2023-03-11 02:55:21 +00:00
## Todo
2023-11-29 06:35:49 +00:00
### v14 todo
- configurable composition cutoff
- rename model parameter weights
- rename model_config parameter to architecture and make it case insensitive
- add --size parameter that accepts strings (e.g. 256x256, 4k, uhd, 8k, etc)
- detect if cuda torch missing and give better error message
- add method to install correct torch version
- add composition cutoff parameter
- allow selection of output video format
- chain multiple operations together imggen => videogen
- make sure terminal output on windows doesn't suck
2023-12-03 15:02:57 +00:00
- add karras schedule to refiners
2023-11-29 06:35:49 +00:00
### Old Todo
2023-03-11 02:55:21 +00:00
- 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/
- https://github.com/neonsecret/stable-diffusion
- 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
- https://github.com/AminRezaei0x443/memory-efficient-attention/issues/7
- Development Environment
- ✅ add tests
- ✅ set up ci (test/lint/format)
- ✅ unified pipeline (txt2img & img2img combined)
- ✅ setup parallel testing
- add docs
- 🚫 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
- ✅ prompt expansion
- ✅ interactive cli
- Image Generation Features
- ✅ add k-diffusion sampling methods
- ✅ tiling
- ✅ generation videos/gifs
- ✅ controlnet
- scribbles input
- segmentation input
- mlsd input
- [Attend and Excite ](https://attendandexcite.github.io/Attend-and-Excite/ )
- 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
- [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
- https://multidiffusion.github.io/
- 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
- https://github.com/LambdaLabsML/lambda-diffusers
- https://www.reddit.com/r/MachineLearning/comments/x6k5bm/n_stable_diffusion_image_variations_released/
- Image Editing
- ✅outpainting
- https://github.com/parlance-zz/g-diffuser-bot/search?q=noise& type=issues
- lama cleaner
- ✅ inpainting
- https://github.com/Jack000/glid-3-xl-stable
- https://github.com/andreas128/RePaint
- ✅ img2img but keeps img stable
- https://www.reddit.com/r/StableDiffusion/comments/xboy90/a_better_way_of_doing_img2img_by_finding_the/
- https://gist.github.com/trygvebw/c71334dd127d537a15e9d59790f7f5e1
- https://github.com/pesser/stable-diffusion/commit/bbb52981460707963e2a62160890d7ecbce00e79
- https://github.com/SHI-Labs/FcF-Inpainting https://praeclarumjj3.github.io/fcf-inpainting/
- ✅ text based image masking
- ✅ ClipSeg - https://github.com/timojl/clipseg
- https://github.com/facebookresearch/detectron2
- https://x-decoder-vl.github.io/
- Maskless editing
- ✅ instruct-pix2pix
-
- Attention Control Methods
- https://github.com/bloc97/CrossAttentionControl
- https://github.com/ChenWu98/cycle-diffusion
- Image Enhancement
- Photo Restoration - https://github.com/microsoft/Bringing-Old-Photos-Back-to-Life
- Upscaling
- ✅ realesrgan
- ldm
- https://github.com/lowfuel/progrock-stable
- [txt2imghd ](https://github.com/jquesnelle/txt2imghd/blob/master/txt2imghd.py )
- latent scaling + reprocessing
- stability upscaler
- rivers have wings upscaler
- stable super-res?
- todo: try with 1-0-0-0 mask at full image resolution (rencoding entire image+predicted image at every step)
- todo: use a gaussian pyramid and only include the "high-detail" level of the pyramid into the next step
- https://www.reddit.com/r/StableDiffusion/comments/xkjjf9/upscale_to_huge_sizes_and_add_detail_with_sd/
- ✅ face enhancers
- ✅ gfpgan - https://github.com/TencentARC/GFPGAN
- ✅ codeformer - https://github.com/sczhou/CodeFormer
- ✅ image describe feature -
- ✅ https://github.com/salesforce/BLIP
- 🚫 CLIP brute-force prompt reconstruction
- The accuracy of this approach is too low for me to include it in imaginAIry
- https://github.com/rmokady/CLIP_prefix_caption
- https://github.com/pharmapsychotic/clip-interrogator (blip + clip)
- https://github.com/KaiyangZhou/CoOp
- 🚫 CPU support. While the code does actually work on some CPUs, the generation takes so long that I don't think it's
worth the effort to support this feature
- ✅ img2img for plms
- ✅ img2img for kdiff functions
- Other
- Enhancement pipelines
- text-to-3d https://dreamfusionpaper.github.io/
- https://shihmengli.github.io/3D-Photo-Inpainting/
- https://github.com/thygate/stable-diffusion-webui-depthmap-script/discussions/50
- Depth estimation
- what is SOTA for monocular depth estimation?
- https://github.com/compphoto/BoostingMonocularDepth
- make a video https://github.com/lucidrains/make-a-video-pytorch
- animations
- https://github.com/francislabountyjr/stable-diffusion/blob/main/inferencing_notebook.ipynb
- https://www.youtube.com/watch?v=E7aAFEhdngI
- https://github.com/pytti-tools/frame-interpolation
- guided generation
- https://colab.research.google.com/drive/1dlgggNa5Mz8sEAGU0wFCHhGLFooW_pf1#scrollTo=UDeXQKbPTdZI
- https://colab.research.google.com/github/aicrumb/doohickey/blob/main/Doohickey_Diffusion.ipynb#scrollTo=PytCwKXCmPid
- https://github.com/mlfoundations/open_clip
- https://github.com/openai/guided-diffusion
- image variations https://github.com/lstein/stable-diffusion/blob/main/VARIATIONS.md
- textual inversion
- https://www.reddit.com/r/StableDiffusion/comments/xbwb5y/how_to_run_textual_inversion_locally_train_your/
- https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_textual_inversion_training.ipynb#scrollTo=50JuJUM8EG1h
- https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_diffusion_textual_inversion_library_navigator.ipynb
- https://github.com/Jack000/glid-3-xl-stable
- fix saturation at high CFG https://www.reddit.com/r/StableDiffusion/comments/xalo78/fixing_excessive_contrastsaturation_resulting/
- https://www.reddit.com/r/StableDiffusion/comments/xbrrgt/a_rundown_of_twenty_new_methodsoptions_added_to/
- ✅ deploy to pypi
- find similar images https://knn5.laion.ai/?back=https%3A%2F%2Fknn5.laion.ai%2F& index=laion5B& useMclip=false
- https://github.com/vicgalle/stable-diffusion-aesthetic-gradients
- Training
- Finetuning "dreambooth" style
- [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
- Deepspeed
-
