JonyandClaude Sonnet 4.5
0ddc571f20
- 将 SeedanceT2V / SeedanceI2V / SeedanceFlipFlop 合并为单一 Seedance 节点 - 通过图片输入自动判断模式：无图=文生视频，首帧=图生视频，首尾帧=首尾帧模式 - 修复轮询状态字段取值路径错误导致的无限循环问题 - 修复视频 URL / 末帧 URL 取值路径（result.data.content.video_url） - 新增末帧图片 IMAGE 输出端，支持 return_last_frame 功能 - 删除水印、服务等级前端参数，移除 1.0/1.5 旧模型，去掉 1080p 分辨率 - 关闭 DEBUG 原始响应日志，仅保留用户可见进度日志 Co-Authored-By: Claude Sonnet 4.5 <[email protected]>
298 lines
11 KiB
Python
298 lines
11 KiB
Python
"""
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Seedance 视频生成节点
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节点列表:
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- 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）
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"""
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import io
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import os
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import re
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import aiohttp
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import torch
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from ..clients.seedance_client import SeedanceClient
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from ..clients.gemini_client import GeminiAPIClient
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from ..utils.image_utils import tensor_to_pil, encode_image_to_base64, pil_to_tensor
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from comfy_api.latest import InputImpl
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try:
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import folder_paths
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FOLDER_PATHS_AVAILABLE = True
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except ImportError:
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FOLDER_PATHS_AVAILABLE = False
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# ── 模型列表 ──────────────────────────────────────────────────────────────────
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_MODELS = [
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"doubao-seedance-2-0-260128",
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"doubao-seedance-2-0-fast-260128",
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]
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_RESOLUTIONS = ["720p", "480p"]
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# ── 模型能力判断 ──────────────────────────────────────────────────────────────
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def _supports_camera_fixed(model: str) -> bool:
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"""2.0 系列不支持固定镜头"""
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return False # 当前仅 2.0 模型，均不支持
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# ── 工具函数 ──────────────────────────────────────────────────────────────────
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def _get_video_output_dir() -> str:
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if FOLDER_PATHS_AVAILABLE:
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base = folder_paths.get_output_directory()
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else:
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plugin_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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base = os.path.join(os.path.dirname(os.path.dirname(plugin_dir)), "output")
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video_dir = os.path.join(base, "video")
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os.makedirs(video_dir, exist_ok=True)
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return video_dir
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def _get_next_counter(directory: str, prefix: str) -> int:
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if not os.path.exists(directory):
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return 1
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pattern = re.compile(rf"^{re.escape(prefix)}_(\d+)")
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max_counter = 0
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for f in os.listdir(directory):
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m = pattern.match(f)
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if m:
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max_counter = max(max_counter, int(m.group(1)))
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return max_counter + 1
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def _tensor_to_base64_url(tensor) -> str:
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"""ComfyUI IMAGE tensor → data:image/png;base64,xxx"""
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pil_images = tensor_to_pil(tensor)
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b64 = encode_image_to_base64(pil_images[0], format="PNG")
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return f"data:image/png;base64,{b64}"
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async def _url_to_tensor(url: str) -> torch.Tensor:
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"""从 URL 下载图片并转为 ComfyUI IMAGE tensor，失败时返回 None"""
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try:
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from PIL import Image
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async with aiohttp.ClientSession() as session:
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async with session.get(url, allow_redirects=True) as resp:
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if resp.status != 200:
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return None
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data = await resp.read()
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img = Image.open(io.BytesIO(data)).convert("RGB")
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return pil_to_tensor([img])
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except Exception as e:
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print(f"[Seedance] 末帧图片下载失败: {e}")
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return None
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def _show_balance():
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"""完成后打印余额（静默失败）"""
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try:
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client = GeminiAPIClient()
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data = client.query_balance_sync()
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print(f"Seedance: {client.format_balance_info(data)}")
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except Exception:
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pass
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def _make_pbar():
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try:
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from comfy.utils import ProgressBar
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return ProgressBar(100)
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except Exception:
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return None
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def _make_callbacks(tag: str, pbar):
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def on_stage(stage: str):
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if stage == "submitting":
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print(f"[{tag}] 提交中...")
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if pbar: pbar.update_absolute(0, 100)
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elif stage.startswith("submitted:"):
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print(f"[{tag}] 已提交 → {stage.split(':', 1)[1]}")
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if pbar: pbar.update_absolute(5, 100)
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elif stage == "downloading":
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print(f"[{tag}] 下载视频中...")
