Comments (1)
Hi, this implementation was done before the authors had released the code, so in a sense, the official repo's code is more "correct" with respect to the paper, while here I had to take some guesses and add a few modifications.
Currently there are three main differences:
- As there is zero code overlap between the two repos, the license and code ownership is different, (this one is licensed under MIT, official one is Apache)
- The official repo has implemented local editing (using the cross attention masks), while this one does not. [Figure 12, page 12 in the paper]
- This repo has implemented image inversion (finding the latent given an image), while the official repo does not (at least not currently). [Figure 10, page 11 in the paper]
While the actual implementation of the cross-attention control/injection might be slightly different, the results are mostly the same, as I tried to be as faithful to the paper but had to modify the algorithms slightly for stable diffusion. I guess the original authors had to do the same thing but in a different way.
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Related Issues (20)
- negative weighting HOT 1
- how to prevent promp 1 from being distorted HOT 1
- Question about the code in CrossAttention_Release.ipynb HOT 1
- Did you get a same result? HOT 1
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- Implementing Dreambooth weights HOT 2
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- Question about original google implementation with stable diffusion HOT 3
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