FLUX SUPER Workflow
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Model description
Flux SUPER Workflow
This workflow is made for Flux and can do:
Text2Img (with or without autoprompt based on the input image)
Img2img (Flux Redux, Controlnet Union, Regular Img2img, everything accesible and easy tweakable with the main knobs)
Cnet Upscale (with noise injection / colormatch)
ExtraFace Detailer (with noise injection / mix / colormatch)
PostProcess (Eveything you need)
Nice Console Infos
Minimal clutter, Maximal features
Bypass groups
Caching Optimisations, Teacache for faster inference
You can now use FLUX KREA as base model
To enhance the image only, activate img2img with "img2img denoise" to 0. This will bypass the first inference to only use the upscaler and face detailer.
This method is way faster than something like SUPIR and give better details.
Use the "Control_end" as a strength parameter, higher value for lower strenght.
Use the noise "injection strenght" to add more details
yolov8m-face.pt https://github.com/akanametov/yolo-face?tab=readme-ov-file#models
face_yolov8n-seg2_60.pt https://huggingface.co/jags/yolov8_model_segmentation-set/blob/main/face_yolov8n-seg2_60.pt
sigclip_vision_384 https://huggingface.co/Comfy-Org/sigclip_vision_384/blob/main/sigclip_vision_patch14_384.safetensors
FLUX.1-dev-ControlNet-Union-Pro https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro/tree/main
Flux.1-dev-Controlnet-Upscaler https://huggingface.co/jasperai/Flux.1-dev-Controlnet-Upscaler/tree/main
Yolo8 face segmentation models are in pickle serialization format and autoflagged as "unsafe" because this is not a secure format, just like ".ckpt"
Be sure to download your models from trusted sources by looking at the profiles and previous commits.