This is a focused image-to-image workflow for Anima Aesthetic 1.1. It is meant for situations where you already have a reference image, rough concept, generated draft, or composition sketch and want to redraw it into a cleaner anime-style result while preserving the broad structure. Instead of starting from an empty latent, the workflow brings an input image into the latent space and lets the prompt guide the redraw. That makes it useful for refining pose, costume, lighting, character atmosphere, and overall illustration quality without losing the original layout too quickly.

The inspected graph includes a LoadImage and VAEEncode route, Qwen Image CLIP, Qwen Image HDR VAE, and an Anima Aesthetic V1.1 model selection path. The active sampling route uses a 31-step er_sde/simple style pass with denoise around 0.70, which is strong enough to restyle and improve the input while still giving the source image influence. The Anima Turbo LoRA node appears in the file but is bypassed, so this preview does not describe it as an active speed LoRA workflow. The strength of this setup is control through the input image rather than through a large stack of auxiliary control nodes.

Main features:

- Image-to-image redraw workflow for Anima Aesthetic 1.1
- Uses source image guidance through LoadImage and VAEEncode
- Qwen Image CLIP text encoding
- Qwen Image HDR VAE route
- 31-step sampling path observed
- Denoise around 0.70 for visible but controlled transformation
- Useful for rough drafts, composition reuse, and style refinement
- Keeps the workflow simpler than a full ControlNet stack
- Good for anime character polishing and illustration cleanup
- Turbo LoRA is present but bypassed, so it is not advertised as active
- Suitable for online testing before local customization
- Designed for users who want controlled redraws rather than pure txt2img

Suggested workflow:

Load a source image with a strong silhouette and clear subject. Write the prompt as a direction for what the image should become, not as a full replacement for the source. If you want to preserve the original structure, reduce denoise; if you want a more dramatic redraw, increase it slowly and rerun with the same image until the character and composition reach the right balance.

⚙️ RunningHub Workflow

Try the workflow online right now — no installation required.
👉 Workflow: https://www.runninghub.ai/post/2078721264412741633?inviteCode=rh-v1111

If the results meet your expectations, you can later deploy it locally for customization.

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📺 Bilibili Updates (Mainland China & Asia-Pacific)

If you’re in the Asia-Pacific region, you can watch the video below to see the workflow demonstration and creative breakdown.
📺 Bilibili Video: https://www.bilibili.com/video/BV1xJKB6vEfp/

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⚙️打开下方链接即可在线体验，无需安装。
👉 工作流： https://www.runninghub.ai/post/2078721264412741633?inviteCode=rh-v1111
如果觉得效果理想，你也可以在本地进行自定义部署。

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📺 Bilibili 更新（中国大陆及南亚太地区）

如果你在中国大陆或南亚太地区，可以通过下方视频查看该工作流的实测效果与构思讲解。
📺 B站视频： https://www.bilibili.com/video/BV1xJKB6vEfp/

我会在 夸克网盘 持续更新模型资源：
👉 https://pan.quark.cn/s/20c6f6f8d87b
这些资源主要面向本地用户，方便进行创作与学习。