Unofficial implementation of "Prompt-to-Prompt Image Editing with Cross Attention Control" with Stable Diffusion
Edit images using prompts with a method that improves control and predictability in image generation.
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CrossAttentionControl has 1.3k stars on GitHub. It has been forked 84 times. CrossAttentionControl is written mainly in Jupyter Notebook. It has been in active development since 2022. CrossAttentionControl is available under the MIT license. Its main topics are cross-attention, deep-learning, diffusion-models, stable-diffusion.
Unofficial implementation of "Prompt-to-Prompt Image Editing with Cross Attention Control" with Stable Diffusion
CrossAttentionControl is an open-source project. It is released under the MIT license.
Yes. CrossAttentionControl is free and open source — you can use, modify and self-host it.
CrossAttentionControl is available under the MIT license.
CrossAttentionControl is written mainly in Jupyter Notebook.
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