OCRing this is a nightmare and is a good benchmark to any self-proclaimed good OCR/vision model.
I think though it could likely be easily OCR'd if you give the image to any decent agentic harness with a good vision model, e.g. newest Claude/GPT ones, and tell them to split the image per lines, and then just OCR each line individually.
I wonder if the script itself was written by an LLM before obfuscation? There seem to be a lot of comments in it, but in this case it's still ok :)
I don't think it was written by an LLM, some things stand out:
The congratulations text is both in English and Japanese. Contains a single heart emoji.
There was an intention to have a cyan to orange gradient, but the range starts in an ANSI block, ends halfway through the 256 color block and 256 terminal colors are not arranged like a gradient at all.
There's no sleep at the end of the loop where I feel like an LLM would add that defensively.
My code usually clocs at 50/50 (or thereabouts)[0]. Has, since my very first real engineering project (in 1987)[1]. I discuss in detail, here[2].
But one reason that I like LLMs, is that they help me to write even more documentation. I have found that I can instruct an LLM to revise my documentation, and make it even more effective.
[0] https://github.com/ChrisMarshallNY (My GH profile. Pretty much everything there, is like that -has, since long before LLMs were a broken rubber on the drug store shelf).
Human could write that many comments to get enough base64 text for a design. Maybe to even get some of the highlighted characters in places they want (roughly equally spaced apart).
Especially in a case like this, I would definitely write a lot of comments to aid in understanding, thus increasing trust so people would try it out and tinker with it.
Honestly it's a bit of a shame. I checked and they could've shortened their base64 payload by 304 chars by removing all comments except the top two congratulatory ones, or by 524 if they removed those too.
Would they still get the highlighted "PEACE FOR ALL" text throughout the shortened string? It looks like the length, and presence of those characters, was an explicit design choice.
> I guess Uniqlo is run through Windows though: one thing that struck me was the font, which I’m almost certain is Consolas,
Surely this would use whatever font the virtual terminal profile was set to? I don’t know of any method to choose a virtual terminal font from bash and don’t see any code that addresses it?
I thought it was funny that the author used a variety of OCR tools with mixed success before spending a lot of time manually fixing up the output from the best one, rather than just typing it in
Took me almost 2 minutes for 4 lines (and I missed a character in one of them!).
I would opt for OCR too, obviously so I'm prepared for the next bash t-shirt I'd come across...
I think this is a case where two people can successfully complete the task manually faster than one attempting to automate it. Get a ruler, read five centimetres of characters to your colleague, have them repeat that five centimetres back to you, correct as you go. Trial-and-error adjust the five-cm distance depending on your success rate as you go along. Format your string with the same line-breaks as the t-shirt, and remove them at the end, so you can be sure you've got the correct length on each row.
All in, you should have a non-corrupted string in 10-15 min.
That was also my thought… but I grew up mashing rubber keys for hours copying “games” out of magazines and books! Then hours after fixing all the typos!
Cool! I bought one a few months ago as soon as I spotted it at a Uniqlo store, and later ordered a larger size online—I really love wearing them. But it never occurred to me to look into the story behind them.
P
./cool.sh: line 31: bc: command not found
./cool.sh: line 34: bc: command not found
./cool.sh: line 37: bc: command not found
E
./cool.sh: line 31: bc: command not found
./cool.sh: line 34: bc: command not found
./cool.sh: line 37: bc: command not found
I think though it could likely be easily OCR'd if you give the image to any decent agentic harness with a good vision model, e.g. newest Claude/GPT ones, and tell them to split the image per lines, and then just OCR each line individually.
I wonder if the script itself was written by an LLM before obfuscation? There seem to be a lot of comments in it, but in this case it's still ok :)
The congratulations text is both in English and Japanese. Contains a single heart emoji.
There was an intention to have a cyan to orange gradient, but the range starts in an ANSI block, ends halfway through the 256 color block and 256 terminal colors are not arranged like a gradient at all.
There's no sleep at the end of the loop where I feel like an LLM would add that defensively.
My code usually clocs at 50/50 (or thereabouts)[0]. Has, since my very first real engineering project (in 1987)[1]. I discuss in detail, here[2].
But one reason that I like LLMs, is that they help me to write even more documentation. I have found that I can instruct an LLM to revise my documentation, and make it even more effective.
[0] https://github.com/ChrisMarshallNY (My GH profile. Pretty much everything there, is like that -has, since long before LLMs were a broken rubber on the drug store shelf).
[1] https://littlegreenviper.com/wp-content/uploads/2022/07/TF30... (Downloads a PDF)
[2] https://littlegreenviper.com/leaving-a-legacy/
Especially in a case like this, I would definitely write a lot of comments to aid in understanding, thus increasing trust so people would try it out and tinker with it.
The comments can be more cute/awe inspiring for people who aren't as familiar with bash but like solving puzzles as well.
Surely this would use whatever font the virtual terminal profile was set to? I don’t know of any method to choose a virtual terminal font from bash and don’t see any code that addresses it?
All in, you should have a non-corrupted string in 10-15 min.
The old one was: https://www.uniqlo.com/us/en/products/E459561-000/00
Very wow. Shame they assumed everyone has "bc"...