Would anyone be interested in creating an open-source machine learning project focused on Milkdrop? The basic idea is that it would analyze a group of Milkdrop presets and then output new presets, preferably with some guidance from the user.<p>While being an interesting ML challenge that would need to generate valid code, it would also be useful for performers and VJ's.<p>A few possible approaches:<p><pre><code> - Generate new Milkdrop presets
- Find similarity between Milkdrop presets
- Walk between groups of Milkdrop presets
- Use the mash-up technique (of the Milkdrop editor) to combine only select sections of code
- Automatically categorize Milkdrop presets
- A preset editor which suggests lines of code
</code></pre>
The average Milkdrop preset is about 15 kilobytes and can be opened in a text editor. So the presets are human readable. Also the code of a single preset is organized into groups: initialization code, per_frame equations, per_vertex equations, warp shader, composite shader.<p>Open-source Milkdrop projects to build on: https://github.com/projectM-visualizer/projectm --- https://github.com/mvsoft74/BeatDrop<p>=====<p>Dataset curated by hand<p>I've spent the last 7 months curating a best-of collection of Milkdrop presets. I went through 52,000 presets and selected only the best 9,795 Milkdrop presets. Includes screenshots of each preset.<p>https://thefulldomeblog.com/2020/02/21/nestdrop-presets-collection-cream-of-the-crop/<p>The presets have been organized into 11 category folders: Dancer, Drawing, Fractal, Geometric, Hypnotic, Particles, Reaction, Sparkle, Supernova, Waveform, Transition. Within each of these category folders the presets have been further organized into 183 various subcategory folders.<p>Full transparency, I'm part of the NestDrop team. I'd like to breath some life into preset creation. http://www.nestimmersion.ca/nestdrop.html