add test script, screenshot to readme
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README.md
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README.md
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# ONNX Web UI
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# ONNX Web UI
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This is a rudimentary web UI for ONNX models, providing a way to run GPU-accelerated models on Windows and AMD with a
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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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remote web interface.
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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.
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![txt2img with example astronaut prompt and image](./docs/readme-preview.png)
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Based on work by:
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Based on work by:
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- [Setup](#setup)
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- [Setup](#setup)
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- [Install Git and Python](#install-git-and-python)
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- [Install Git and Python](#install-git-and-python)
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- [Create a Virtual Environment](#create-a-virtual-environment)
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- [Create a Virtual Environment](#create-a-virtual-environment)
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- [Install pip packages](#install-pip-packages)
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- [Install AI packages](#install-ai-packages)
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- [Install ORT Nightly package](#install-ort-nightly-package)
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- [Install ORT Nightly package](#install-ort-nightly-package)
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- [Download and Convert Models](#download-and-convert-models)
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- [Download and Convert Models](#download-and-convert-models)
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- [Usage](#usage)
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- [Usage](#usage)
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## Setup
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## Setup
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This is a very similar process to what harishanand95 and averad's gists recommend, split up into a few larger steps:
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This is a very similar process to what [harishanand95](https://gist.github.com/harishanand95/75f4515e6187a6aa3261af6ac6f61269)
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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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1. Create a virtual environment
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1. Install Git and Python, if you have not already
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2. Install pip package
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2. Create a virtual environment
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3. Install AI packages
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4. Install ORT Nightly package
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5. Download and convert models
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### Install Git and Python
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### Install Git and Python
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> .\onnx_env\Scripts\Activate.bat
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> .\onnx_env\Scripts\Activate.bat
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```
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```
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### Install pip packages
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### Install AI packages
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Update pip itself:
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Update pip itself:
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from diffusers import OnnxStableDiffusionPipeline
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cfg=8
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steps=22
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height=512
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width=512
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prompt = "an astronaut eating a hamburger"
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pipe = OnnxStableDiffusionPipeline.from_pretrained("../../stable_diffusion_onnx", provider="DmlExecutionProvider", safety_checker=None)
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image = pipe(prompt, height, width, num_inference_steps=steps, guidance_scale=cfg).images[0]
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image.save("test.png")
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return <Box>
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return <Box>
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<Stack spacing={2}>
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<Stack spacing={2}>
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<Box>
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txt2img mode
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</Box>
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<Select
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<Select
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value={scheduler}
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value={scheduler}
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label="Scheduler"
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label="Scheduler"
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