Extensions/ComfyUI-PainterLongVideo
ComfyUI Extension

ComfyUI-PainterLongVideo

Powerful node for generating long-form videos with consistent motion, global scene coherence, and slow-motion correction in Wan 2.2-based workflows.

By princepainter·Created 9 months ago·Updated 9 months ago· 130
princepainter/ComfyUI-PainterLongVideo
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Updated9 months ago
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PainterLongVideo Node for ComfyUI

ComfyUI 的 PainterLongVideo 节点

A powerful node for generating long-form videos with consistent motion, global scene coherence, and slow-motion correction in Wan 2.2-based workflows. If you don’t connect to the previous_video access point, it is equivalent to a keyframe node with dynamic enhancement functionality. 一个强大的节点，用于在基于 Wan 2.2 的工作流中生成长视频，具备运动一致性、全局场景连贯性以及慢动作修复功能。如果你不接参考视频，它就等于是一个带动态加强功能的首尾帧节点。

✨ Features / 功能亮点

  • Long Video Continuation: Seamlessly continues from the last frame of a previous video segment.
    长视频接续：无缝接续上一段视频的最后一帧。

  • Slow-Motion Fix: Built-in motion_amplitude control to enhance motion intensity and fix sluggish movement in 4-step LoRAs (e.g., lightx2v).
    慢动作修复：内置 motion_amplitude 参数，增强运动幅度，修复 4 步 LoRA（如 lightx2v）中的迟缓问题。

  • Global Consistency Anchor: Optional initial_reference_image input allows the model to remember the original character/scene layout from the first segment, preventing drift when the camera returns.
    全局一致性锚定：可选的 initial_reference_image 输入，让模型记住第一段的初始人物与场景布局，防止镜头回溯时内容漂移。

  • Compact UI: Clean, official-style node size with short name PainterLongVideo.
    紧凑界面：简洁、官方风格的节点尺寸，名称简短为 PainterLongVideo。

📥 Installation / 安装方法

  1. Place this folder into your ComfyUI custom nodes directory:
    将本文件夹放入 ComfyUI 的自定义节点目录中：

  2. Ensure you have the required dependencies (usually included with standard ComfyUI):
    确保已安装所需依赖（通常随标准 ComfyUI 自带）：

  • torch
  • comfyui (latest)
  1. Restart ComfyUI. The node will appear under video/painter category.
    重启 ComfyUI。该节点将出现在 video/painter 分类下。

⚙️ Inputs / 输入参数

| Input | Type | Description | |------|------|-------------| | positive | CONDITIONING | Positive prompt conditioning. | | negative | CONDITIONING | Negative prompt conditioning. | | vae | VAE | VAE model for latent encoding/decoding. | | width | INT | Output width (multiple of 16). Default: 832. | | height | INT | Output height (multiple of 16). Default: 480. | | length | INT | Number of output frames. Default: 81. | | batch_size | INT | Batch size for generation. Default: 1. | | previous_video | IMAGE | The full output video from the previous segment (used for continuity). | | motion_frames | INT | Number of trailing frames from previous_video used as motion reference. Default: 5. | | motion_amplitude | FLOAT | Motion intensity multiplier (1.0 = normal, 1.15 = recommended). Range: 1.0–2.0. | | initial_reference_image (optional) | IMAGE | The first frame of the very first video segment. Helps maintain global consistency across segments. | | clip_vision_output (optional) | CLIP_VISION_OUTPUT | Optional CLIP vision embedding for image-guided generation. |

| 输入 | 类型 | 说明 | |------|------|------| | positive | CONDITIONING | 正向提示词条件。 | | negative | CONDITIONING | 负向提示词条件。 | | vae | VAE | 用于 latent 编解码的 VAE 模型。 | | width | INT | 输出宽度（需为 16 的倍数）。默认：832。 | | height | INT | 输出高度（需为 16 的倍数）。默认：480。 | | length | INT | 输出帧数。默认：81。 | | batch_size | INT | 生成批次大小。默认：1。 | | previous_video | IMAGE | 上一段视频的完整输出（用于连续性）。 | | motion_frames | INT | 从 previous_video 末尾提取的参考帧数量。默认：5。 | | motion_amplitude | FLOAT | 运动强度倍率（1.0=正常，1.15=推荐）。范围：1.0–2.0。 | | initial_reference_image (可选) | IMAGE | 整个视频序列的第一帧。用于跨段落保持全局一致性。 | | clip_vision_output (可选) | CLIP_VISION_OUTPUT | 可选的 CLIP 视觉嵌入，用于图像引导生成。 |

💡 Usage Tips / 使用建议

  • For best results, always provide the first frame of Segment 1 as initial_reference_image to all subsequent segments.
    为获得最佳效果，请将第一段的第一帧作为 initial_reference_image 输入到所有后续段落中。

  • Set motion_amplitude = 1.15 as default. Increase to 1.2–1.3 if motion still feels too slow.
    默认设为 motion_amplitude = 1.15。若仍觉动作太慢，可增至 1.2–1.3。

  • Keep motion_frames small (3–7) unless complex motion is needed.
    除非需要复杂运镜，否则保持 motion_frames 较小（3–7）。

  • This node works best with Wan 2.2 + 4-step LoRA pipelines.
    本节点最适合搭配 Wan 2.2 + 4 步 LoRA 流程使用。

🧠 How It Works / 工作原理

The node:

  1. Encodes the last frame of previous_video as the starting point.
  2. Constructs a latent sequence with the first frame fixed and others initialized to gray.
  3. Applies motion enhancement via latent difference scaling (motion_amplitude).
  4. Injects both last-frame and initial-frame latents into reference_latents for dual-reference guidance.

该节点：

  1. 将 previous_video 的最后一帧编码为起点；
  2. 构建 latent 序列：首帧固定，其余初始化为灰色；
  3. 通过 latent 差值缩放实现运动增强（motion_amplitude）；
  4. 将结尾帧和起始帧同时注入 reference_latents，实现双重参考引导。

📜 License / 许可证

MIT License – Free to use, modify, and distribute.
MIT 许可证 – 免费使用、修改和分发。