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that was so brilliant! i loved it! thanks for putting it out :)
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.

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

It's not just monitors. My first exposure to ASCII art were posters that were printed on a Teletype, in the mid 1970's. The files had attributions to RTTY operators, which made me believe they were done by hand. Of course a Teletype had no concept of pixels.

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

Tell me someone has turned this into a library we can use
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.
> To increase the contrast of our sampling vector, we might raise each component of the vector to the power of some exponent.

How do you arrive at that? It's presented like it's a natural conclusion, but if I was trying to adjust contrast... I don't see the connection.

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Next up: proportional fonts and font weights?
Great breakdown and visuals. Most ASCII filters do not account for glyph shape.

It reminds me of how chafa uses an 8x8 bitmap for each glyph: https://github.com/hpjansson/chafa/blob/master/chafa/interna...

There's a lot of nitty gritty concerns I haven't dug into: how to make it fast, how to handle colorspaces, or like the author mentions, how to exaggerate contrast for certain scenes. But I think 99% of the time, it will be hard to beat chafa. Such a good library.

EDIT - a gallery of (Unicode-heavy) examples, in case you haven't seen chafa yet: https://hpjansson.org/chafa/gallery/

Nice! Now add colors and we can finally play Doom on the command line.

More seriously, using colors (not trivial probably, as it adds another dimension), and some select Unicode characters, this could produce really fancy renderings in consoles!

Well-written post. Very interesting, especially the interactive widgets.
The contrast enhancement seems simpler to perform with an unsharp mask in the continuous image.

It probably has a different looking result, though.

I'm not sure if this exponent is actually enhancing contrast or just fixing the gamma.
This is amazing all round - in concept, writing, and coding (both the idea and the blog post about it).

I feel confident stating that - unless fed something comprehensive like this post as input, and perhaps not even then - an LLM could not do something novel and complex like this, and will not be able to for some time, if ever. I’d love to read about someone proving me wrong on that.

I'm confident that they can. This isn't a new idea. Something like this would be a walk in the park for Opus 4.5 in the right harness.

Of course it likely still needs a skilled pair of eyes and a steady hand to keep it on track or keep things performant, but it's an iterative process. I've already built my own ASCII rendering engines in the past, and have recently built one with a coding model, and there was no friction.

I did something very similar to this (searching for similar characters across the grid, including some fuzzy matching for nearby pixels) around 1996. I wonder if I still have the code? It was exceedingly slow, think minutes for a frame at the Pentiums of the time.
Great article!

I think there's a small problem with intermediate values in this code snippet:

  const maxValue = Math.max(...samplingVector)

  samplingVector = samplingVector.map((value) => {
    value = x / maxValue; // Normalize
    value = Math.pow(x, exponent);
    value = x * maxValue; // Denormalize
    return value;
  })
Replace x by value.
Just pushed a fix, should be live in a minute or two, thanks again!
This loop is similarly suspect:

  let maxValue = value;
  for (const externalIndex of AFFECTING_EXTERNAL_INDICES[i]) {
    maxValue = Math.max(value, externalSamplingVector[externalIndex]);
  }
Thanks! This article put a genuine smile on my face, I can still discover some interesting stuff on the Internet beyond AI slop.
It reminds me quite a bit of collision engines for 2D physics/games. Could probably find some additional clever optimisations for the lookup/overlap (better than kd-trees) if you dive into those. Not that it matters too much. Very cool.
Very cool effect!

> It may seem odd or arbitrary to use circles instead of just splitting the cell into two rectangles, but using circles will give us more flexibility later on.

I still don’t really understand why the inner part of the rectangle can’t just be split in a 2x3 grid. Did I miss the explanation?

I think this is connected to the overlap and offset that are used layer to account for complex or symmetrical letter shapes. If the author had just split the grid, those effects would have been harder to achieve.
> I don’t believe I’ve ever seen shape utilized in generated ASCII art, and I think that’s because it’s not really obvious how to consider shape when building an ASCII renderer.

Not to take away from this truly amazing write-up (wow), but there's at least one generator that uses shape:

https://meatfighter.com/ascii-silhouettify/

See particularly the image right above where it says "Note how the algorithm selects the largest characters that fit within the outlines of each colored region."

There's also a description at the bottom of how its algorithm works, if anyone wants to compare.

Appears to be around 150 times slower. I suspect increasing the sample circle cell resolution would give similarly crisp edges.
In the "Image to Terminal character" space this is also a known solution. Map characters to their shape and then pick the one with the lowest diff to the real chunk in the image. If you consider that you have a foreground and a background colour you can get a pretty close image in the terminal :D

https://hpjansson.org/chafa/

My go version: https://github.com/BigJk/imeji

Surprised you didn't include the output result for the test image as a showcase of the library's results.

Edit: nvm, confused by the libraries purpose. Thought it was primarily character based rendering focused based on the subject under discussion.

Yes I have not not seen this technique used for image to ascii art. Maybe for hand crafted stuff it isn't.
Fantastic article! I wrote an ASCII renderer to show a 3D Claude for my Claude Wrapped[^1], and instead of supersampling I just decided to raymarch the whole thing. SDFs give you a smoother result than even super sampling, but of course your scene has to be represented with distance functions and combinations thereof whereas your method is generally applicable.

Taking into account the shape of different ASCII characters is brilliant, though!

[1]: https://spader.zone/wrapped/

Looks very cool! Thanks for sharing.

The resulting ASCII looks dithered, with sequences like e.g. :-:-:-:-:. I'd guess that it's an intentional effect since a flat surface would naturally repeat the same character, right? Where does the dithering come from?

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Mesmerizing, the i, ! shading is unreasonably effective.
Those 3D interactive animations are the smoothest 3D rendering I've ever seen in a mobile browser. I'm impressed