OCRing Music from YouTube with Common Lisp: Difference between revisions

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I guess you could do this with Python+Jupyter as well, but I dunno, this just really feels nifty to me, like it's a natural extension of the REPL experience. It also helped massively while testing out threshold values for the image to see what would work best for classification.
I guess you could do this with Python+Jupyter as well, but I dunno, this just really feels nifty to me, like it's a natural extension of the REPL experience. It also helped massively while testing out threshold values for the image to see what would work best for classification.


I wired it all up by having FFmpeg dump out a series of BMP images to a pipe (so I could quickly parse the buffer size and read it into `lisp-magick-wand`) and set up a parallelized loop to call `classify` and store the parsed-out data.
I wired it all up by having FFmpeg dump out a series of BMP images to a pipe (so I could quickly parse the buffer size and read it into <code>lisp-magick-wand</code>) and set up a parallelized loop to call `classify` and store the parsed-out data.


<syntaxhighlight lang="lisp">
<syntaxhighlight lang="lisp">

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