A command line version of Disco Diffusion.
You will need at least 16gb of RAM if not using a GPU. An Nvidia GPU is highly recommended! The speed improvement is massive. 8gb is probably the minimum amount of GPU memory.
This author has an RTX 3080 with 10gb and it runs fairly well, but some advanced features are not possible with "only" 10gb.
You'll also need between 20 and 40gb of free disk space, depending on which models you enable.
Ubuntu 20.04 or similar (A docker environment, VM, or Windows Subsystem for Linux should work provided it can access your GPU).
If using a GPU: CUDA 11.4+ (installation instructions can be found here: https://developer.nvidia.com/cuda-11-4-1-download-archive).
Windows 10 or 11 (If using a GPU, NVIDIA drivers installed) Other versions may work but are untested
Minimal testing has been done with the latest MacOS on an M1 Macbook Air. PLEASE NOTE: GPU acceleration is not yet supported. It will work, but it will be slow.
You can test that your environment is working properly by running:
nvidia-smi
The output should indicate a driver version, CUDA version, and so on. If you get an error, stop here and troubleshoot how to get Nvidia drivers, CUDA, and/or a connection to your GPU with the environment you're using.
[Linux]
sudo apt update
sudo apt upgrade -y
wget https://repo.anaconda.com/archive/Anaconda3-2021.11-Linux-x86_64.sh
bash Anaconda3-2021.11-Linux-x86_64.sh
respond 'yes' to accept license terms and provide install dir when prompted
respond 'yes' to run conda initialization
Logout and back in for the changes to take effect
[Windows]
Download from here and install: https://www.anaconda.com/products/individual
From the start menu, open a "Anaconda Powershell Prompt" (Powershell is important)
[MacOS]
Install Homebrew:
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
Restart your terminal, then:
brew install miniforge
conda init zsh
Restart your terminal again.
[Linux and Windows]
conda create --name progrockdiffusion python=3.7
[MacOS]
conda create --name progrockdiffusion python=3.8
[All Platforms]
conda activate progrockdiffusion
Now change to whatever base directory you want ProgRockDiffusion to go into.
git clone https://github.com/lowfuel/progrockdiffusion.git
cd progrockdiffusion
Note: the "cd" command above is important, as the next steps will add additional libraries and data to ProgRockDiffusion
From here on out, this is the directory you'll want to be in when you use the program.
git clone https://github.com/crowsonkb/guided-diffusion
git clone https://github.com/openai/CLIP.git
git clone https://github.com/assafshocher/ResizeRight.git
git clone https://github.com/CompVis/latent-diffusion.git
git clone https://github.com/CompVis/taming-transformers
pip install -e ./CLIP
pip install -e ./guided-diffusion
pip install -e ./taming-transformers
pip install lpips datetime timm
You defnitely should install the GPU version if you have an NVIDIA card. It's almost 30x faster. Otherwise, you can install the CPU version instead (required for MacOS)
pip install torch==1.10.2+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install torchvision==0.11.3+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install torchaudio==0.10.2+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip install torch==1.11.0+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html
pip install torchvision==0.12.0+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html
pip install torchaudio==0.11.0+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html
[MacOS]
export GRPC_PYTHON_BUILD_SYSTEM_OPENSSL=1
export GRPC_PYTHON_BUILD_SYSTEM_ZLIB=1
pip install grpcio
[All Platforms]
pip install ipywidgets omegaconf pytorch_lightning einops
pip install matplotlib pandas
conda install opencv
[Linux] Depending on your Linux platform, you may get an error about libGL.so.1 If you do, try installing these dependencies:
sudo apt-get install ffmpeg libsm6 libxext6 -y
[Linux] Finally:
sudo apt install imagemagick
NOTE: On your first run it might appear to hang. Let it go for a good while, though, as it might just be downloading models. Somtimes there is no feedback during the download process (why? Who knows)
If you've opened a new terminal or powershell prompt, you may need to activate your ProgRockDiffusion session again:
conda activate progrockdiffusion
CD to the directory where you installed ProgRockDiffusion. Now you're ready!
