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Tesseract.js – A Javascript port of the Tesseract OCR engine
21–30 of 38 posts
Re: Tesseract.js – A Javascript port of the Tesseract OCR engine
#22I spend 2 months 2 years ago on building a passport data extractor. For KYC (know your customer) purposes.
Unfortunately I did not manage to get to a situation where the extracted data was really useful.
I just tried this JS version (sure the native one is the same) and without changing anything (apart from the training dataset) I got much better results. Exciting.
Re: Tesseract.js – A Javascript port of the Tesseract OCR engine
#23Tesseract sucked for me. Had a simple use case where I was trying to read numbers (in a computer font) from .png files and at completely predictable locations in the image -- and Tesseract was getting it horribly wrong a huge percent of the time. Went with AWS Rekognition and results were instantly 1000x better.
Re: Tesseract.js – A Javascript port of the Tesseract OCR engine
#24I've used this library in the past for prototyping a project to extract Chinese subtitles from youtube videos in a chrome extension. It worked pretty well. The only problem is the library couldn't really handle realtime video. Can't really fault it for that though I was sending it every frame. The throughput was good but latency kept increasing probably because I was giving it to much data.
There's a mode where you can increase the number of worker threads. Tesseract is also designed for text documents and the preprocessing filter I made to convert the images to look more like a text document was pretty naive.
I'm taking an online computer vision class next semester and hope to pick the project back up after learning a bit more.
Re: Tesseract.js – A Javascript port of the Tesseract OCR engine
#25Tesseract sucked for me. Had a simple use case where I was trying to read numbers (in a computer font) from .png files and at completely predictable locations in the image -- and Tesseract was getting it horribly wrong a huge percent of the time. Went with AWS Rekognition and results were instantly 1000x better.
Had the _exact_ same situation! Was just trying to OCR values of screenshots, which were always of the same screen (app screenshots taken by users) and it was so bad. Ended up just using AWS Rekognition and it worked really well.
Re: Tesseract.js – A Javascript port of the Tesseract OCR engine
#26What is the best way, paid or otherwise, to attempt OCR on a pdf of old typewritten text?
Re: Tesseract.js – A Javascript port of the Tesseract OCR engine
#27I spend 2 months 2 years ago on building a passport data extractor. For KYC (know your customer) purposes. Unfortunately I did not manage to get to a situation where the extracted data was really useful. I just tried this JS version (sure the native one is the same) and without changing anything (apart from the training dataset) I got much better results. Exciting.
For passports, I would use the MRZ instead. All of the passport data is encoded there and it's machine readable.
Re: Tesseract.js – A Javascript port of the Tesseract OCR engine
#28What is the best way, paid or otherwise, to attempt OCR on a pdf of old typewritten text?
Upload to Google drive and it will do it automatically
Re: Tesseract.js – A Javascript port of the Tesseract OCR engine
#29What is the best way, paid or otherwise, to attempt OCR on a pdf of old typewritten text?
ABBYY FineReader has always come out ahead for me in terms of OCR accuracy.
Re: Tesseract.js – A Javascript port of the Tesseract OCR engine
#30Tesseract sucked for me. Had a simple use case where I was trying to read numbers (in a computer font) from .png files and at completely predictable locations in the image -- and Tesseract was getting it horribly wrong a huge percent of the time. Went with AWS Rekognition and results were instantly 1000x better.
We really need better open source {OCR, TTS, dictation, ...}. All of the common FOSS tools for these tasks are so horribly behind the state of the art.
The sad thing is most of the state of the art models and algorithms are open research, they just are usually not written by software engineers and need to be rewritten to be deployable. Usually you just get some shell script like "run_eval.sh" that generates the figures in the paper through a bunch of spaghetti code, and most of the time it will depend on a specific old version of Tensorflow, that probably isn't available for your CUDA version, and probably won't compile on your system without hours of Googling.