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Show HN: isometric.nyc – giant isometric pixel art map of NYC

cannoneyed.com

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Re: Show HN: isometric.nyc – giant isometric pixel art map of NYC

#81

Just curious, about how long did this project take you? I don't see that mentioned in the article.

We had our third kid in late November, and I worked sporadically on it over the following two months of paternity leave and holiday... If I had to bet, I'd say I put in well over 200 hours of work on it, the majority of that being manual auditing/driving of the generation process. If any AI model were reliable at checking the generated pixels, I could have automated this process, but they simply aren't there yet, so I had to do a lot more manual work than I'd anticipated.

All told I probably put in less than 20 hours of actual software engineering work, though, which consisted entirely of writing specs and iterating with various coding agents.

Re: Show HN: isometric.nyc – giant isometric pixel art map of NYC

#82

> I’m not particularly interested in getting mired down in the muck of the morality and economics of it all. I’m really only interested in one question: What’s possible now that was impossible before? Upvote for the cool thing I haven’t seen before but cancelled out by this sentiment. Oof.

I mean this pretty literally though - I'm not particularly interested in these questions. They've been discussed a ton by people way more qualified to discuss them, but I personally I feel like it's been pretty much the same conversation on loop for the last 5 years... That's not to say they're not very important issues! They are, and I think it's reasonable to have strong opinions here because they cut to the core o…

I appreciate the thoughtful reply. I will try to give you the benefit of the doubt then and not extrapolate from your relatively benign feelings as it pertains to a creative art project any capacity for you to take up engineering projects that would make the world worse.

You get your votes back from me.

Re: Show HN: isometric.nyc – giant isometric pixel art map of NYC

#83

I was extremely excited until I looked closer and realized how many of these look like ... well AI. The article is such a good read and would recommend people check it out. Feels like something is missing... maybe just a pixelation effect over the actual result? Seems like a lot of the images also lack continuity (something they go over in the article) Overall, such a cool usage of AI that blends Art and AI well.

Yeah it leaves a lot to be desired. Once you see the AI it's hard to unsee. I actually had a few other generation styles, more 8-bit like, that probably would have lended themselves better to actual pixel-art processing, but I opted to use this fine-tune and in for a penny in for a pound, so to speak...

Re: Show HN: isometric.nyc – giant isometric pixel art map of NYC

#84
This doesn't really look like pixel art; it looks like you applied a (very sophisticated) Photoshop filter to Google Earth. Everything is a little blurry, and the characteristic sharp edges of handmade pixel art (e.g. [0]) are completely absent.

To me, the appeal of pixel art is that each pixel looks deliberately placed, with clever artistic tricks to circumvent the limitations of the medium. For instance, look at the piano keys here [1]. They deliberately lack the actual groupings of real piano keys (since that wouldn't be feasible to render at this scale), but are asymmetrically spaced in their own way to convey the essence of a keyboard. It's the same sort of cleverness that goes into designing LEGO sets.

None of these clever tricks are apparent in the AI-generated NYC.

On another note, a big appeal of pixel art for me is the sheer amount of manual labor that went into it. Even if AI were capable of rendering pixel art indistinguishable from [0] or [1], I'm not sure I'd be impressed. It would be like watching a humanoid robot compete in the Olympics. Sure, a Boston Dynamics bot from a couple years in the future will probably outrun Usain Bolt and outgymnast Simone Biles, but we watch Bolt and Biles compete because their performance represents a profound confluence of human effort and talent. Likewise, we are extremely impressed by watching human weightlifters throw 200kg over their heads but don't give a second thought to forklifts lifting 2000kg or 20000kg.

OP touches on this in his blog post [2]:

   I spent a decade as an electronic musician, spending literally thousands of hours dragging little boxes around on a screen. So much of creative work is defined by this kind of tedious grind. [...] This isn't creative. It's just a slog. Every creative field - animation, video, software - is full of these tedious tasks. In the end, the quality of art is defined by the quality of your decisions - how much work you put into something is just a proxy for how much you care and how much you have to say.
I would argue that in some case (e.g. pixel art), the slog is what makes the art both aesthetically appealing (the deliberately placed nature of each pixel is what defines the aesthetic) but also awe-inspiring (the slog represents an immense amount of sustained focus).

