A: didn’t even try what by does
B: Single quotes prevent execution
C: there is no way to execute commands afaik so this won’t work either
D: that syntax is just wrong afaik
Which one of these commands is correct?
A sed -e 's/\b(\w+)\b/echo \1 | rev/g' file.txt
B: sed 's/b\w+\b/echo & | rev/ge' file.txt
Csed -e 's/(\w+)/$(echo \1 | rev)/g' file.txt
D: sed 's/([a-zA-Z]\+\)/\n&\n/g; s/\n\(\)\(.*\)\(\)\n/\3\2\1/g; s/\n//g' file.tx
It’s interesting that Google doesn’t even get all the text. I had to manually extend the selection and that still misses the “t” on the end of answer D, munches C and more alarmingly changes the case for “-E”.
Chatty was so kind to transcribe. May contain errors.
The transcription of D is wrong. It should be:
sed 's/\([a-zA-Z]\+\)/\n&\n/g; s/\n\(.\)\(.*\)\(.\)\n/\3\2\1/g; s/\n//g' file.txtalso D is correct, assuming file.txt contains a list of words one per line
Chatty claims the correct answer to be:
Spoiler
B
I tried it my self and I conclude:
Spoiler
none is correct.
Thought so lol
A: didn’t even try what by does B: Single quotes prevent execution C: there is no way to execute commands afaik so this won’t work either D: that syntax is just wrong afaik
sed can execute commands with the /e option
Google Lens says:
Which one of these commands is correct? A sed -e 's/\b(\w+)\b/echo \1 | rev/g' file.txt B: sed 's/b\w+\b/echo & | rev/ge' file.txt Csed -e 's/(\w+)/$(echo \1 | rev)/g' file.txt D: sed 's/([a-zA-Z]\+\)/\n&\n/g; s/\n\(\)\(.*\)\(\)\n/\3\2\1/g; s/\n//g' file.txIt’s interesting that Google doesn’t even get all the text. I had to manually extend the selection and that still misses the “t” on the end of answer D, munches C and more alarmingly changes the case for “-E”.
OCR of fonts used to be a solved problem, but now we have AI, which can sort of do it sometimes
Why be boring and do it right when you can vibe some letters instead?
OCR was AI.
Anyway today’s models are measurably better especially when you go beyond simple text on a clean page.
Any good OCR model also uses “AI”
And LLMs are usually really good at detecting text
Source: Had to OCR a quite a few ancient university papers