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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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README.md
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README.md
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<h1 align='center'><b>Stable Diffusion Dream Script</b></h1>
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<h1 align='center'><b>Stable Diffusion Dream Script</b></h1>
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<p align='center'>
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<p align='center'>
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<img src="static/logo_temp.png"/>
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<img src="static/logo.png"/>
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</p>
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</p>
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<p align="center">
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<p align="center">
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@ -22,7 +22,7 @@ text-to-image generator. This fork supports:
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generating images in your browser.
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generating images in your browser.
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3. Support for img2img in which you provide a seed image to guide the
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3. Support for img2img in which you provide a seed image to guide the
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image creation
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image creation. (inpainting & masking coming soon)
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4. Preliminary inpainting support.
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4. Preliminary inpainting support.
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@ -33,9 +33,9 @@ text-to-image generator. This fork supports:
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7. Weighted subprompts for prompt tuning.
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7. Weighted subprompts for prompt tuning.
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8. [Image variations](VARIATIONS.md) which allow you to systematically
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7. [Image variations](VARIATIONS.md) which allow you to systematically
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generate variations of an image you like and combine two or more
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generate variations of an image you like and combine two or more
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images together to combine the best features of both.
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images together to combine the best features of both.
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9. Textual inversion for customization of the prompt language and images.
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9. Textual inversion for customization of the prompt language and images.
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@ -387,9 +387,8 @@ and introducing a new vocabulary to the fixed model.
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To train, prepare a folder that contains images sized at 512x512 and execute the following:
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To train, prepare a folder that contains images sized at 512x512 and execute the following:
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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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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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```
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```
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(ldm) ~/stable-diffusion$ python3 ./main.py --base ./configs/stable-diffusion/v1-finetune.yaml \
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(ldm) ~/stable-diffusion$ python3 ./main.py --base ./configs/stable-diffusion/v1-finetune.yaml \
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-t \
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-t \
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@ -460,7 +459,7 @@ repository and associated paper for details and limitations.
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- WebUI supports GFPGAN/ESRGAN facial reconstruction and upscaling [Kevin Gibbons](https://github.com/bakkot)
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- WebUI supports GFPGAN/ESRGAN facial reconstruction and upscaling [Kevin Gibbons](https://github.com/bakkot)
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- WebUI supports incremental display of in-progress images during generation [Kevin Gibbons](https://github.com/bakkot)
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- WebUI supports incremental display of in-progress images during generation [Kevin Gibbons](https://github.com/bakkot)
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- A new configuration file scheme that allows new models (including upcoming stable-diffusion-v1.5)
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- A new configuration file scheme that allows new models (including upcoming stable-diffusion-v1.5)
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to be added without altering the code. ([David Wager](https://github.com/maddavid12))
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to be added without altering the code. ([David Wager](https://github.com/maddavid12))
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- Can specify --grid on dream.py command line as the default.
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- Can specify --grid on dream.py command line as the default.
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- Miscellaneous internal bug and stability fixes.
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- Miscellaneous internal bug and stability fixes.
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- Works on M1 Apple hardware.
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- Works on M1 Apple hardware.
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@ -484,8 +483,8 @@ There are separate installation walkthroughs for [Linux](#linux), [Windows](#win
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```
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```
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~$ wget https://repo.anaconda.com/archive/Anaconda3-2022.05-Linux-x86_64.sh
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~$ wget https://repo.anaconda.com/archive/Anaconda3-2022.05-Linux-x86_64.sh
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~$ chmod +x Anaconda3-2022.05-Linux-x86_64.sh
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~$ chmod +x Anaconda3-2022.05-Linux-x86_64.sh
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~$ ./Anaconda3-2022.05-Linux-x86_64.sh
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~$ ./Anaconda3-2022.05-Linux-x86_64.sh
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```
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```
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After installing anaconda, you should log out of your system and log back in. If the installation
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After installing anaconda, you should log out of your system and log back in. If the installation
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@ -674,9 +673,9 @@ python scripts\dream.py
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```
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```
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10. Subsequently, to relaunch the script, first activate the Anaconda
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10. Subsequently, to relaunch the script, first activate the Anaconda
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command window (step 3), enter the stable-diffusion directory (step 5,
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command window (step 3), enter the stable-diffusion directory (step 5,
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"cd \path\to\stable-diffusion"), run "conda activate ldm" (step 6b),
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"cd \path\to\stable-diffusion"), run "conda activate ldm" (step 6b),
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and then launch the dream script (step 9).
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and then launch the dream script (step 9).
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**Note:** Tildebyte has written an alternative ["Easy peasy Windows
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**Note:** Tildebyte has written an alternative ["Easy peasy Windows
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install"](https://github.com/lstein/stable-diffusion/wiki/Easy-peasy-Windows-install)
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install"](https://github.com/lstein/stable-diffusion/wiki/Easy-peasy-Windows-install)
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class T2I(Generate):
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class T2I(Generate):
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def __init__(self,**kwargs):
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def __init__(self,**kwargs):
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print(f'>> The ldm.simplet2i module is deprecated. Use ldm.generate instead. It is a drop-in replacement.')
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print(f'>> The ldm.simplet2i module is deprecated. Use ldm.generate instead. It is a drop-in replacement.')
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super().__init__(kwargs)
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super().__init__(kwargs)
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