 255.0 + mask = 1.0 - torch.from_numpy(mask) + elif i.mode == "P" and "transparency" in i.info: + mask = np.array(i.convert("RGBA").getchannel("A")).astype(np.float32) / 255.0 + mask = 1.0 - torch.from_numpy(mask) else: - mask = torch.zeros((64,64), dtype=torch.float32, device="cpu") + mask = torch.zeros((64, 64), dtype=torch.float32, device="cpu") output_images.append(image) output_masks.append(mask.unsqueeze(0)) @@ -270,7 +289,7 @@ class LoadImage_V3(io.ComfyNodeV3): def fingerprint_inputs(s, image): image_path = folder_paths.get_annotated_filepath(image) m = hashlib.sha256() - with open(image_path, 'rb') as f: + with open(image_path, "rb") as f: m.update(f.read()) return m.digest().hex() @@ -288,8 +307,8 @@ class LoadImageOutput_V3(io.ComfyNodeV3): node_id="LoadImageOutput_V3", display_name="Load Image (from Outputs) _V3", description="Load an image from the output folder. " - "When the refresh button is clicked, the node will update the image list " - "and automatically select the first image, allowing for easy iteration.", + "When the refresh button is clicked, the node will update the image list " + "and automatically select the first image, allowing for easy iteration.", category="image", inputs=[ io.Combo.Input( @@ -317,12 +336,12 @@ class LoadImageOutput_V3(io.ComfyNodeV3): output_masks = [] w, h = None, None - excluded_formats = ['MPO'] + excluded_formats = ["MPO"] for i in ImageSequence.Iterator(img): i = node_helpers.pillow(ImageOps.exif_transpose, i) - if i.mode == 'I': + if i.mode == "I": i = i.point(lambda i: i * (1 / 255)) image = i.convert("RGB") @@ -335,12 +354,12 @@ class LoadImageOutput_V3(io.ComfyNodeV3): image = np.array(image).astype(np.float32) / 255.0 image = torch.from_numpy(image)[None,] - if 'A' in i.getbands(): - mask = np.array(i.getchannel('A')).astype(np.float32) / 255.0 - mask = 1. - torch.from_numpy(mask) - elif i.mode == 'P' and 'transparency' in i.info: - mask = np.array(i.convert('RGBA').getchannel('A')).astype(np.float32) / 255.0 - mask = 1. - torch.from_numpy(mask) + if "A" in i.getbands(): + mask = np.array(i.getchannel("A")).astype(np.float32) / 255.0 + mask = 1.0 - torch.from_numpy(mask) + elif i.mode == "P" and "transparency" in i.info: + mask = np.array(i.convert("RGBA").getchannel("A")).astype(np.float32) / 255.0 + mask = 1.0 - torch.from_numpy(mask) else: mask = torch.zeros((64, 64), dtype=torch.float32, device="cpu") output_images.append(image) @@ -359,7 +378,7 @@ class LoadImageOutput_V3(io.ComfyNodeV3): def fingerprint_inputs(s, image): image_path = folder_paths.get_annotated_filepath(image) m = hashlib.sha256() - with open(image_path, 'rb') as f: + with open(image_path, "rb") as f: m.update(f.read()) return m.digest().hex() diff --git a/comfy_extras/v3/nodes_primitive.py b/comfy_extras/v3/nodes_primitive.py new file mode 100644 index 000000000..debfa60d5 --- /dev/null +++ b/comfy_extras/v3/nodes_primitive.py @@ -0,0 +1,104 @@ +from __future__ import annotations + +import sys + +from comfy_api.v3 import io + + +class String_V3(io.ComfyNodeV3): + @classmethod + def DEFINE_SCHEMA(cls): + return io.SchemaV3( + node_id="PrimitiveString_V3", + display_name="String _V3", + category="utils/primitive", + inputs=[ + io.String.Input("value"), + ], + outputs=[io.String.Output()], + ) + + @classmethod + def execute(cls, value: str) -> io.NodeOutput: + return io.NodeOutput(value) + + +class StringMultiline_V3(io.ComfyNodeV3): + @classmethod + def DEFINE_SCHEMA(cls): + return io.SchemaV3( + node_id="PrimitiveStringMultiline_V3", + display_name="String (Multiline) _V3", + category="utils/primitive", + inputs=[ + io.String.Input("value", multiline=True), + ], + outputs=[io.String.Output()], + ) + + @classmethod + def execute(cls, value: str) -> io.NodeOutput: + return