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* Add instructions on how to install alongside pyenv (#393)

Like probably many others, I have a lot of different virtualenvs, one for each project. Most of them are handled by `pyenv`. 
After installing according to these instructions I had issues with ´pyenv`and `miniconda` fighting over the $PATH of my system.
But then I stumbled upon this nice solution on SO: https://stackoverflow.com/a/73139031 , upon which I have based my suggested changes.

It runs perfectly on my M1 setup, with the anaconda setup as a virtual environment handled by pyenv. 

Feel free to incorporate these instructions as you see fit. 

Thanks a million for all your hard work.

* Disabled debug output (#436)

Co-authored-by: Henry van Megen <hvanmegen@gmail.com>

* Add New Logo

Co-authored-by: Håvard Gulldahl <havard@lurtgjort.no>
Co-authored-by: Henry van Megen <h.vanmegen@gmail.com>
Co-authored-by: Henry van Megen <hvanmegen@gmail.com>
Co-authored-by: Lincoln Stein <lincoln.stein@gmail.com>
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@ -1,7 +1,7 @@
<h1 align='center'><b>Stable Diffusion Dream Script</b></h1> <h1 align='center'><b>Stable Diffusion Dream Script</b></h1>
<p align='center'> <p align='center'>
<img src="static/logo_temp.png"/> <img src="static/logo.png"/>
</p> </p>
<p align="center"> <p align="center">
@ -22,7 +22,7 @@ text-to-image generator. This fork supports:
generating images in your browser. generating images in your browser.
3. Support for img2img in which you provide a seed image to guide the 3. Support for img2img in which you provide a seed image to guide the
image creation image creation. (inpainting & masking coming soon)
4. Preliminary inpainting support. 4. Preliminary inpainting support.
@ -33,7 +33,7 @@ text-to-image generator. This fork supports:
7. Weighted subprompts for prompt tuning. 7. Weighted subprompts for prompt tuning.
8. [Image variations](VARIATIONS.md) which allow you to systematically 7. [Image variations](VARIATIONS.md) which allow you to systematically
generate variations of an image you like and combine two or more generate variations of an image you like and combine two or more
images together to combine the best features of both. images together to combine the best features of both.
@ -387,7 +387,6 @@ and introducing a new vocabulary to the fixed model.
To train, prepare a folder that contains images sized at 512x512 and execute the following: To train, prepare a folder that contains images sized at 512x512 and execute the following:
WINDOWS: As the default backend is not available on Windows, if you're using that platform, set the environment variable `PL_TORCH_DISTRIBUTED_BACKEND=gloo` WINDOWS: As the default backend is not available on Windows, if you're using that platform, set the environment variable `PL_TORCH_DISTRIBUTED_BACKEND=gloo`
``` ```

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