CIVITAI / Workflows

Anima Base Text-to-Image + ControlNet Face & Hand Repair Workflow

This workflow is designed for Anima Base text-to-image generation with ControlNet-style structure guidance, face refinement, and hand repair. Its main purpose is to let creators start from a pure text prompt, generate an anime-style image through Anima Base, use structure control to improve composition stability, and then automatically refine the most failure-prone areas: the face, eyes, hands, and fingers. Unlike a basic text-to-image workflow, this setup is not only a single-pass image generator. It combines Anima Base generation, Qwen image text encoding, empty latent creation, prompt-guided sampling, NAG guidance, ControlNet / Anima LLLite-style structure control, latent upscaling, second-pass refinement, face detection, SAM-assisted facial repair, hand detection, hand segmentation, FaceDetailer repair, preview nodes, and final image output. This makes it more suitable for creators who want a complete anime image production pipeline rather than a simple prompt-to-picture graph. The workflow uses anima_baseV10.safetensors as the main Anima Base model route, qwen_3_06b_base.safetensors as the text encoder, and qwen_image_vae.safetensors as the VAE. It also includes CLIPSetLastLayer, EmptyLatentImage, CLIPTextEncode, NAGuidance, AnimaLLLiteApply, AIO_Preprocessor, ClownsharKSampler_Beta, LatentUpscaleBy, VAEDecode, FaceDetailer, SAMLoader, UltralyticsDetectorProvider, and multiple preview nodes. This structure shows that the workflow is built for text-to-image generation plus controlled refinement. The first generation stage starts from an empty latent image, meaning the image is created from text rather than from an existing input image. The positive prompt describes the target anime key visual, such as an adult anime beauty, celestial fantasy scene, long platinum hair, luminous skin, floating palace balcony, colossal sky dragon, clouds, wind, sunlight, and cinematic scale contrast. The negative prompt suppresses low quality, blurry output, JPEG artifacts, low resolution, and other weak-image problems. A key part of the workflow is the ControlNet-style guidance route. The workflow includes a reference image path, DepthAnything preprocessing, and Anima LLLite application. This allows the creator to use structure guidance while still generating from text. In practical terms, this helps the output keep stronger pose, depth, silhouette, layout, and spatial