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FLUX is fast and it's open source

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Re: FLUX is fast and it's open source

#23
Text to image models feels inefficient to me. I wonder if it would be possible and better to do it in separate steps, like text to scene graph, scene graph to semantically segmented image, segmented image to final image. That way each step could be trained separately and be modular, and the image would be easier to edit instead of completely replace it with the output of a new prompt. That way it should be much easier to generate stuff like "object x next to object y, with the text foo on it", and the art style or level of realism would depend on the final rendering model which would be separate from the prompt adherence.

Kind of like those video2video (or img2img on each frame I guess) models where they enhance the image outputs from video games:

https://www.theverge.com/2021/5/12/22432945/intel-gta-v-real... https://www.reddit.com/r/aivideo/comments/1fx6zdr/gta_iv_wit...

Re: FLUX is fast and it's open source

#25

Text to image models feels inefficient to me. I wonder if it would be possible and better to do it in separate steps, like text to scene graph, scene graph to semantically segmented image, segmented image to final image. That way each step could be trained separately and be modular, and the image would be easier to edit instead of completely replace it with the output of a new prompt. That way it should be much easie…

That's essentially what diffusion does, except it doesn't have clear boundaries between "scene graph" and "full image". It starts out noisy and adds more detail gradually

Re: FLUX is fast and it's open source

#28

Text to image models feels inefficient to me. I wonder if it would be possible and better to do it in separate steps, like text to scene graph, scene graph to semantically segmented image, segmented image to final image. That way each step could be trained separately and be modular, and the image would be easier to edit instead of completely replace it with the output of a new prompt. That way it should be much easie…

The issue with this is there's a false assumption that an image is a collection of objects. It's not (necessarily).

I want a picture of frozen cyan peach fuzz.

Re: FLUX is fast and it's open source

#29

Text to image models feels inefficient to me. I wonder if it would be possible and better to do it in separate steps, like text to scene graph, scene graph to semantically segmented image, segmented image to final image. That way each step could be trained separately and be modular, and the image would be easier to edit instead of completely replace it with the output of a new prompt. That way it should be much easie…

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