5 comments

  • nickdothutton 21 minutes ago
    What a great post. There is an element of ascii rendering in a pet project of mine and I’m definitely going to try and integrate this work. From great constraints comes great creativity.
  • sph 40 minutes ago
    Every example I thought "yeah, this is cool, but I can see there's space for improvement" — and lo! did the author satisfy my curiosity and improve his technique further.

    Bravo, beautiful article! The rest of this blog is at this same level of depth, worth a sub: https://alexharri.com/blog

  • adam_patarino 21 minutes ago
    Tell me someone has turned this into a library we can use
  • nathaah3 1 hour ago
    that was so brilliant! i loved it! thanks for putting it out :)
  • Jyaif 57 minutes ago
    It's important to note that the approach described focuses on giving fast results, not the best results.

    Simply trying every character and considering their entire bitmap, and keeping the character that reduces the distance to the target gives better results, at the cost of more CPU.

    This is a well known problem because early computers with monitors used to only be able to display characters.

    At some point we were able to define custom character bitmap, but not enough custom characters to cover the entire screen, so the problem became more complex. Which new character do you create to reproduce an image optimally?

    And separately we could choose the foreground/background color of individual characters, which opened up more possibilities.

    • finghin 10 minutes ago
      In practice isn’t a large HashMap best for lookup, based on compile-time or static constants describing the character-space?
      • spuz 2 minutes ago
        In the appendix, he talks about reducing the lookup space by quantising the sampled points to just 8 possible values. That allowed him to make a look up table about 2MB in size which were apparently incredibly fast.
    • Sharlin 24 minutes ago
      And a (the?) solution is using an algorithm like k-means clustering to find the tileset of size k that can represent a given image the most faithfully. Of course that’s only for a single frame at a time.