chore(docs): update features, link to user guide
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README.md
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README.md
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@ -20,25 +20,37 @@ Please [see the User Guide](https://github.com/ssube/onnx-web/blob/main/docs/use
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## Features
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- AMD and Nvidia hardware acceleration using CUDA, DirectML, or ROCm
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This is an incomplete list of new and interesting features, with links to the user guide:
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- hardware acceleration on both AMD and Nvidia
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- [tested on CUDA, DirectML, and ROCm](#install-pip-packages)
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- [half-precision support for low-memory GPUs](docs/user-guide.md#optimizing-models-for-lower-memory-usage)
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- fallback for CPU-only systems
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- web app to generate and view images
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- [hosted on Github Pages](https://ssube.github.io/onnx-web), from your CDN, or locally
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- keeps your recent images and progress as you change tabs
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- queue up multiple images
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- convert and load your own models
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- directly supports HuggingFace Hub and Civitai
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- supports LoRA with [an extra conversion step](./docs/converting-models.md)
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- [persists your recent images and progress as you change tabs](docs/user-guide.md#image-history)
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- queue up multiple images and retry errors
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- supports many `diffusers` pipelines
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- txt2img
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- img2img
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- inpainting
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- upscale (with ONNX acceleration)
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- long prompt weighting
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- blending mode for combining images
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- [txt2img](docs/user-guide.md#txt2img-tab)
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- [img2img](docs/user-guide.md#img2img-tab)
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- [inpainting](docs/user-guide.md#inpaint-tab), with mask drawing and upload
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- [upscaling](docs/user-guide.md#upscale-tab), with ONNX acceleration
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- [add and use your own models](docs/user-guide.md#adding-your-own-models)
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- [convert models from diffusers and SD checkpoints](docs/converting-models.md)
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- [download models from HuggingFace hub, Civitai, and HTTPS sources](docs/user-guide.md#model-sources)
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- blend in additional networks
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- [permanent and prompt-based blending](docs/user-guide.md#permanently-blending-additional-networks)
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- [supports LoRA weights](docs/user-guide.md#lora-tokens)
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- [supports Textual Inversion concepts and embeddings](docs/user-guide.md#textual-inversion-tokens)
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- infinite prompt length
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- [with long prompt weighting](docs/user-guide.md#long-prompt-weighting)
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- expand and control Textual Inversions per-layer
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- [image blending mode](docs/user-guide.md#blend-tab)
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- combine images from history
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- upscaling and face correction
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- upscaling with Real ESRGAN or Stable Diffusion
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- face correction with CodeFormer or GFPGAN
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- API server can run models on a remote GPU
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- [API server can be run remotely](docs/server-admin.md)
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- REST API can be served over HTTPS or HTTP
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- background processing for all image pipelines
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- polling for image status, plays nice with load balancers
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@ -322,24 +334,77 @@ Diffusion v2 models.
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#### Converting your own models
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You can include your own models in the conversion script without making any code changes.
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You can include your own models in the conversion script without making any code changes and download additional
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networks to blend during conversion or by using prompt tokens. For more details, please [see the user guide
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](./docs/user-guide.md#adding-your-own-models).
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Make a copy of the `api/extras.json` file and edit it to include the models you want to download and convert:
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```json
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{
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"diffusion": [
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["diffusion-knollingcase", "Aybeeceedee/knollingcase"],
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["diffusion-openjourney", "prompthero/openjourney"]
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{
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"name": "diffusion-knollingcase",
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"label": "Knollingcase",
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"source": "Aybeeceedee/knollingcase"
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},
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{
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"name": "diffusion-openjourney",
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"source": "prompthero/openjourney"
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},
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{
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"name": "diffusion-stablydiffused-aesthetic-v2-6",
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"label": "Stably Diffused Aesthetic Mix v2.6",
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"source": "civitai://6266?type=Pruned%20Model&format=SafeTensor",
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"format": "safetensors"
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},
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{
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"name": "diffusion-unstable-ink-dream-v6",
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"label": "Unstable Ink Dream v6",
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"source": "civitai://5796",
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"format": "safetensors"
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},
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{
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"name": "sonic-diffusion-v1-5",
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"source": "runwayml/stable-diffusion-v1-5",
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"inversions": [
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{
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"name": "ugly-sonic",
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"source": "huggingface://sd-concepts-library/ugly-sonic",
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"model": "concept"
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}
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]
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}
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],
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"correction": [],
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"upscaling": []
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"upscaling": [],
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"networks": [
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{
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"name": "cubex",
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"source": "huggingface://sd-concepts-library/cubex",
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"label": "Cubex",
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"model": "concept",
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"type": "inversion"
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},
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{
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"name": "birb",
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"source": "huggingface://sd-concepts-library/birb-style",
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"label": "Birb",
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"model": "concept",
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"type": "inversion"
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},
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{
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"name": "minecraft",
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"source": "huggingface://sd-concepts-library/minecraft-concept-art",
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"label": "Minecraft Concept",
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"model": "concept",
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"type": "inversion"
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},
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],
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"sources": []
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}
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```
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Models based on Stable Diffusion typically need to be in the `diffusion` category, including the Stable Diffusion
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upscaling model. For more details, please [see the user guide](./docs/user-guide.md#adding-your-own-models).
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Set the `ONNX_WEB_EXTRA_MODELS` environment variable to the path to your new `extras.json` file before running the
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launch script:
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@ -538,5 +603,6 @@ Getting this set up and running on AMD would not have been possible without guid
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There are many other good options for using Stable Diffusion with hardware acceleration, including:
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- https://github.com/azuritecoin/OnnxDiffusersUI
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- https://github.com/ForserX/StableDiffusionUI
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- https://github.com/pingzing/stable-diffusion-playground
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- https://github.com/quickwick/stable-diffusion-win-amd-ui
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@ -33,6 +33,7 @@ Please see [the server admin guide](server-admin.md) for details on how to confi
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- [LoRA tokens](#lora-tokens)
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- [Textual Inversion tokens](#textual-inversion-tokens)
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- [CLIP skip tokens](#clip-skip-tokens)
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- [Long prompt weighting](#long-prompt-weighting)
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- [Tabs](#tabs)
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- [Txt2img tab](#txt2img-tab)
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- [Scheduler parameter](#scheduler-parameter)
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@ -67,6 +68,7 @@ Please see [the server admin guide](server-admin.md) for details on how to confi
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- [Downloading models from Civitai](#downloading-models-from-civitai)
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- [Downloading models from HuggingFace](#downloading-models-from-huggingface)
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- [Using a custom VAE](#using-a-custom-vae)
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- [Optimizing models for lower memory usage](#optimizing-models-for-lower-memory-usage)
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- [Permanently blending additional networks](#permanently-blending-additional-networks)
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- [Extras file format](#extras-file-format)
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- [Known errors](#known-errors)
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@ -279,6 +281,10 @@ You can skip the last layers of the CLIP text encoder using the `clip` token:
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This makes your prompt less specific and some models have been trained to work better with some amount of skipping.
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### Long prompt weighting
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TODO
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## Tabs
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### Txt2img tab
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@ -705,6 +711,10 @@ Some common VAE models include:
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- https://huggingface.co/stabilityai/sd-vae-ft-mse
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- https://huggingface.co/stabilityai/sd-vae-ft-mse-original
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### Optimizing models for lower memory usage
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TODO
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### Permanently blending additional networks
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TODO
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