I’ve used flucoma to generate clusters of audio to facilitate musaicking, the audio plot. But now I want to use the audio snippets to select video output as well.
I’ve managed to generate a umap of video clips, and these appear as several clusters, the video plot. I could superimpose this over the audio plot, and when selecting an audio clip, I can select 4 nearest neighbours in the video plot. But, the clusters in the audio plot vs the clusters in the video plot are very different.
How can I transform the video plot to match the audio plot? It’s not supercollider specific, more of a python jupyter slant.
That’s a little different from what i had in mind. The video plot is made up of cut up pieces of small 10 sec chunks that have been umapped to a 2D plot. I could do a nearest neighbour on this plot just like how the 2D audio corpus explorer works.
I want to superimpose this plot over the audio plot, and by selecting a node in the audio plot, do a 2 nearest neighbour on the video plot. The problem is the video clusters are different from the audio clusters, so I’d like to transform the video clusters by translate/rotate/skew to roughly match the audio clusters.
so this is #2. and it is not trivial since there is no good way to do it. There is a thread here where I try to do that - matching a space onto another - in which there is also a link to a machine-learnt curated example in SC.
Let me know if that helps or not. I can try to explain better.