tessdoc | Tesseract documentation | Computer Vision library

I am trying to install tesseract-ocr on Debian 9 with gcc (Debian 6.3.0-18+deb9u1) 6.3.0 20170516.

I run with the below order, according to this https://github.com/tesseract-ocr/tessdoc/blob/master/Compiling-%E2%80%93-GitInstallation.md

./autogen.sh ./configure make

Now when I run make I get the following error:

I tried searching around in the internet, github issues and such, but was unable to find if it's possible to get the result with different possible character alternatives while using tesseract.

for example while running tesseract -l jpn --psm 10 input.png - on this image I get the output 白, but if possible I'd like to also see the other possibilities, and if possible with their confidence coefficients.

I found that it's specially useful while trying to recognize a single character as the tesseract --psm 10 will give wrong but close results for complex kanji.

Like was being recognized as 側. So, I was thinking if I could like get the 5 most probable or sth like that from the command line, then it could be great. And if it's not possible through the command line I'm also willing to see a direct programming approach using the API.

EDIT: tesseract -l jpn --psm 10 iu.png - command on results in 雨 result. On doing this on the code given in the answer I can see that the confidence is 93.68% and shows only one result. If I run the same in this image instead , I'll get 言 (99.46%) which means it is giving a sensible result, but it's only giving me a single result ignoring others. I hypothesized that it does so because the confidence is high because if I run the same command on , I get 遊 but when I run the code, I get

I'm having issues reading white text on a bright background, it finds the text itself but it cannot really translate it correctly.

The image:

The result I keep getting is LanEerus which is not that far off, to be honest.

What I'm wondering is what image pre-processing could fix this? I'm using photoshop to manually pre-process it before I try to do it with code, to find what should work first.

I've tried making it a bitmap, but that makes the borders of the text pretty bad, resulting in tesseract just translating it to random characters.

Inverting colors and/or grayscaling doesn't seem to do the trick, either.

Anyone have any ideas? I know it's a pretty bad background for the text for this case. Trust me, I wish that the background was different!

My code for the tests:

I have a rather small set of images which contains dates. The size might be a problem, but I'd say that the quality is OK. I have followed the guidelines to provide the clearest image I can to the engine. After resizing, apply filters, lots of trial and error, etc. I came up with an image that is almost properly read. I put an example below:

Now, this is read as “9 MAR 2021\n\x0c. Not bad, but the first 2 is read as ". At this point I think I'm misusing part of the power of Tesseract. After all, I know what it should expect, i.e. something as "%d %b %Y".

Is there a way to tell Tesseract that it should try to find the best match given this strong constraint? Providing this metadata to the engine should heavily facilitate the task. I have been reading the documentation, but I can't find the way to do this.

I'm using pytesseract on Tesseract 4.1. with Pytyon 3.9.

I have installed the pytesseract module in my venv and want to extract text from a german file

with executingthis script from pytesseract and setting the lenguage to german

I am using the current alpha version 5 of tesseract. Currently, I am trying to train using images without font files. I managed to generate box files from the image using the following command.

I want to convert the C++ version Result iterator example in tesseract-ocr doc to Python.