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README.md
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README.md
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# ONNX Web
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# ONNX Web
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This is a rudimentary web UI for ONNX models, providing a way to run GPU-accelerated models on Windows and even AMD
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This is a web UI for running ONNX models with GPU acceleration locally or on a remote machine.
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with a remote web interface.
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This is still fairly early and instructions are a little rough, but it works on my machine. If I keep working on this
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The API runs on both Linux and Windows and provides access to the major functionality of `diffusers`, metadata
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for more than a week, I would like to add img2img and Nvidia support.
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about the available models and accelerators, and the output of previous runs.
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The GUI runs in all major browsers, including on mobile devices, and allows you to select the model and accelerator
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being used, along with the prompt and other image parameters. The last few output images are shown, making it easy to
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refer back to previous parameters.
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![txt2img with example astronaut prompt and image](./docs/readme-preview.png)
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![txt2img with example astronaut prompt and image](./docs/readme-preview.png)
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@ -15,6 +18,8 @@ Based on guides by:
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- https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs
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- https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs
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- https://www.travelneil.com/stable-diffusion-updates.html
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- https://www.travelneil.com/stable-diffusion-updates.html
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This is still an early project and the instructions are a little rough, but it works on my machine.
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## Features
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## Features
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- REST API server capable of running ONNX models with DirectML acceleration
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- REST API server capable of running ONNX models with DirectML acceleration
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@ -54,11 +59,11 @@ This is a very similar process to what [harishanand95](https://gist.github.com/h
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and [averad's](https://gist.github.com/averad/256c507baa3dcc9464203dc14610d674) gists recommend, split up into a few
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and [averad's](https://gist.github.com/averad/256c507baa3dcc9464203dc14610d674) gists recommend, split up into a few
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steps:
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steps:
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1. Install Git and Python, if you have not already
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1. [Install Git and Python](#install-git-and-python), if you have not already
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2. Create a virtual environment
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2. [Create a virtual environment](#create-a-virtual-environment)
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3. Install pip packages
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3. [Install pip packages](#install-pip-packages)
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4. Install ORT Nightly package
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4. [Install ORT Nightly package](#install-ort-nightly-package)
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5. Download and convert models
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5. [Download and convert models](#download-and-convert-models)
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### Note about setup paths
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### Note about setup paths
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