This workflow is prepared for Anima Aesthetic 1.1 text-to-image character generation with extra attention on the common weak points: faces and hands. The source name includes CN, but the inspected JSON shows the LLLite/Control-style branch is bypassed in the current file, so this Civitai preview presents the active value more accurately as a text-to-image workflow with face and hand detailer support. It is a good setup when you want direct anime character generation first, then localized repair passes to improve close-up features and hand shapes.

The active graph uses `anima-base-202605-v1.0.safetensors`, Qwen Image CLIP, and Qwen Image HDR VAE. The generation route includes 30-step sampler passes, a 3:4 resolution selector, and 1.5x latent upscale stages. The detailer section includes face and hand detection resources such as `bbox/face_yolov8n.pt`, `bbox/hand_yolov8s.pt`, `segm/PitHandDetailer-v2-Test-v9c.pt`, and FaceDetailer nodes. These are the important parts for Civitai users: the workflow is not only generating an image, it also adds targeted local refinement for character features after the main render.

Main features:

- Text-to-image Anima Aesthetic 1.1 workflow
- Active face detailer route
- Active hand detector and hand refinement route
- Qwen Image CLIP text encoder
- Qwen Image HDR VAE decode path
- 3:4 composition support through resolution selection
- 30-step generation and refinement routes observed
- 1.5x latent upscale stage in the graph
- Useful for anime character portraits and full-body tests
- Local repair stages help reduce face and hand artifacts
- CN/LLLite branch is present but bypassed in this file
- Conservative title avoids advertising inactive control nodes

Suggested workflow:

Begin with a prompt that clearly defines the character, pose, hands, and camera distance. Check the base generation before relying on the detailer passes. If the detailers overcorrect the face or fingers, lower their denoise or detection impact. If hands remain unstable, simplify the hand pose in the prompt, then run the detailer route again with a cleaner seed.

⚙️ RunningHub Workflow

Try the workflow online right now — no installation required.
👉 Workflow: https://www.runninghub.ai/post/2078374939884212225?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/2078374939884212225?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。