Rolling your own serverless OCR in 40 lines of code
christopherkrapu.com
Rolling your own serverless OCR in 40 lines of code
1–10 of 69 posts
Re: Rolling your own serverless OCR in 40 lines of code
#2Wouldn't "Serverless OCR" mean something like running tesseract locally on your computer, rather than creating an AI framework and running it on a server?
Re: Rolling your own serverless OCR in 40 lines of code
#3Wouldn't "Serverless OCR" mean something like running tesseract locally on your computer, rather than creating an AI framework and running it on a server?
Serverless means spinning compute resources up on demand in the cloud vs. running a server permanently.
Re: Rolling your own serverless OCR in 40 lines of code
#4How does this compare to Tesserect?
Re: Rolling your own serverless OCR in 40 lines of code
#5[deleted]
Re: Rolling your own serverless OCR in 40 lines of code
#6Slight tangent: i was wondering why DeepSeek would develop something like this. In the linked paper it says
> In production, DeepSeek-OCR can generate training data for LLMs/VLMs at a scale of 200k+ pages per day (a single A100-40G).
That... doesn't sound legal
Re: Rolling your own serverless OCR in 40 lines of code
#7Wouldn't "Serverless OCR" mean something like running tesseract locally on your computer, rather than creating an AI framework and running it on a server?
Thanks for noting this - for a moment I was excited.
Re: Rolling your own serverless OCR in 40 lines of code
#8Question for the crowd -- with autoscaling, when a new pod is created it will still download the model right from huggingface?
I like to push everything into the image as much as I can. So in the image modal, I would run a command to trigger downloading the model. Then in the app just point to the locally downloaded model. So bigger image, but do not need to redownload on start up.
Re: Rolling your own serverless OCR in 40 lines of code
#9Wouldn't "Serverless OCR" mean something like running tesseract locally on your computer, rather than creating an AI framework and running it on a server?
Serverless means spinning compute resources up on demand in the cloud vs. running a server permanently.
~99.995% of the computing resources used on this are from somebody else's servers, running the LLM model.
Re: Rolling your own serverless OCR in 40 lines of code
#10Deepseek OCR is no longer state of the art. There are much better open source OCR models available now.
ocrarena.ai maintains a leaderboard, and a number of other open source options like dots [1] or olmOCR [2] rank higher.