[0] https://platform.theverge.com/wp-content/uploads/sites/2/cho...

[1] https://www.reddit.com/media?url=https%3A%2F%2Fi.redd.it%2Fu...

[2] https://cannoneyed.com/projects/isometric-nyc

Re: Show HN: isometric.nyc – giant isometric pixel art map of NYC

#85
post #53

Earlier quoted context omitted.

That’s exactly right - the fine tuned Qwen model was able to generate seamless pixels most of the time, but you can find lots of places around the map where it failed. More interestingly, not even the biggest smartest image models can tell if a seam exists or not (likely due to the way they represent image tokens internally)

I'm curious why you didn't do something like generate new tiles one at a time, but just expand the input area on the sides with already-generated neighbors. Looks like your infill model doesn't really care about tile sizes, and I doubt it really needs full adjacent tiles to match style. Why 2x2 tile inputs rather than say... generate new tiles one at a time, but add 50px of bordering tile on each side that already ha…

Yeah I actually did that quite a bit too. I didn't want to get too bogged down in the nitty gritty of the tiling algorithm because it's actually quite difficult to communicate via writing (which probably contributed to it being hard to get AI to implement).

The issue is that the overall style was not consistent from tile to tile, so you'd see some drift, particularly in the color - and you can see it in quite a few places on the map because of this.

Re: Show HN: isometric.nyc – giant isometric pixel art map of NYC

#86

To take it a step further it would be super cool to so rhiw figure out the roadway system from the map data and use the buildings as masks over the roads and have little simulated cars driving

100% - I originally wanted to do that but when I realized how much manual work I'd have to do just to get the tiles generated I had to cut back on scope pretty hard.

I actually have a nice little water shader that renders waves on the water tiles via a "depth mask", but my fine-tunes for generating the shader mask weren't reliable enough and I'd spent far too much time on the project to justify going deeper. Maybe I'll try again when the next generation of smarter, cheaper models get released.

Re: Show HN: isometric.nyc – giant isometric pixel art map of NYC

#87
This is really wonderful. Thanks for doing it!

I especially appreciated the deep dive on the workflow and challenges. It's the best generally accessible explication I've yet seen of the pros and cons of vibe coding an ambitious personal project with current tooling. It gives a high-level sense of "what it's generally like" with enough detail and examples to be grounded in reality while avoiding slipping into the weeds.

Re: Show HN: isometric.nyc – giant isometric pixel art map of NYC

#88
post #48

Earlier quoted context omitted.

In my experience image models are very "thirsty" and can often learn the overall style of an image from far fewer models. Even Qwen is a HUGE model relatively speaking. Interestingly enough, the model could NOT learn how to reliably generate trees or water no matter how much data and/or strategies I threw at it... This to me is the big failure mode of fine-tuning - it's practically impossible to understand what will…

I see, yeah, I can see how if it's like 100% matching some parts of the style, but then failing completely on other parts, it's a huge pain to deal with. I wonder if a bigger model could loop here - like, have GPT 5.2 compare the fine-tune output and the Nano Banana output, notice that trees + water are bad, select more examples to fine-tune on, and the retry. Perhaps noticing that the trees and water are missing or…

Interestingly enough even the big guns couldn't reliably act as judges. I think there are a few reasons for that:

- the way they represent image tokens isn't conducive to this kind of task

- text-to-image space is actually quite finicky, it's basically impossible to describe to the model what trees ought to look like and have them "get it"

- there's no reliable way to few-shot prompt these models for image tasks yet (!!)

Re: Show HN: isometric.nyc – giant isometric pixel art map of NYC

#89

Sorry about the hug of death - while I spent an embarassing amount of money on rented H100s, I couldn't be bothered to spend $5 for Cloudflare workers... Hope you all enjoy it, it should be back up now

> while I spent an embarassing amount of money on rented H100s

Would you mind sharing a ballpark estimate?

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