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if pbar: pbar.update_absolute(99, 100)
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elif stage == "done":
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print(f"[{tag}] 完成")
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if pbar: pbar.update_absolute(100, 100)
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def on_progress(pct: int):
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if pbar: pbar.update_absolute(5 + int(pct * 0.94), 100)
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return on_stage, on_progress
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# ── 统一节点 ─────────────────────────────────────────────────────────────────
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#
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# 模式由图片输入自动判断：
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# 首帧 = None → T2V 文生视频 （联网搜索生效）
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# 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）
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# 首帧 = 图片，尾帧 = 图片 → FlipFlop 首尾帧（联网搜索/固定镜头均忽略）
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class Seedance:
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"""Seedance 视频生成（文生视频 / 图生视频 / 首尾帧，自动判断模式）"""
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"提示词": ("STRING", {"multiline": True, "default": ""}),
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"模型": (_MODELS, {"default": "doubao-seedance-2-0-260128"}),
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"分辨率": (_RESOLUTIONS, {"default": "720p"}),
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"宽高比": (["16:9", "adaptive", "9:16", "1:1", "4:3", "3:4", "21:9"],
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{"default": "16:9"}),
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"时长秒(-1=自动)": ("INT", {"default": 5, "min": -1, "max": 30, "step": 1}),
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"生成音频": (["关闭", "打开"], {"default": "关闭"}),
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"联网搜索": (["关闭", "打开"], {"default": "关闭"}),
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"返回末帧图片": (["关闭", "打开"], {"default": "关闭"}),
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"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffff}),
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},
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"optional": {
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"首帧图片": ("IMAGE",),
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"尾帧图片": ("IMAGE",),
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},
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}
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RETURN_TYPES = ("VIDEO", "IMAGE")
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RETURN_NAMES = ("视频", "末帧图片")
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FUNCTION = "generate"
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CATEGORY = "comfyui_o1key/Seedance"
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async def generate(self, **kwargs):
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prompt = kwargs["提示词"].strip()
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model = kwargs["模型"]
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resolution = kwargs["分辨率"]
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ratio = kwargs["宽高比"]
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duration = kwargs["时长秒(-1=自动)"]
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gen_audio = kwargs["生成音频"] == "打开"
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web_search = kwargs["联网搜索"] == "打开"
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return_last = kwargs["返回末帧图片"] == "打开"
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seed = kwargs.get("seed", 0)
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first_image = kwargs.get("首帧图片", None)
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last_image = kwargs.get("尾帧图片", None)
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# 模式判断
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if first_image is None and last_image is not None:
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raise ValueError("请同时接入首帧图片，或仅接入首帧图片。")
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if first_image is None:
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mode = "t2v"
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tag = "Seedance文生视频"
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file_prefix = "seedance_t2v"
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elif last_image is None:
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mode = "i2v"
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tag = "Seedance图生视频"
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file_prefix = "seedance_i2v"
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else:
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mode = "flipflop"
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tag = "Seedance首尾帧"
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file_prefix = "seedance_flip"
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if not prompt:
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raise ValueError("提示词不能为空。")
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if duration == -1 and mode == "t2v":
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pass # 2.0 均支持自动时长
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elif duration == -1 and mode != "t2v":
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pass # 2.0 均支持自动时长
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metadata: dict = {
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"resolution": resolution,
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"watermark": False,
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}
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if ratio != "adaptive":
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metadata["ratio"] = ratio
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if duration != -1:
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metadata["duration"] = duration
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if gen_audio:
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metadata["generate_audio"] = True
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if return_last:
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metadata["return_last_frame"] = True
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if seed != 0:
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metadata["seed"] = seed
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# 模式专属参数
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if mode == "t2v":
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if web_search:
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metadata["tools"] = [{"type": "web_search"}]
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body = {
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"model": model,
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"prompt": prompt,
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"metadata": metadata,
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}
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elif mode == "i2v":
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first_url = _tensor_to_base64_url(first_image)
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metadata["content"] = [
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{
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"type": "image_url",
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"image_url": {"url": first_url},
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"role": "first_frame",
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},
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{"type": "text", "text": prompt},
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]
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body = {
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"model": model,
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"prompt": prompt,
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"images": [first_url],
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"metadata": metadata,
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}
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else: # flipflop
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first_url = _tensor_to_base64_url(first_image)
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last_url = _tensor_to_base64_url(last_image)
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metadata["content"] = [
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{
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"type": "image_url",
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"image_url": {"url": first_url},
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"role": "first_frame",
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},
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{
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"type": "image_url",
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"image_url": {"url": last_url},
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"role": "last_frame",
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},
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{"type": "text", "text": prompt},
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]
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body = {
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"model": model,
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"prompt": prompt,
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"images": [first_url],
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"metadata": metadata,
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}
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video_dir = _get_video_output_dir()
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counter = _get_next_counter(video_dir, file_prefix)
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save_path = os.path.join(video_dir, f"{file_prefix}_{counter:05d}.mp4")
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client = SeedanceClient()
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pbar = _make_pbar()
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on_stage, on_prog = _make_callbacks(tag, pbar)
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try:
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result_path, last_frame_url = await client.generate_async(
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body=body, save_path=save_path,
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on_stage=on_stage, on_progress=on_prog,
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)
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last_frame_tensor = None
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if return_last and last_frame_url:
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last_frame_tensor = await _url_to_tensor(last_frame_url)
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return (InputImpl.VideoFromFile(result_path), last_frame_tensor)
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finally:
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_show_balance()
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# ── 节点注册 ──────────────────────────────────────────────────────────────────
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NODE_CLASS_MAPPINGS = {
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"Seedance": Seedance,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"Seedance": "Seedance 视频生成",
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}
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