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## ChangeLog
**9.0.0**
- perf: cli now has minimal overhead such that `aimg --help` runs in ~650ms instead of ~3400ms
- feature: `edit` and `imagine` commands now accept multiple images (which they will process separately). This allows
batch editing of images as requested in [#229 ](https://github.com/brycedrennan/imaginAIry/issues/229 )
@ -530,7 +532,7 @@ would be uncorrelated to the rest of the surrounding image. It created terrible
## Todo
- Performance Optimizations
- Inference Performance Optimizations
- ✅ fp16
- ✅ [Doggettx Sliced attention ](https://github.com/CompVis/stable-diffusion/compare/main...Doggettx:stable-diffusion:autocast-improvements# )
- ✅ xformers support https://www.photoroom.com/tech/stable-diffusion-100-percent-faster-with-memory-efficient-attention/
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- https://github.com/CompVis/stable-diffusion/pull/177
- https://github.com/huggingface/diffusers/pull/532/files
- https://github.com/HazyResearch/flash-attention
- https://github.com/chavinlo/sda-node
- Development Environment
- ✅ add tests
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- ✅ unified pipeline (txt2img & img2img combined)
- ✅ setup parallel testing
- add docs
- remove yaml config
- delete more unused code
- 🚫 remove yaml config
- 🚫 delete more unused code
- faster latent logging https://discuss.huggingface.co/t/decoding-latents-to-rgb-without-upscaling/23204/9
- Interface improvements
- ✅ init-image at command line
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- Image Generation Features
- ✅ add k-diffusion sampling methods
- ✅ tiling
- generation videos/gifs
- ✅ generation videos/gifs
- Compositional Visual Generation
- https://github.com/energy-based-model/Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch
- https://colab.research.google.com/github/energy-based-model/Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch/blob/main/notebooks/demo.ipynb#scrollTo=wt_j3uXZGFAS
- ✅ negative prompting
- some syntax to allow it in a text string
- 🚫 images as actual prompts instead of just init images.
- [paint with words ](https://www.reddit.com/r/StableDiffusion/comments/10lzgze/i_figured_out_a_way_to_apply_different_prompts_to/ )
- https://github.com/cloneofsimo/paint-with-words-sd
- images as actual prompts instead of just init images.
- not directly possible due to model architecture.
- can it just be integrated into sampler?
- requires model fine-tuning since SD1.4 expects 77x768 text encoding input
- https://twitter.com/Buntworthy/status/1566744186153484288
- https://github.com/justinpinkney/stable-diffusion
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- [Textual Inversion ](https://arxiv.org/abs/2208.01618 )
- [Fast Textual Inversion ](https://github.com/peterwilli/sd-leap-booster )
- [Low-rank Adaptation for Fast Text-to-Image Diffusion Fine-tuning (LORA) ](https://github.com/cloneofsimo/lora )
- https://huggingface.co/spaces/lora-library/Low-rank-Adaptation
- Performance Improvements
- [ColoassalAI ](https://github.com/hpcaitech/ColossalAI/tree/main/examples/images/diffusion ) - almost got it working but it's not easy enough to install to merit inclusion in imaginairy. We should check back in on this.
- Xformers
Bryce
2 years ago