fix(docs): add links from getting started to other docs
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@ -86,9 +86,9 @@ mark-of-the-web check to ensure the server runs successfully. Upon extraction, i
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file. Once model conversion is complete, the server will commence, opening a browser window for immediate access to the
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web UI.
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### Cross platform setup
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For more details, please see [the setup guide](./setup-guide.md#windows-all-in-one-bundle).
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Link to the other methods.
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### Cross platform setup
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Users who have a working Python environment and prefer installing their own dependencies can opt for a cross-platform
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installation using a Python virtual environment. Ensure a functioning Python setup with either pip or conda. Begin by
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@ -96,6 +96,8 @@ cloning the onnx-web git repository, followed by installing the base requirement
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platform. Execute the launch script, patiently waiting for the model conversion process to conclude. Post-conversion,
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open your browser and load the web UI for interaction.
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For more details, please see [the setup guide](./setup-guide.md#cross-platform-method).
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### Server setup with containers
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For server administrators, onnx-web is also distributed as OCI containers, offering a streamlined deployment. Choose the
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@ -103,6 +105,8 @@ installation method that aligns with your proficiency and system requirements, w
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bundle, the intermediate cross-platform setup, or the containerized deployment for server admins. Each pathway ensures a
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straightforward onnx-web installation tailored to your technical needs.
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For more details, please see [the server admin guide](./server-admin.md#containers).
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## Running
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Running onnx-web is the gateway to unlocking the creative potential of Stable Diffusion in AI art. Whether you are a
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@ -140,42 +144,56 @@ The txt2img tab in onnx-web serves the purpose of generating images from text pr
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descriptions and witness the algorithm's creative interpretation, providing a seamless avenue for text-based image
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generation.
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For more details, please see [the user guide](./user-guide.md#txt2img-tab).
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### Img2img Tab
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For image-based prompts, the img2img tab is the go-to interface within onnx-web. Beyond its fundamental image
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generation capabilities, this tab introduces the ControlNet mode, empowering users with advanced control over the
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generated images through an innovative feature set.
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For more details, please see [the user guide](./user-guide.md#img2img-tab).
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### Inpaint Tab
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The inpaint tab specializes in image generation with a unique combination of image prompts and masks. This
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functionality allows users to guide the algorithm using both the source image and a mask, enhancing the precision and
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customization of the generated content.
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For more details, please see [the user guide](./user-guide.md#inpaint-tab).
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### Upscale Tab
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Addressing the need for higher resolutions, the upscale tab provides users with tools for high resolution and super
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resolution. This feature is particularly useful for enhancing the quality and clarity of generated images, meeting
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diverse artistic and practical requirements.
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For more details, please see [the user guide](./user-guide.md#upscale-tab).
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### Blend Tab
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Enabling users to combine outputs or integrate external images, the blend tab in onnx-web offers a versatile blending
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tool. This functionality adds a layer of creativity by allowing users to merge multiple outputs or incorporate
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external images seamlessly.
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For more details, please see [the user guide](./user-guide.md#blend-tab).
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### Models Tab
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Central to managing the core of onnx-web, the models tab provides users with the capability to manage Stable Diffusion
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models. Additionally, it allows for the management of LoRAs (Latents of Random Ancestors) associated with these
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models, facilitating a comprehensive approach to model customization.
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For more details, please see [the user guide](./user-guide.md#models-tab).
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### Settings Tab
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Tailoring the user experience, the settings tab is the control center for managing onnx-web's web UI settings. Users
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can configure server APIs, toggle dark mode for a personalized visual experience, and reset other tabs as needed,
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ensuring a user-friendly and customizable environment.
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For more details, please see [the user guide](./user-guide.md#settings-tab).
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## Image parameters
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In onnx-web, image parameters play a pivotal role in shaping the output of the Stable Diffusion process. These
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@ -184,6 +202,8 @@ height, collectively govern the characteristics of the diffusion model's trainin
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### Common image parameters
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These parameters are part of the Stable Diffusion pipeline and common to most tools.
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- Scheduler
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- Role: The scheduler dictates the annealing schedule during the diffusion process.
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- Explanation: It determines how the noise level changes over time, influencing how the diffusion process resolves
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@ -226,6 +246,8 @@ height, collectively govern the characteristics of the diffusion model's trainin
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### Unique image parameters
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These parameters are unique to how onnx-web generates images.
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- UNet tile size
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- One such parameter is the UNet tile size. This parameter governs the maximum size for each instance the UNet model
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runs. While it aids in reducing memory usage during panoramas and high-resolution processes, caution is needed.
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@ -269,6 +291,8 @@ networks can be effectively utilized at higher or lower values, spanning from -1
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sliders. This flexibility provides users with nuanced control over the influence of LoRA networks on the generated
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images.
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For more details, please see [the user guide](./user-guide.md#lora-and-lycoris-tokens).
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### CLIP skip
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`<clip:skip:2>` for anime.
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@ -279,6 +303,8 @@ image results. For instance, skipping 2 levels refines the output by bypassing s
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optimizing the creative outcome. This combination of tokens and functionalities enables users to precisely tailor
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prompts in onnx-web for expressive image generation.
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For more details, please see [the user guide](./user-guide.md#clip-skip-tokens).
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## Highres
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onnx-web supports a unique highres implementation, a powerful tool for super-resolution upscaling followed by img2img
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@ -300,6 +326,8 @@ recursive image features.
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Highres prompts are separated from the base txt2img prompt using the double pipe syntax (`||`). These prompts guide the
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upscaling and refinement processes, enabling users to incorporate distinct instructions and achieve nuanced outputs.
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For more details, please see [the user guide](./user-guide.md#prompt-stages).
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### Highres iterations
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`scale ** iterations`
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@ -311,6 +339,8 @@ original size. This scaling effect continues exponentially with each additional
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prompts and iterations allows users to progressively enhance image resolution while maintaining detailed and refined
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visual elements.
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For more details, please see [the user guide](./user-guide.md#highres-iterations-parameter).
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## Profiles
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The onnx-web web UI simplifies user experience with the introduction of a feature known as profiles. When you find
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@ -370,6 +400,8 @@ functionality proves invaluable for adding characters to backgrounds, introducin
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precise control over where elements appear. It becomes a powerful tool for avoiding crowded or overlapping elements,
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offering nuanced control over image composition.
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For more details, please see [the user guide](./user-guide.md#region-tokens).
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### Region seeds
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`<reseed:X:Y:W:H:seed>`
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@ -379,6 +411,8 @@ times within the same image. To prevent hard edges and seamlessly integrate thes
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region prompts and region seeds include options for blending with the surrounding prompt or seed. It's important to
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note that these region features are currently exclusive to the panorama pipeline.
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For more details, please see [the user guide](./user-guide.md#reseed-tokens-region-seeds).
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## Grid mode
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onnx-web introduces a powerful feature known as Grid Mode, designed to facilitate the efficient generation of multiple
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