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Decision brief
Disco Diffusion is a comprehensive toolkit of Jupyter Notebooks and models for creating advanced AI-generated art and animations, including modes for 3D animation and video input.
Good fit when
- Use Disco Diffusion when you specifically need to implement Katherine Crowson's Secondary Model Method or Dango's advanced cutout technique.
- It is a good choice if you are interested in 3D animation capabilities that leverage models like AdaBins and MiDaS for depth estimation, combined with pytorch3d transformations.
Avoid when
- Avoid Disco Diffusion if the inclusion of Super Resolution or SLIP models is critical to your project's requirements.
- Do not use this tool if you are looking for a solution that requires frequent updates and refinements, since development has ceased at version v5.1.
- Pricing:
- freemium - The Disco Diffusion repository is open source under an ambiguous 'Other' license; commercial use may require negotiation with contributors.
- Requirements:
- Min 8 GB RAM; Colab-Convert must be installed for .py to .ipynb conversion.; Ensure that python and pip are up to date.
Observed Jul 15, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (1119d since push)
- As of 3w
- Provenance
- Not a fork · Organization account
- As of 3w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/alembics/disco-diffusionSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A collection of notebooks, models, and techniques for generating AI art and animations.
Capability facts
- Languages
- jupyter notebook
Source: github.language · Aug 1, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 1, 2026)
This project uses a special conversion tool to convert the python files into notebooks for easier development.Source link
Tags
README
Disco Diffusion
A frankensteinian amalgamation of notebooks, models and techniques for the generation of AI Art and Animations.
[to be updated with further info soon]
Contributing
This project uses a special conversion tool to convert the python files into notebooks for easier development.
What this means is you do not have to touch the notebook directly to make changes to it
the tool being used is called Colab-Convert
- install using
pip install colab-convert - convert .py to .ipynb
colab-convert /path/to/file.py /path/to/file.ipynb - convert .ipynb to .py
colab-convert /path/to/file.ipynb /path/to/file.py
Changelog
v1 Oct 29th 2021 - Somnai
- Initial QoL improvements added, including user friendly UI, settings+prompt saving and improved google drive folder organization.
v1.1 Nov 13th 2021 - Somnai
- Now includes sizing options, intermediate saves and fixed image prompts and perlin inits. unexposed batch option since it doesn't work
v2 Update: Nov 22nd 2021 - Somnai
- Initial addition of Katherine Crowson's Secondary Model Method (https://colab.research.google.com/drive/1mpkrhOjoyzPeSWy2r7T8EYRaU7amYOOi#scrollTo=X5gODNAMEUCR)
- Fix for incorrectly named settings files
v3 Update: Dec 24th 2021 - Somnai
- Implemented Dango's advanced cutout method
- Added SLIP models, thanks to NeuralDivergent
- Fixed issue with NaNs resulting in black images, with massive help and testing from @Softology
- Perlin now changes properly within batches (not sure where this perlin_regen code came from originally, but thank you)
v4 Update: Jan 2022 - Somnai
- Implemented Diffusion Zooming
- Added Chigozie keyframing
- Made a bunch of edits to processes
v4.1 Update: Jan 14th 2022 - Somnai
- Added video input mode
- Added license that somehow went missing
- Added improved prompt keyframing, fixed image_prompts and multiple prompts
- Improved UI
- Significant under the hood cleanup and improvement
- Refined defaults for each mode
- Removed SLIP models for the time being due to import conflicts
- Added latent-diffusion SuperRes for sharpening
- Added resume run mode
v5 Update: Feb 20th 2022 - gandamu / Adam Letts
- Added 3D animation mode. Uses weighted combination of AdaBins and MiDaS depth estimation models. Uses pytorch3d for 3D transforms on Colab and/or Linux.
v5.1 Update: Mar 30th 2022 - zippy / Chris Allen and gandamu / Adam Letts
- Integrated Turbo+Smooth features from Disco Diffusion Turbo -- just the implementation, without its defaults.
- Implemented resume of turbo animations in such a way that it's now possible to resume from different batch folders and batch numbers.
- 3D rotation parameter units are now degrees (rather than radians)
- Corrected name collision in sampling_mode (now diffusion_sampling_mode for plms/ddim, and sampling_mode for 3D transform sampling)
- Added video_init_seed_continuity option to make init video animations more continuous
- Removed pytorch3d from needing to be compiled with a lite version specifically made for Disco Diffusion
- Remove Super Resolution
- Remove Slip Models
- Update for crossplatform support
v5.1 Update: Apr 4th 2022 - MSFTserver aka HostsServer
- Removed pytorch3d from needing to be compiled with a lite version specifically made for Disco Diffusion
- Remove Super Resolution
- Remove Slip Models
- Update for crossplatform support
v5.2 Update: Apr 10th 2022 - nin_artificial / Tom Mason
- VR Mode
v5.3 Update: Jun 10th 2022 - nshepperd, huemin, cut_pow
- Horizontal and Vertical symmetry
- Addition of ViT-L/14@336px model (requires high VRAM)
v5.4 Update: Jun 14th 2022 - devdef / Alex Spirin, integrated into DD main by gandamu / Adam L
For agents
This page has a .md twin and JSON over the API.