---
title: Wan 2.2 Animate Character Replace
emoji: 🎬
colorFrom: purple
colorTo: pink
sdk: gradio
sdk_version: 5.43.1
app_file: app.py
pinned: false
license: apache-2.0
short_description: Replace a video's character with Wan 2.2 Animate
---

# Wan 2.2 Animate — Character Replace

Upload a reference image (the character to insert) and a source video. The pipeline
detects pose, face and body mask in the video with ViTPose/YOLO/SAM2, then re-renders
it with the reference character using **Wan 2.2 Animate** on a free
[ZeroGPU](https://huggingface.co/docs/hub/en/spaces-zerogpu) GPU.

This Space is a vendored ComfyUI checkout (core + 4 custom node packs) driven headlessly
by `app.py`, which wraps a workflow exported with
[ComfyUI-to-Python-Extension](https://github.com/pydn/ComfyUI-to-Python-Extension) in a
Gradio UI, following
[Run ComfyUI workflows on Spaces](https://huggingface.co/blog/run-comfyui-workflows-on-spaces).

## How it's put together

- `app.py` — Gradio UI + the exported workflow, adapted to:
  - download every model from the Hub at first launch (`download_models()`) instead of
    committing weights to the repo,
  - load the fixed models (UNET + LoRAs, CLIP, CLIP Vision, VAE, SAM2, detector) once at
    startup and keep them resident, and
  - run only the per-request part of the graph inside a `@spaces.GPU(duration=300)`
    function.
- `custom_nodes/` — the 4 node packs this workflow depends on:
  - [ComfyUI-KJNodes](https://github.com/kijai/ComfyUI-KJNodes)
  - [ComfyUI-VideoHelperSuite](https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite)
  - [ComfyUI-WanAnimatePreprocess](https://github.com/kijai/ComfyUI-WanAnimatePreprocess)
  - [ComfyUI-segment-anything-2](https://github.com/kijai/ComfyUI-segment-anything-2)
- everything else (`comfy/`, `nodes.py`, `execution.py`, ...) is an unmodified checkout of
  [ComfyUI](https://github.com/comfyanonymous/ComfyUI).

## Models (downloaded automatically on first launch)

| File | Source |
|---|---|
| `umt5_xxl_fp8_e4m3fn_scaled.safetensors` | `Comfy-Org/Wan_2.1_ComfyUI_repackaged` |
| `clip_vision_h.safetensors` | `Comfy-Org/Wan_2.1_ComfyUI_repackaged` |
| `wan_2.1_vae.safetensors` | `Comfy-Org/Wan_2.2_ComfyUI_Repackaged` |
| `Wan2_2-Animate-14B_fp8_e4m3fn_scaled_KJ.safetensors` | `Kijai/WanVideo_comfy_fp8_scaled` |
| `lightx2v_I2V_14B_480p_cfg_step_distill_rank64_bf16.safetensors` | `Kijai/WanVideo_comfy` |
| `WanAnimate_relight_lora_fp16.safetensors` | `Kijai/WanVideo_comfy` |
| `sam2.1_hiera_base_plus.safetensors` | `Kijai/sam2-safetensors` |
| `yolov10m.onnx` | `Wan-AI/Wan2.2-Animate-14B` |
| `vitpose-l-wholebody.onnx` | `JunkyByte/easy_ViTPose` |

## Known limitations

- **ZeroGPU duration.** A full Wan 2.2 Animate render (14B UNET + SAM2 + ViTPose + YOLO,
  chained) can run long for a video model, but free-tier ZeroGPU rejects any
  `@spaces.GPU(duration=...)` above roughly 120s regardless of what the docs imply is
  possible (a 300s request was rejected outright as "illegal duration", partly because
  the `large` GPU size multiplies the requested duration for quota accounting). `app.py`
  is set to `duration=120`. A free account's *daily* ZeroGPU quota is also only 5 minutes
  total, so even a couple of runs near that ceiling can exhaust the whole day. Keep
  `Frame Load Cap` low while testing, and consider a PRO account (higher duration ceiling
  and 40 min/day quota) or a GPU quota grant for real use.
- **VRAM.** ZeroGPU's default `large` size gives 48GB; if you see OOM errors, request
  `size="xlarge"` (96GB, 2x quota cost) on the `@spaces.GPU` decorator in `app.py`.
- First launch is slow: it downloads ~20-30GB of models before the UI becomes usable.