Trained from my existing dataset using quality photorealistic images.
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And why are there colored squares instead of faces? Was that in the dataset?
makiaeveliOct 11, 2026
it's just a bad attempt at making it face-agnostic, a technique for older models like SDXL. It's easier to either wholly cut the face, or better, leave the face, but prompt it in such a way that the face is not the focus of the learning. These krea2 and qwen encoders are capable of understanding the input image well enough to ignore the face. generally things like this is someone trying to do good, just putting that effort in the wrong place for the tool. It's lame to see people be upset with that.