io.NodeOutput(value) + + +class Int_V3(io.ComfyNodeV3): + @classmethod + def DEFINE_SCHEMA(cls): + return io.SchemaV3( + node_id="PrimitiveInt_V3", + display_name="Int _V3", + category="utils/primitive", + inputs=[ + io.Int.Input("value", min=-sys.maxsize, max=sys.maxsize, control_after_generate=True), + ], + outputs=[io.Int.Output()], + ) + + @classmethod + def execute(cls, value: int) -> io.NodeOutput: + return io.NodeOutput(value) + + +class Float_V3(io.ComfyNodeV3): + @classmethod + def DEFINE_SCHEMA(cls): + return io.SchemaV3( + node_id="PrimitiveFloat_V3", + display_name="Float _V3", + category="utils/primitive", + inputs=[ + io.Float.Input("value", min=-sys.maxsize, max=sys.maxsize), + ], + outputs=[io.Float.Output()], + ) + + @classmethod + def execute(cls, value: float) -> io.NodeOutput: + return io.NodeOutput(value) + + +class Boolean_V3(io.ComfyNodeV3): + @classmethod + def DEFINE_SCHEMA(cls): + return io.SchemaV3( + node_id="PrimitiveBoolean_V3", + display_name="Boolean _V3", + category="utils/primitive", + inputs=[ + io.Boolean.Input("value"), + ], + outputs=[io.Boolean.Output()], + ) + + @classmethod + def execute(cls, value: bool) -> io.NodeOutput: + return io.NodeOutput(value) + + +NODES_LIST: list[type[io.ComfyNodeV3]] = [ + String_V3, + StringMultiline_V3, + Int_V3, + Float_V3, + Boolean_V3, +] diff --git a/comfy_extras/v3/nodes_stable_cascade.py b/comfy_extras/v3/nodes_stable_cascade.py index 36d7e3321..4693ad9eb 100644 --- a/comfy_extras/v3/nodes_stable_cascade.py +++ b/comfy_extras/v3/nodes_stable_cascade.py @@ -1,25 +1,25 @@ """ - This file is part of ComfyUI. - Copyright (C) 2024 Stability AI +This file is part of ComfyUI. +Copyright (C) 2024 Stability AI - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. +This program is free software: you can redistribute it and/or modify +it under the terms of the GNU General Public License as published by +the Free Software Foundation, either version 3 of the License, or +(at your option) any later version. - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. +This program is distributed in the hope that it will be useful, +but WITHOUT ANY WARRANTY; without even the implied warranty of +MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +GNU General Public License for more details. - You should have received a copy of the GNU General Public License - along with this program. If not, see . +You should have received a copy of the GNU General Public License +along with this program. If not, see . """ import torch -import nodes -import comfy.utils +import comfy.utils +import nodes from comfy_api.v3 import io @@ -30,7 +30,7 @@ class StableCascade_EmptyLatentImage_V3(io.ComfyNodeV3): node_id="StableCascade_EmptyLatentImage_V3", category="latent/stable_cascade", inputs=[ - io.Int.Input("width", default=1024,min=256,max=nodes.MAX_RESOLUTION, step=8), + io.Int.Input("width", default=1024, min=256, max=nodes.MAX_RESOLUTION, step=8), io.Int.Input("height", default=1024, min=256, max=nodes.MAX_RESOLUTION, step=8), io.Int.Input("compression", default=42, min=4, max=128, step=1), io.Int.Input("batch_size", default=1, min=1, max=4096), @@ -72,9 +72,9 @@ class StableCascade_StageC_VAEEncode_V3(io.ComfyNodeV3): out_width = (width // compression) * vae.downscale_ratio out_height = (height // compression) * vae.downscale_ratio - s = comfy.utils.common_upscale(image.movedim(-1,1), out_width, out_height, "bicubic", "center").movedim(1,-1) + s = comfy.utils.common_upscale(image.movedim(-1, 1), out_width, out_height, "bicubic", "center").movedim(1, -1) - c_latent = vae.encode(s[:,:,:,:3]) + c_latent = vae.encode(s[:, :, :, :3]) b_latent = torch.zeros([c_latent.shape[0], 4, (height // 8) * 2, (width // 8) * 2]) return io.NodeOutput({"samples": c_latent}, {"samples": b_latent}) @@ -90,7 +90,7 @@ class StableCascade_StageB_Conditioning_V3(io.ComfyNodeV3): io.Latent.Input("stage_c"), ], outputs=[ - io.Conditioning.Output(), + io.Conditioning.Output(), ], ) @@ -99,7 +99,7 @@ class StableCascade_StageB_Conditioning_V3(io.ComfyNodeV3): c = [] for t in conditioning: d = t[1].copy() - d['stable_cascade_prior'] = stage_c['samples'] + d["stable_cascade_prior"] = stage_c["samples"] n = [t[0], d] c.append(n) return io.NodeOutput(c) @@ -128,7 +128,7 @@ class StableCascade_SuperResolutionControlnet_V3(io.ComfyNodeV3): width = image.shape[-2] height = image.shape[-3] batch_size = image.shape[0] - controlnet_input = vae.encode(image[:,:,:,:3]).movedim(1, -1) + controlnet_input = vae.encode(image[:, :, :, :3]).movedim(1, -1) c_latent = torch.zeros([batch_size, 16, height // 16, width // 16]) b_latent = torch.zeros([batch_size, 4, height // 2, width // 2]) diff --git a/comfy_extras/v3/nodes_webcam.py b/comfy_extras/v3/nodes_webcam.py index 3a4cf8da0..6b65fa7d9 100644 --- a/comfy_extras/v3/nodes_webcam.py +++ b/comfy_extras/v3/nodes_webcam.py @@ -1,14 +1,13 @@ import hashlib -import torch import numpy as np +import torch from PIL import Image, ImageOps, ImageSequence -from comfy_api.v3 import io -import nodes import folder_paths import node_helpers - +import nodes +from comfy_api.v3 import io MAX_RESOLUTION = nodes.MAX_RESOLUTION @@ -51,12 +50,12 @@ class WebcamCapture_V3(io.ComfyNodeV3): output_masks = [] w, h = None, None - excluded_formats = ['MPO'] + excluded_formats = ["MPO"] for i in ImageSequence.Iterator(img): i = node_helpers.pillow(ImageOps.exif_transpose, i) - if i.mode == 'I': + if i.mode == "I": i = i.point(lambda i: i * (1 / 255)) image = i.convert("RGB") @@ -69,12 +68,12 @@ class WebcamCapture_V3(io.ComfyNodeV3): image = np.array(image).astype(np.float32) / 255.0 image = torch.from_numpy(image)[None,] - if 'A' in i.getbands(): - mask = np.array(i.getchannel('A')).astype(np.float32) / 255.0 - mask = 1. - torch.from_numpy(mask) - elif i.mode == 'P' and 'transparency' in i.info: - mask = np.array(i.convert('RGBA').getchannel('A')).astype(np.float32) / 255.0 - mask = 1. - torch.from_numpy(mask) + if "A" in i.getbands(): + mask = np.array(i.getchannel("A")).astype(np.float32) / 255.0 + mask = 1.0 - torch.from_numpy(mask) + elif i.mode == "P" and "transparency" in i.info: + mask = np.array(i.convert("RGBA").getchannel("A")).astype(np.float32) / 255.0 + mask = 1.0 - torch.from_numpy(mask) else: mask = torch.zeros((64, 64), dtype=torch.float32, device="cpu") output_images.append(image) @@ -93,7 +92,7 @@ class WebcamCapture_V3(io.ComfyNodeV3): def fingerprint_inputs(s, image, width, height, capture_on_queue): image_path = folder_paths.get_annotated_filepath(image) m = hashlib.sha256() - with open(image_path, 'rb') as f: + with open(image_path, "rb") as f: m.update(f.read()) return m.digest().hex() diff --git a/nodes.py b/nodes.py index d38f2e810..11a1b85cb 100644 --- a/nodes.py +++ b/nodes.py @@ -2303,6 +2303,7 @@ def init_builtin_extra_nodes(): "v3/nodes_controlnet.py", "v3/nodes_images.py", "v3/nodes_mask.py", + "v3/nodes_primitive.py", "v3/nodes_webcam.py", "v3/nodes_stable_cascade.py", ] diff --git a/pyproject.toml b/pyproject.toml index 96ead2157..69e84a997 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -12,6 +12,8 @@ documentation = "https://docs.comfy.org/" [tool.ruff] lint.select = [ + "E", # pycodestyle errors + "I", # isort "N805", # invalid-first-argument-name-for-method "S307", # suspicious-eval-usage "S102", # exec @@ -22,3 +24,8 @@ lint.select = [ "F", ] exclude = ["*.ipynb"] +line-length = 120 +lint.pycodestyle.ignore-overlong-task-comments = true + +[tool.ruff.lint.per-file-ignores] +"!comfy_extras/v3/*" = ["E", "I"] # enable these rules only for V3 nodes