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Tesseract 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 i

Tesseract 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.

ikornaselur 5y ago
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.
dheera 5y ago
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.
kn100 5y ago
Post processing is absolutely essential with tesseract. Not to self promote but I discussed this at some length in this blog post, if you're interested: https://kn100.me/taking-back-data-from-eufy/ https://kn100.me/taking-back-data-from-eufy/
frosted-flakes 5y ago
I think it's mostly for OCR'ing high-resolution scans of printed media. I scanned and OCR'd a several hundred page printed book (my grandfather's memoirs) with great results. The text needed very little processing. But I had to manually transcribe all of the image captions, because they were scans of photocopies of photocopies of typewriter labels stuck to photos by hand, and thus very poor quality, and Tesseract produced complete gibberish.

ikornaselur 5y ago

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.

dheera 5y ago

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.

kn100 5y ago

Post processing is absolutely essential with tesseract. Not to self promote but I discussed this at some length in this blog post, if you're interested: https://kn100.me/taking-back-data-from-eufy/ https://kn100.me/taking-back-data-from-eufy/

frosted-flakes 5y ago

I think it's mostly for OCR'ing high-resolution scans of printed media. I scanned and OCR'd a several hundred page printed book (my grandfather's memoirs) with great results. The text needed very little processing. But I had to manually transcribe all of the image captions, because they were scans of photocopies of photocopies of typewriter labels stuck to photos by hand, and thus very poor quality, and Tesseract produced complete gibberish.