This workflow is intended to be used with the <a target="_blank" rel="ugc" href="https://civarchive.com/models/2168935/z-image?modelVersionId=2442439">Z-Image Turbo</a> model to generate an image and then refine the image using the <a target="_blank" rel="ugc" href="https://civarchive.com/models/1513492?modelVersionId=2368123">GonzaLomo V6.0 Photo XL</a> model. V6.0 will provide the image with much better detailed anatomical features.Note that it's not required to use the GonzaLomo SDXL model as any photorealistic SDXL model should do a very good job at refining the Z-Image image.The different detailers require separate models that should go in your ComfyUI /models/ultralytics/bbox folder. I've uploaded them to this model page <a rel="ugc" href="https://civarchive.com/models/2172100?modelVersionId=2543959">here </a>but you can also find these files <a target="_blank" rel="ugc" href="https://huggingface.co/Tenofas/ComfyUI/tree/d79945fb5c16e8aef8a1eb3ba1788d72152c6d96/ultralytics/bbox">here</a> and <a target="_blank" rel="ugc" href="https://huggingface.co/ashllay/YOLO_Models/tree/e07b01219ff1807e1885015f439d788b038f49bd/bbox">here</a>.

GonzaLomo Z-Image Refiner Workflow

v1.0 of this workflow used SDXL to refine the whole image which turned out to be less than ideal. With v1.1, I'm taking a different approach that I'm not entirely sure is necessary, although it does seem to give me the best result.Essentially, I'm taking a similar high/low noise approach to the way WAN 2.2 video generation works. 3 steps on "high", return with noise, and then 7 steps on "low". In my A/B testing this seemed to give a better result than just running 10 steps in one sampler. I'm also generating at a very high resolution 1536x1920 and not doing any upscaling.Theoretically, the "high" noise sampler could have different sampler/scheduler/CFG settings and possibly increase image composition and quality further.

Files with SHA256: 5668da80410d97ce64118950b02f3887ae474f89454b3d5c50ad36a7ae4ede0e