## Install Disco Diffusion v5 for Windows NOTE: Pytorch3d no longer has to be compiled i have stripped out the function we use to make this a lot easier and also so we do not have to use WSL2 with linux and can now run directly on your windows system. Comments section is not checked often for issues please join the disco diffusion discord for assistance https://discord.gg/mK4AneuycS You may now use the official disco diffusion notebook with this tutorial as it has been uodated to reflect the changes here for better cross platform support This will walk you through getting your environment setup to run most of the GANs with Anaconda as a Virtual Python Environment. System Requirements: ``` OS: Windows (11/10/8/7), Ubuntu(19,20) GPU: Nvidia (AMD hasnt been tested) VRAM: 12gb+ ``` ## 1) Download Tools!
  1. A) Cuda enabled GPU
  1. B) Python (Anaconda)
  1. C) Git
  1. D) FFmpeg
  1. E) ImageMagick
  1. F) Wget
  1. G) cURL
## 2) Install Disco Dependencies
  1. A) Setup and activate conda env
  1. B) Install a few more pip dependencies
  1. C) Install Pytorch with CUDA support!
  1. D) Download disco diffusion repo!
## 3) Run Disco Diffusion there are several ways to run disco diffusion at this point: #### 1. [PYTHON .py] plain python file wich means you will need to go into the file and manually find all the configuration options and change them as needed, an easy way to go about this is searching the document for `#@param` lines and edit ones containing that comment trailing the lines e.g. `use_secondary_model = True #@param {type: 'boolean'}`. #### 2-3. [VS .py/.ipynb] running the .ipynb file directly in VS also requires editing of the #@param lines in the code #### 4-5. [VS + Jupyter extension .py/.ipynb] using the jupyter extension in VS we can get individual cell support to run the either the .ipynb or the .py file also requires editing of the #@param lines in the code #### 6. [Jupyter .ipynb] using Jupyter notebooks to run the .ipynb file also requires editing of the #@param lines in the code #### 7. [Colab w/ Jupyter using colab links] using Google Colab as a front end to get the nice view of all the editable fields while using Jupyter as middleware to connect your local resources