The simplest way to run it is:
[Linux]
python3 prd.py
[Windows and MacOS]
python prd.py
This will generate an image using the settings from "settings.json", which you could edit to adjust the defaults (or, better yet, make a copy of it and tell prd to use an alternative settings file using the command line arguments below).
Note: On windows you'll type "python" instead of "python3" in the commands below.
usage: python3 prd.py [-h] [-s SETTINGS] [-o OUTPUT] [-p PROMPT]
Generate images from text prompts.
By default, the supplied settings.json file will be used.
You can edit that, and/or use the options below to fine tune:
Optional arguments:
-h, --help show this help message and exit
-s SETTINGS, --settings SETTINGS
A settings JSON file to use, best to put in quotes
Can be specified more than once to layer settings on top of one another
-o OUTPUT, --output OUTPUT
What output directory to use within images_out
-p PROMPT, --prompt PROMPT
Override the prompt
-i, --ignoreseed
Use a random seed instead of what is in your settings file
-c, --cpu CORES
Force CPU mode, and (optionally) specify how many threads to run.
--cuda DEVICE-ID
Specify which CUDA device ID to use for rendering (default: 0).
-g PERCENT, --geninit PERCENT:
Will save an image called geninit.png at PERCENT of overall steps, for use with --useinit
-u, --useinit:
Forces use of geninit.png as an init_image starting at 20% of defined steps.
Usage examples:
To use the Default output directory and settings from settings.json:
python3 prd.py
To use your own settings.json file (note that putting it in quotes can help parse errors):
python3 prd.py -s "some_directory/mysettings.json"
Note that multiple settings files are allowed. They're parsed in order. The values present are applied over any previous value:
python3 prd.py -s "some_directory/mysettings.json" -s "highres.json"
To quickly just override the output directory name and the prompt:
python3 prd.py -p "A cool image of the author of this program" -o Coolguy
Multiple prompts with weight values are supported:
python3 prd.py -p "A cool image of the author of this program" -p "Pale Blue Sky:.5"
You can ignore the seed coming from a settings file by adding -i, resulting in a new random seed
To force use of the CPU for image generation, add a -c or --cpu (warning: VERY slow):
python3 prd.py -c
To specify which CUDA device to use (advanced) by device ID (default is 0):
python3 prd.py --cuda 1
Simply edit the settings.json file provided, or BETTER YET copy it and make several that include your favorite settings. Note that multiple settings files can be specified in your command, and they'll be loaded in order. Settings.json is always loaded, and any specified after that are layered on top (they only need to contain the settings you want to tweak). For example you could have a settings file that just contains a higher width, height, and more steps, for when you want to make a high-quality image. Layer that on top of your regular settings and it will apply those values without changing anything else.
In your prompt, if you use _artist_ instead of an artists name, an artist will be picked at random from artists.txt
pip install --force-reinstall numpy
If you are getting "OMP: Error #15: Initializing libiomp5md.dll, but found libiomp5md.dll already initialized"
This seems to be because of a Pytorch compiling bug for Intel CPUs. You can set an environment variable that will fix this, either on your machine (if you know how to do that), or by editing prd.py. To do it by editing prd.py, find the line that says "import os" and add the following right below it:
os.environ['KMP_DUPLICATE_LIB_OK']='True'
Let's assume you installed the GPU version. You can adjust these instructions if you did CPU first, of course. Clone your existing conda environment:
conda create --name prdcpu --clone progrockdiffusion
conda activate prdcpu
Now install the CPU version of pytorch:
pip install torch==1.11.0+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html
pip install torchvision==0.12.0+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html
pip install torchaudio==0.11.0+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html
All set! You can now switch between the two by simply doing:
conda activate progrockdiffusion
conda activate prdcpu
- Currently Superres Sampling doesn't work, it will crash.
- Animations are untested but likely not working
- Get Animations working