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add test script, screenshot to readme

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Sean Sube 2023-01-05 09:44:01 -06:00
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# ONNX Web UI
This is a rudimentary web UI for ONNX models, providing a way to run GPU-accelerated models on Windows and AMD with a
remote web interface.
This is a rudimentary web UI for ONNX models, providing a way to run GPU-accelerated models on Windows and even AMD
with a remote web interface.
This is still fairly early and instructions are a little rough, but it works on my machine.
![txt2img with example astronaut prompt and image](./docs/readme-preview.png)
Based on work by:
@ -17,7 +21,7 @@ Based on work by:
- [Setup](#setup)
- [Install Git and Python](#install-git-and-python)
- [Create a Virtual Environment](#create-a-virtual-environment)
- [Install pip packages](#install-pip-packages)
- [Install AI packages](#install-ai-packages)
- [Install ORT Nightly package](#install-ort-nightly-package)
- [Download and Convert Models](#download-and-convert-models)
- [Usage](#usage)
@ -28,10 +32,15 @@ Based on work by:
## Setup
This is a very similar process to what harishanand95 and averad's gists recommend, split up into a few larger steps:
This is a very similar process to what [harishanand95](https://gist.github.com/harishanand95/75f4515e6187a6aa3261af6ac6f61269)
and [averad's](https://gist.github.com/averad/256c507baa3dcc9464203dc14610d674) gists recommend, split up into a few
steps:
1. Create a virtual environment
2. Install pip package
1. Install Git and Python, if you have not already
2. Create a virtual environment
3. Install AI packages
4. Install ORT Nightly package
5. Download and convert models
### Install Git and Python
@ -68,7 +77,7 @@ Every time you start using ONNX web, activate the virtual environment:
> .\onnx_env\Scripts\Activate.bat
```
### Install pip packages
### Install AI packages
Update pip itself:

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from diffusers import OnnxStableDiffusionPipeline
cfg=8
steps=22
height=512
width=512
prompt = "an astronaut eating a hamburger"
pipe = OnnxStableDiffusionPipeline.from_pretrained("../../stable_diffusion_onnx", provider="DmlExecutionProvider", safety_checker=None)
image = pipe(prompt, height, width, num_inference_steps=steps, guidance_scale=cfg).images[0]
image.save("test.png")

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@ -39,9 +39,6 @@ export function Txt2Img(props: Txt2ImgProps) {
return <Box>
<Stack spacing={2}>
<Box>
txt2img mode
</Box>
<Select
value={scheduler}
label="Scheduler"