Jony
c646b0d1d7
- K3_video.py / K3_video_firstlast.py / K3_motion_control.py - K_video.py - kling_video.py (KlingVideo / KlingFirstLastFrame / KlingMotionControlTest) - seedance_video.py (Seedance / SeedanceMultiModal) 所有视频节点下载视频时改写到 tempfile.mkstemp() 临时路径， 最终落盘完全交给下游保存节点处理，不再重复写入 output/video/。 同步清理已无用的 _get_video_dir / _get_next_counter / import re 等辅助代码。
444 lines
18 KiB
Python
444 lines
18 KiB
Python
"""
|
||
Seedance 视频生成节点
|
||
节点列表:
|
||
- Seedance: 文生视频 / 图生视频 / 首尾帧生视频（根据图片输入自动切换模式）
|
||
"""
|
||
|
||
import io
|
||
import os
|
||
import tempfile
|
||
|
||
import aiohttp
|
||
import torch
|
||
|
||
from ..clients.seedance_client import SeedanceClient
|
||
from ..clients.gemini_client import GeminiAPIClient
|
||
from ..utils.image_utils import tensor_to_pil, encode_image_to_base64, pil_to_tensor
|
||
from ..utils.r2_uploader import upload_video, upload_audio
|
||
|
||
from comfy_api.latest import InputImpl
|
||
|
||
|
||
# ── 模型列表 ──────────────────────────────────────────────────────────────────
|
||
|
||
_MODELS = [
|
||
"doubao-seedance-2-0-260128",
|
||
]
|
||
|
||
_RESOLUTIONS = ["720p", "1080p", "480p"]
|
||
|
||
|
||
# ── 模型能力判断 ──────────────────────────────────────────────────────────────
|
||
|
||
def _supports_camera_fixed(model: str) -> bool:
|
||
"""2.0 系列不支持固定镜头"""
|
||
return False # 当前仅 2.0 模型，均不支持
|
||
|
||
|
||
# ── 工具函数 ──────────────────────────────────────────────────────────────────
|
||
|
||
def _tensor_to_base64_url(tensor) -> str:
|
||
"""ComfyUI IMAGE tensor → data:image/png;base64,xxx"""
|
||
pil_images = tensor_to_pil(tensor)
|
||
b64 = encode_image_to_base64(pil_images[0], format="PNG")
|
||
return f"data:image/png;base64,{b64}"
|
||
|
||
|
||
|
||
async def _url_to_tensor(url: str) -> torch.Tensor:
|
||
"""从 URL 下载图片并转为 ComfyUI IMAGE tensor，失败时返回 None"""
|
||
try:
|
||
from PIL import Image
|
||
async with aiohttp.ClientSession() as session:
|
||
async with session.get(url, allow_redirects=True) as resp:
|
||
if resp.status != 200:
|
||
return None
|
||
data = await resp.read()
|
||
img = Image.open(io.BytesIO(data)).convert("RGB")
|
||
return pil_to_tensor([img])
|
||
except Exception as e:
|
||
print(f"[Seedance] 末帧图片下载失败: {e}")
|
||
return None
|
||
|
||
|
||
def _show_balance():
|
||
"""完成后打印余额（静默失败）"""
|
||
try:
|
||
client = GeminiAPIClient()
|
||
data = client.query_balance_sync()
|
||
print(f"Seedance: {client.format_balance_info(data)}")
|
||
except Exception:
|
||
pass
|
||
|
||
|
||
def _make_pbar():
|
||
try:
|
||
from comfy.utils import ProgressBar
|
||
return ProgressBar(100)
|
||
except Exception:
|
||
return None
|
||
|
||
|
||
def _make_callbacks(tag: str, pbar):
|
||
def on_stage(stage: str):
|
||
if stage == "submitting":
|
||
print(f"[{tag}] 提交中...")
