ComfyUI/comfy_extras/v3/nodes_video.py

211 lines
8.1 KiB
Python

from __future__ import annotations
import json
import os
from fractions import Fraction
import av
import torch
import folder_paths
from comfy.cli_args import args
from comfy_api.input import AudioInput, ImageInput, VideoInput
from comfy_api.input_impl import VideoFromComponents, VideoFromFile
from comfy_api.util import VideoCodec, VideoComponents, VideoContainer
from comfy_api.v3 import io, ui
class CreateVideo(io.ComfyNode):
@classmethod
def define_schema(cls):
return io.Schema(
node_id="CreateVideo_V3",
display_name="Create Video _V3",
category="image/video",
description="Create a video from images.",
inputs=[
io.Image.Input("images", tooltip="The images to create a video from."),
io.Float.Input("fps", default=30.0, min=1.0, max=120.0, step=1.0),
io.Audio.Input("audio", optional=True, tooltip="The audio to add to the video."),
],
outputs=[
io.Video.Output(),
],
)
@classmethod
def execute(cls, images: ImageInput, fps: float, audio: AudioInput = None):
return io.NodeOutput(VideoFromComponents(
VideoComponents(
images=images,
audio=audio,
frame_rate=Fraction(fps),
)
))
class GetVideoComponents(io.ComfyNode):
@classmethod
def define_schema(cls):
return io.Schema(
node_id="GetVideoComponents_V3",
display_name="Get Video Components _V3",
category="image/video",
description="Extracts all components from a video: frames, audio, and framerate.",
inputs=[
io.Video.Input("video", tooltip="The video to extract components from."),
],
outputs=[
io.Image.Output(display_name="images"),
io.Audio.Output(display_name="audio"),
io.Float.Output(display_name="fps"),
],
)
@classmethod
def execute(cls, video: VideoInput):
components = video.get_components()
return io.NodeOutput(components.images, components.audio, float(components.frame_rate))
class LoadVideo(io.ComfyNode):
@classmethod
def define_schema(cls):
input_dir = folder_paths.get_input_directory()
files = [f for f in os.listdir(input_dir) if os.path.isfile(os.path.join(input_dir, f))]
files = folder_paths.filter_files_content_types(files, ["video"])
return io.Schema(
node_id="LoadVideo_V3",
display_name="Load Video _V3",
category="image/video",
inputs=[
io.Combo.Input("file", options=sorted(files), upload=io.UploadType.video),
],
outputs=[
io.Video.Output(),
],
)
@classmethod
def execute(cls, file):
video_path = folder_paths.get_annotated_filepath(file)
return io.NodeOutput(VideoFromFile(video_path))
@classmethod
def fingerprint_inputs(s, file):
video_path = folder_paths.get_annotated_filepath(file)
mod_time = os.path.getmtime(video_path)
# Instead of hashing the file, we can just use the modification time to avoid rehashing large files.
return mod_time
@classmethod
def validate_inputs(s, file):
if not folder_paths.exists_annotated_filepath(file):
return "Invalid video file: {}".format(file)
return True
class SaveVideo(io.ComfyNode):
@classmethod
def define_schema(cls):
return io.Schema(
node_id="SaveVideo_V3",
display_name="Save Video _V3",
category="image/video",
description="Saves the input images to your ComfyUI output directory.",
inputs=[
io.Video.Input("video", tooltip="The video to save."),
io.String.Input("filename_prefix", default="video/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."),
io.Combo.Input("format", options=VideoContainer.as_input(), default="auto", tooltip="The format to save the video as."),
io.Combo.Input("codec", options=VideoCodec.as_input(), default="auto", tooltip="The codec to use for the video."),
],
outputs=[],
hidden=[io.Hidden.prompt, io.Hidden.extra_pnginfo],
is_output_node=True,
)
@classmethod
def execute(cls, video: VideoInput, filename_prefix, format, codec):
width, height = video.get_dimensions()
full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(
filename_prefix,
folder_paths.get_output_directory(),
width,
height
)
saved_metadata = None
if not args.disable_metadata:
metadata = {}
if cls.hidden.extra_pnginfo is not None:
metadata.update(cls.hidden.extra_pnginfo)
if cls.hidden.prompt is not None:
metadata["prompt"] = cls.hidden.prompt
if len(metadata) > 0:
saved_metadata = metadata
file = f"{filename}_{counter:05}_.{VideoContainer.get_extension(format)}"
video.save_to(
os.path.join(full_output_folder, file),
format=format,
codec=codec,
metadata=saved_metadata
)
return io.NodeOutput(ui=ui.PreviewVideo([ui.SavedResult(file, subfolder, io.FolderType.output)]))
class SaveWEBM(io.ComfyNode):
@classmethod
def define_schema(cls):
return io.Schema(
node_id="SaveWEBM_V3",
category="image/video",
is_experimental=True,
inputs=[
io.Image.Input("images"),
io.String.Input("filename_prefix", default="ComfyUI"),
io.Combo.Input("codec", options=["vp9", "av1"]),
io.Float.Input("fps", default=24.0, min=0.01, max=1000.0, step=0.01),
io.Float.Input("crf", default=32.0, min=0, max=63.0, step=1, tooltip="Higher crf means lower quality with a smaller file size, lower crf means higher quality higher filesize."),
],
outputs=[],
hidden=[io.Hidden.prompt, io.Hidden.extra_pnginfo],
is_output_node=True,
)
@classmethod
def execute(cls, images, codec, fps, filename_prefix, crf):
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]
)
file = f"{filename}_{counter:05}_.webm"
container = av.open(os.path.join(full_output_folder, file), mode="w")
if cls.hidden.prompt is not None:
container.metadata["prompt"] = json.dumps(cls.hidden.prompt)
if cls.hidden.extra_pnginfo is not None:
for x in cls.hidden.extra_pnginfo:
container.metadata[x] = json.dumps(cls.hidden.extra_pnginfo[x])
codec_map = {"vp9": "libvpx-vp9", "av1": "libsvtav1"}
stream = container.add_stream(codec_map[codec], rate=Fraction(round(fps * 1000), 1000))
stream.width = images.shape[-2]
stream.height = images.shape[-3]
stream.pix_fmt = "yuv420p10le" if codec == "av1" else "yuv420p"
stream.bit_rate = 0
stream.options = {'crf': str(crf)}
if codec == "av1":
stream.options["preset"] = "6"
for frame in images:
frame = av.VideoFrame.from_ndarray(torch.clamp(frame[..., :3] * 255, min=0, max=255).to(device=torch.device("cpu"), dtype=torch.uint8).numpy(), format="rgb24")
for packet in stream.encode(frame):
container.mux(packet)
container.mux(stream.encode())
container.close()
return io.NodeOutput(ui=ui.PreviewVideo([ui.SavedResult(file, subfolder, io.FolderType.output)]))
NODES_LIST = [CreateVideo, GetVideoComponents, LoadVideo, SaveVideo, SaveWEBM]