tesserocr VS pytesseract

Did you read the instructions for windows? https://github.com/sirfz/tesserocr

If you’re using tesserocr then you can use OpenCV images directly, so you can just extract the relevant image rows (e.g. query_image = main_image[prev_line:this_line]) and process then without needing to save each image.

This tutorial is a good start towards getting the data from an image of a form with a known structure. I’d personally recommend using tesserocr (actual library binding, more efficient, more functionality) instead of pytesseract (requires images to be saved before processing, uses command-line options in a subprocess instead of binding to the library), but both should work (that tutorial uses pytesseract, which is also what u/Iceberg_Bart_Simpson linked to).

Side note, but I’d suggest using tesserocr over pytesseract. It’s an actual binding to the tesseract library, so comes with numerous efficiency and interface benefits, and can operate on OpenCV images directly (whereas pytesseract saves them to disk first).

If you’re after speed I’d recommend mss for screenshots/recording, and tesserocr instead of pytesseract (note in particular the OpenCV option.

tesserocr is an actual binding to the tesseract library, and is better in practically every way than pytesseract (more efficient, more options for usage, doesn’t require saving images to disk before they can be processed, and more).

If you have an electronically created pdf (not scanned) and you’re just wanting to run OCR on embedded images then you’ll want a pdf library that can extract the figure images for you, and then you can use tesserocr to run OCR on those images.

If you want a suggestion, use tesserocr instead of Pytesseract. It’s an actual binding to the tesseract library (Python talks to it directly, instead of calling a program as a subprocess), which means it runs more efficiently, you can process multiple images sequentially with the same OCR engine (pytesseract has to start a process and a new engine for every image that gets processed), you get access to more functionality options, and a bunch of other beneficial stuff. If you’re doing preprocessing with OpenCV it’s even possible to pass those arrays directly to tesseract in memory, whereas Pytesseract requires that you save each image to a file before it can process it.

As a somewhat unrelated side note, I’d strongly suggest using tesserocr instead of pytesseract, and even more so if you’re working with opencv as well. It’s a true library binding which means it’s more efficient, you have more functionality available to you, you can process multiple images with the same Tesseract engine, and you can process opencv images directly (compared to pytesseract which saves them as a file first and then calls the tesseract CLI as a subprocess).

In Python the library PyTesseract constructs a command to run and calls Tesseract via the command-line as a subprocess, which is inefficient if you have more than one image to process, because it has to reinitialize the OCR engine for every image. tesserocr is a different library which came around a bit later, which is a direct binding to the Tesseract library, so you can initialise the engine once and process several images with it, and for images that are stored in memory (e.g. OpenCV arrays that you’ve done some processing on) you can process them directly instead of having to save them as individual files (which PyTesseract requires).

If you don't have it already: https://github.com/madmaze/pytesseract

Yes, pytesseract is a wrapper script and all heavy lifting is done by Tesseract. See the README.

As far as working with reading text from a image there are lots of different libraries for doing this sort of thing, but one of the biggest is probably pytesseract. It is extremely powerful for image to text, and reliably beats alphabet soup captchas.

I'm going to use the Tesseract OCR engine and library, and its Python wrapper PyTesseract for text extraction. But there are numerous libraries out there to extract text from an image. In a real world application I would probably use cloud services from AWS, Google or Microsoft to handle this task.

There's Python Tesseract to do the OCR from python. I think this is not really a beginner's project. Not too much programming, but you need to be able to install the required libraries and glue everything together. If you don't know how to do that maybe start with something simpler.

From what I have heard, tesseract is the best python module for OCR

Yeah, I’m pretty sure the Remarkable OCR is not up to these kinds of tasks unfortunately. If you know some coding you could write something that’d likely work well in Python using for ex. this for receiving the mail attachment and this for converting the PDF to CSV. This is in case you’d write your data as a table on the Remarkable, which I guess is preferable to writing something like (0.5, 8.4, -0.3). If you’d rather do it that way, there are other more suitable OCR tools like this one. The checkbox use-case in the comment above would also be possible by modifying this approach. DM if you’d like to discuss further work.

pytesseract - Python-tesseract is an optical character recognition (OCR) tool for python. That is, it will recognize and "read" the text embedded in images. Python-tesseract is a wrapper for Google's Tesseract-OCR Engine. It is also useful as a stand-alone invocation script to tesseract, as it can read all image types supported by the Pillow and Leptonica imaging libraries, including jpeg, png, gif, bmp, tiff, and others. Additionally, if used as a script, Python-tesseract will print the recognized text instead of writing it to a file.

There are multiple open-source OCR tools like pytesseract or EasyOCR, which can be used to integrate OCR functionality into a program. However, these tools require significant configurations to get up and running to provide results with an acceptable accuracy level.