|
||
if pbar: pbar.update_absolute(0, 100)
|
||
elif stage.startswith("submitted:"):
|
||
print(f"[{tag}] 已提交 → {stage.split(':', 1)[1]}")
|
||
if pbar: pbar.update_absolute(5, 100)
|
||
elif stage == "downloading":
|
||
print(f"[{tag}] 下载视频中...")
|
||
if pbar: pbar.update_absolute(99, 100)
|
||
elif stage == "done":
|
||
print(f"[{tag}] 完成")
|
||
if pbar: pbar.update_absolute(100, 100)
|
||
|
||
def on_progress(pct: int):
|
||
if pbar: pbar.update_absolute(5 + int(pct * 0.94), 100)
|
||
|
||
return on_stage, on_progress
|
||
|
||
|
||
|
||
# ── 统一节点 ─────────────────────────────────────────────────────────────────
|
||
#
|
||
# 模式由图片输入自动判断：
|
||
# 首帧 = None → T2V 文生视频 （联网搜索生效）
|
||
# 首帧 = 图片，尾帧 = None → I2V 图生视频 （固定镜头生效，当前 2.0 不支持故忽略）
|
||
# 首帧 = 图片，尾帧 = 图片 → FlipFlop 首尾帧（联网搜索/固定镜头均忽略）
|
||
|
||
class Seedance:
|
||
"""Seedance 视频生成（文生视频 / 图生视频 / 首尾帧，自动判断模式）"""
|
||
|
||
@classmethod
|
||
def INPUT_TYPES(cls):
|
||
return {
|
||
"required": {
|
||
"提示词": ("STRING", {"multiline": True, "default": ""}),
|
||
"模型": (_MODELS, {"default": "doubao-seedance-2-0-260128"}),
|
||
"分辨率": (_RESOLUTIONS, {"default": "720p"}),
|
||
"宽高比": (["16:9", "adaptive", "9:16", "1:1", "4:3", "3:4", "21:9"],
|
||
{"default": "16:9"}),
|
||
"时长秒(-1=自动)": ("INT", {"default": 5, "min": -1, "max": 30, "step": 1}),
|
||
"生成音频": (["关闭", "打开"], {"default": "关闭"}),
|
||
"联网搜索": (["关闭", "打开"], {"default": "关闭"}),
|
||
"返回末帧图片": (["关闭", "打开"], {"default": "关闭"}),
|
||
"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffff}),
|
||
},
|
||
"optional": {
|
||
"首帧图片": ("IMAGE",),
|
||
"尾帧图片": ("IMAGE",),
|
||
},
|
||
}
|
||
|
||
RETURN_TYPES = ("VIDEO", "IMAGE")
|
||
RETURN_NAMES = ("视频", "末帧图片")
|
||
FUNCTION = "generate"
|
||
CATEGORY = "comfyui_o1key/Seedance"
|
||
|
||
async def generate(self, **kwargs):
|
||
prompt = kwargs["提示词"].strip()
|
||
model = kwargs["模型"]
|
||
resolution = kwargs["分辨率"]
|
||
ratio = kwargs["宽高比"]
|
||
duration = kwargs["时长秒(-1=自动)"]
|
||
gen_audio = kwargs["生成音频"] == "打开"
|
||
web_search = kwargs["联网搜索"] == "打开"
|
||
return_last = kwargs["返回末帧图片"] == "打开"
|
||
seed = kwargs.get("seed", 0)
|
||
first_image = kwargs.get("首帧图片", None)
|
||
last_image = kwargs.get("尾帧图片", None)
|
||
|
||
# 模式判断
|
||
if first_image is None and last_image is not None:
|
||
raise ValueError("请同时接入首帧图片，或仅接入首帧图片。")
|
||
if first_image is None:
|
||
mode = "t2v"
|
||
tag = "Seedance文生视频"
|
||
file_prefix = "seedance_t2v"
|
||
elif last_image is None:
|
||
mode = "i2v"
|
||
tag = "Seedance图生视频"
|
||
file_prefix = "seedance_i2v"
|
||
else:
|
||
mode = "flipflop"
|
||
tag = "Seedance首尾帧"
|
||
file_prefix = "seedance_flip"
|
||
|
||
if not prompt:
|
||
raise ValueError("提示词不能为空。")
|
||
