update features
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README.md
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README.md
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@ -23,6 +23,7 @@ details](https://github.com/ssube/onnx-web/blob/main/docs/user-guide.md).
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This is an incomplete list of new and interesting features, with links to the user guide:
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- SDXL support
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- hardware acceleration on both AMD and Nvidia
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- tested on CUDA, DirectML, and ROCm
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- [half-precision support for low-memory GPUs](docs/user-guide.md#optimizing-models-for-lower-memory-usage) on both
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@ -37,6 +38,7 @@ This is an incomplete list of new and interesting features, with links to the us
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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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- [panorama](docs/user-guide.md#panorama-pipeline)
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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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@ -45,20 +47,24 @@ This is an incomplete list of new and interesting features, with links to the us
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- [permanent and prompt-based blending](docs/user-guide.md#permanently-blending-additional-networks)
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- [supports LoRA and LyCORIS 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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- each layer of the embeddings can be controlled and used individually
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- ControlNet
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- image filters for edge detection and other methods
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- with ONNX acceleration
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- highres mode
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- runs img2img on the results of the other pipelines
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- multiple iterations can produce 8k images and larger
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- [multi-stage](docs/user-guide.md#prompt-stages) and [region prompts](docs/user-guide.md#region-tokens)
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- combine multiple prompts in the same image
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- provide prompts for different areas in the image and blend them together
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- change the prompt for highres mode and refine details without recursion
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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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- upscaling and correction
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- upscaling with Real ESRGAN, SwinIR, and Stable Diffusion
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- face correction with CodeFormer and GFPGAN
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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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@ -460,7 +460,19 @@ This makes your prompt less specific and some models have been trained to work b
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#### Prompt stages
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TODO: explain `first stage || hires prompt` syntax
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You can provide a different prompt for the highres and upscaling stages of an image using prompt stages. Each stage
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of a prompt is separated by `||` and can include its own LoRAs, embeddings, and regions. If you are using multiple
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iterations of highres, each iteration can have its own prompt stage. This can help you avoid recursive body parts
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and some other weird mutations that can be caused by iterating over a subject prompt.
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For example, a prompt like `human being sitting on wet grass, outdoors, bright sunny day` is likely to produce many
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small people mixed in with the grass when used with highres. This becomes even worse with 2+ iterations. However,
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changing that prompt to `human being sitting on wet grass, outdoors, bright sunny day || outdoors, bright sunny day, detailed, intricate, HDR`
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will use the second stage as the prompt for highres: `outdoors, bright sunny day, detailed, intricate, HDR`.
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This allows you to add and refine details, textures, and even the style of the image during the highres pass.
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Prompt stages are only used during upscaling if you are using the Stable Diffusion upscaling model.
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### Long prompt weighting syntax
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