- You are not paying per inference, you can self host the model
- It can run inside AWS EC2
- It has very high levels of accuracy for extracting code from images
- what are some of the most accurate OCR models out there that can extract code from images
- this however doesn't work really well for structured text like code
- what are some absolutely state of the art self hostable OCR models out there capable of extracting code from text with very high levels of accuracy
- I have tried tesseract currently and it is not very good with this. Even if you are not familiar with any other model, perhaps you can suggest a pipeline for tesseract that I can follow to improve the accuracy of the extraction process
- Currently, my pipeline looks like this:
- for every input image, check if the image is light text on dark background or dark text on light background
- as you know tesseract is trained from mostly dark text on light background so I invert the images with dark background before processing them with tesseract
- are there other processes you think that I need to include?
https://github.com/LESIM-Co-Ltd/CoreOCR
There are other similar wrappers for macOS Vision framework; just search on GitHub.
- my primary use case is to invoke it from a server such as python / express to perform batch recognition for images submitted via api endpoints.
- Any ideas how much time it needs for OCRing a 1280x720 png image. Thank you for sharing that btw
I don't know but it's pretty fast. If I understand correctly, it's using the same functionality as the OCR in Apple Notes. (And for that reason Xcode needs to be installed.)