if duration == -1 and mode == "t2v":
|
||
pass # 2.0 均支持自动时长
|
||
elif duration == -1 and mode != "t2v":
|
||
pass # 2.0 均支持自动时长
|
||
|
||
metadata: dict = {
|
||
"resolution": resolution,
|
||
"watermark": False,
|
||
}
|
||
if ratio != "adaptive":
|
||
metadata["ratio"] = ratio
|
||
if duration != -1:
|
||
metadata["duration"] = duration
|
||
if gen_audio:
|
||
metadata["generate_audio"] = True
|
||
if return_last:
|
||
metadata["return_last_frame"] = True
|
||
if seed != 0:
|
||
metadata["seed"] = seed
|
||
|
||
# 模式专属参数
|
||
if mode == "t2v":
|
||
if web_search:
|
||
metadata["tools"] = [{"type": "web_search"}]
|
||
body = {
|
||
"model": model,
|
||
"prompt": prompt,
|
||
"metadata": metadata,
|
||
}
|
||
|
||
elif mode == "i2v":
|
||
first_url = _tensor_to_base64_url(first_image)
|
||
metadata["content"] = [
|
||
{
|
||
"type": "image_url",
|
||
"image_url": {"url": first_url},
|
||
"role": "first_frame",
|
||
},
|
||
{"type": "text", "text": prompt},
|
||
]
|
||
body = {
|
||
"model": model,
|
||
"prompt": prompt,
|
||
"images": [first_url],
|
||
"metadata": metadata,
|
||
}
|
||
|
||
else: # flipflop
|
||
first_url = _tensor_to_base64_url(first_image)
|
||
last_url = _tensor_to_base64_url(last_image)
|
||
metadata["content"] = [
|
||
{
|
||
"type": "image_url",
|
||
"image_url": {"url": first_url},
|
||
"role": "first_frame",
|
||
},
|
||
{
|
||
"type": "image_url",
|
||
"image_url": {"url": last_url},
|
||
"role": "last_frame",
|
||
},
|
||
{"type": "text", "text": prompt},
|
||
]
|
||
body = {
|
||
"model": model,
|
||
"prompt": prompt,
|
||
"images": [first_url],
|
||
"metadata": metadata,
|
||
}
|
||
|
||
# 保存路径（临时文件，避免与下游保存节点重复落盘）
|
||
_, save_path = tempfile.mkstemp(suffix=".mp4", prefix=f"{file_prefix}_")
|
||
|
||
client = SeedanceClient()
|
||
pbar = _make_pbar()
|
||
on_stage, on_prog = _make_callbacks(tag, pbar)
|
||
|
||
try:
|
||
result_path, last_frame_url = await client.generate_async(
|
||
body=body, save_path=save_path,
|
||
on_stage=on_stage, on_progress=on_prog,
|
||
)
|
||
last_frame_tensor = None
|
||
if return_last and last_frame_url:
|
||
last_frame_tensor = await _url_to_tensor(last_frame_url)
|
||
return (InputImpl.VideoFromFile(result_path), last_frame_tensor)
|
||
finally:
|
||
_show_balance()
|
||
|
||
|
||
# ── 多模态参考生视频节点 ──────────────────────────────────────────────────────
|
||
|
||
class SeedanceMultiModal:
|
||
"""Seedance 2.0 多模态参考生视频（参考图片 + 参考视频 + 参考音频 + 文本）"""
|
||
|
||
@classmethod
|
||
def INPUT_TYPES(cls):
|
||
return {
|
||
"required": {
|
||
"提示词": ("STRING", {"multiline": True, "default": ""}),
|
||
"模型": (_MODELS, {"default": "doubao-seedance-2-0-260128"}),
|
||
"分辨率": (_RESOLUTIONS, {"default": "720p"}),
|
||
