ComfyUI-SD-CN-Animation

ComfyUI-SD-CN-Animation — Model Weights

Pre-trained model weights for ComfyUI-SD-CN-Animation, a ComfyUI custom node pack for temporally coherent video generation and stylization using optical flow.

Models

Auto-Download

If you install the ComfyUI-SD-CN-Animation node pack, these weights are downloaded automatically the first time ComfyUI starts with the pack installed. No manual setup required.

Manual Installation

If you prefer to download manually, place the files in your ComfyUI models directory:

ComfyUI/models/FloweR/FloweR_0.1.2.pth
ComfyUI/models/RAFT/raft-things.pth

Or via CLI (run from the folder that contains ComfyUI/):

hf download pxlpshr/ComfyUI-SD-CN-Animation models/FloweR/FloweR_0.1.2.pth models/RAFT/raft-things.pth --local-dir ComfyUI

The files live under models/ in this repo, so --local-dir ComfyUI places them at the paths above.

What This Enables

Txt2Vid (Text to Video)

Generate video sequences from a text prompt. FloweR drives the motion by predicting optical flow and the next frame, while Stable Diffusion adds detail and style through a two-pass sampling pipeline (inpaint + refine). Histogram matching prevents color drift.

Vid2Vid (Video Stylization)

Stylize existing videos with any SD checkpoint. RAFT computes real optical flow between input frames, warps the previous stylized frame forward, and uses occlusion detection to determine what needs regenerating. Maintains temporal coherence across the full sequence.

Both modes support ControlNet and IPAdapter for additional control over style and structure.

Model Origins

• FloweR — Optical Flow Reconstruction model by volotat, from the SD-CN-Animation project.
• RAFT — Recurrent All-Pairs Field Transforms for Optical Flow by Zachary Teed and Jia Deng (Princeton Vision Lab). BSD 3-Clause License. Paper | Code

License

• FloweR model weights: MIT License (from SD-CN-Animation)
• RAFT model weights: BSD 3-Clause License (from Princeton)