"宽高比": (["adaptive", "16:9", "9:16", "1:1", "4:3", "3:4", "21:9"],
|
||
{"default": "adaptive"}),
|
||
"时长秒(-1=自动)": ("INT", {"default": 5, "min": -1, "max": 15, "step": 1}),
|
||
"生成音频": (["关闭", "打开"], {"default": "关闭"}),
|
||
"联网搜索": (["关闭", "打开"], {"default": "关闭"}),
|
||
"返回末帧图片": (["关闭", "打开"], {"default": "关闭"}),
|
||
"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffff}),
|
||
},
|
||
"optional": {
|
||
"参考图片": ("IMAGE",),
|
||
"参考视频1": ("VIDEO",),
|
||
"参考视频2": ("VIDEO",),
|
||
"参考视频3": ("VIDEO",),
|
||
"参考音频1": ("AUDIO",),
|
||
"参考音频2": ("AUDIO",),
|
||
"参考音频3": ("AUDIO",),
|
||
},
|
||
}
|
||
|
||
RETURN_TYPES = ("VIDEO", "IMAGE")
|
||
RETURN_NAMES = ("视频", "末帧图片")
|
||
FUNCTION = "generate"
|
||
CATEGORY = "comfyui_o1key/Seedance"
|
||
INPUT_IS_LIST = True
|
||
|
||
async def generate(self, **kwargs):
|
||
# INPUT_IS_LIST=True 时所有参数都是列表，取第一个元素
|
||
def _first(v, default=None):
|
||
if isinstance(v, list):
|
||
return v[0] if v else default
|
||
return v if v is not None else default
|
||
|
||
prompt = _first(kwargs.get("提示词"), "").strip()
|
||
model = _first(kwargs.get("模型"))
|
||
resolution = _first(kwargs.get("分辨率"))
|
||
ratio = _first(kwargs.get("宽高比"))
|
||
duration = _first(kwargs.get("时长秒(-1=自动)"), 5)
|
||
gen_audio = _first(kwargs.get("生成音频"), "关闭") == "打开"
|
||
web_search = _first(kwargs.get("联网搜索"), "关闭") == "打开"
|
||
return_last = _first(kwargs.get("返回末帧图片"), "关闭") == "打开"
|
||
seed = _first(kwargs.get("seed"), 0)
|
||
|
||
# 参考图片：INPUT_IS_LIST 时是 [tensor, tensor, ...] 列表，直接保留
|
||
raw_images = kwargs.get("参考图片", None)
|
||
ref_images = [img for img in raw_images if img is not None] if raw_images else None
|
||
|
||
ref_videos = [_first(kwargs.get(f"参考视频{i}")) for i in range(1, 4)]
|
||
ref_audios = [_first(kwargs.get(f"参考音频{i}")) for i in range(1, 4)]
|
||
|
||
ref_videos = [v for v in ref_videos if v is not None]
|
||
ref_audios = [a for a in ref_audios if a is not None]
|
||
|
||
# ── 校验 ──────────────────────────────────────────────────────────
|
||
has_image = bool(ref_images)
|
||
has_video = len(ref_videos) > 0
|
||
has_audio = len(ref_audios) > 0
|
||
|
||
if not has_image and not has_video and not has_audio and not prompt:
|
||
raise ValueError("至少需要提供参考图片、参考视频或提示词之一。")
|
||
if has_audio and not has_image and not has_video:
|
||
raise ValueError("不可单独输入音频，请至少连接一张参考图片或一个参考视频。")
|
||
|
||
# ── 构建 content 列表 ─────────────────────────────────────────────
|
||
content = []
|
||
|
||
# 参考图片（批次，最多9张）
|
||
if has_image:
|
||
imgs = ref_images[:9]
|
||
if len(ref_images) > 9:
|
||
print(f"[SeedanceMultiModal] 参考图片超过9张，仅取前9张（共{len(ref_images)}张）")
|
||
for img_tensor in imgs:
|
||
# 每个 tensor 可能是 [1,H,W,C] 或 [H,W,C]，统一确保有 batch 维
|
||
if img_tensor.dim() == 3:
|
||
img_tensor = img_tensor.unsqueeze(0)
|
||
url = _tensor_to_base64_url(img_tensor)
|
||
content.append({
|
||
"type": "image_url",
|
||
"image_url": {"url": url},
|
||
"role": "reference_image",
|
||
})
|
||
|
||
# 参考视频（最多3个）
|
||
for v in ref_videos:
|
||
url = await upload_video(v)
|
||
content.append({
|
||
"type": "video_url",
|
||
"video_url": {"url": url},
|
||
"role": "reference_video",
|
||
})
|
||
|
||
# 参考音频（最多3段）
|
||
for a in ref_audios:
|
||
url = await upload_audio(a)
|
||
content.append({
|
||
"type": "audio_url",
|
||
"audio_url": {"url": url},
|
||
"role": "reference_audio",
|
||
})
|
||
|
||
# 文本提示词（放最后）
|
||
if prompt:
|
||
content.append({"type": "text", "text": prompt})
|
||
|
||
if not content:
|
||
raise ValueError("content 为空，请至少提供参考图片、参考视频或提示词。")
|
||
|
||
# ── 构建请求体（new-api 兼容格式）──────────────────────────────────
|
||
metadata: dict = {
|
||
"resolution": resolution,
|
||
"watermark": False,
|
||
"content": content,
|
||
}
|
||
|
||
if ratio != "adaptive":
|
||
metadata["ratio"] = ratio
|
||
if duration != -1:
|
||
metadata["duration"] = duration
|
||
if gen_audio:
|
||
metadata["generate_audio"] = True
|
||
if return_last:
|
||
metadata["return_last_frame"] = True
|
||
if seed != 0:
|
||
metadata["seed"] = seed
|
||
if web_search:
|
||
metadata["tools"] = [{"type": "web_search"}]
|
||
|
||
# 顶层 image：取第一张参考图的 base64（new-api 单图字段）
|
||
first_image_url = next(
|
||
(item["image_url"]["url"] for item in content if item["type"] == "image_url"),
|
||
None,
|
||
)
|
||
|
||
body = {
|
||
"model": model,
|
||
"prompt": prompt if prompt else " ",
|
||
"metadata": metadata,
|
||
}
|
||
if first_image_url:
|
||
body["image"] = first_image_url
|
||
|
||
# ── 保存路径（临时文件，避免与下游保存节点重复落盘）──────────────────
|
||
_, save_path = tempfile.mkstemp(suffix=".mp4", prefix="seedance_mm_")
|
||
|
||
client = SeedanceClient()
|
||
pbar = _make_pbar()
|
||
on_stage, on_prog = _make_callbacks("Seedance多模态", pbar)
|
||
|
||
try:
|
||
result_path, last_frame_url = await client.generate_async(
|
||
body=body, save_path=save_path,
|
||
on_stage=on_stage, on_progress=on_prog,
|
||
)
|
||
last_frame_tensor = None
|
||
if return_last and last_frame_url:
|
||
last_frame_tensor = await _url_to_tensor(last_frame_url)
|
||
return (InputImpl.VideoFromFile(result_path), last_frame_tensor)
|
||
finally:
|
||
_show_balance()
|
||
|
||
|
||
# ── 节点注册 ──────────────────────────────────────────────────────────────────
|
||
|
||
NODE_CLASS_MAPPINGS = {
|
||
"Seedance": Seedance,
|
||
"SeedanceMultiModal": SeedanceMultiModal,
|
||
}
|
||
|
||
NODE_DISPLAY_NAME_MAPPINGS = {
|
||
"Seedance": "Seedance 视频生成",
|
||
"SeedanceMultiModal": "Seedance 多模态参考生视频",
|
||
}
|