tesseract-ocr.github.io | Tesseract documentation | Computer Vision library
kandi X-RAY | tesseract-ocr.github.io Summary
kandi X-RAY | tesseract-ocr.github.io Summary
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QUESTION
I'm following the instructions at https://tesseract-ocr.github.io/tessdoc/Compiling.html#windows and when I run: vcpkg install tesseract:x86-windows-static It is pulling down tesseract 4. I tried using -head and it still pulls down 4. Any idea how I can build a self-contained executable for tesseract 5.x?
...ANSWER
Answered 2022-Feb-15 at 06:39At the moment vcpkg support version 4.1.1: https://vcpkg.info/port/tesseract
There is request for update: https://github.com/microsoft/vcpkg/issues/16019 from Feb 3, 2021 which Microsoft ignores ;-)
You can (manually) upgrade tesseract version in vcpkg. See tesseract forum discussion: https://groups.google.com/g/tesseract-ocr/c/2xAJaGRqymw?pli=1
QUESTION
I'm having issues reading white text on a bright background, it finds the text itself but it cannot really translate it correctly.
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:
...ANSWER
Answered 2021-May-05 at 01:11Here's one possible solution. This is in Python, but it should be clear enough for a Java port. We will apply a method called gained division. The idea is that you try to build a model of the background and then weight each input pixel by that model. The output gain should be relatively constant during most of the image. This will get rid of most of the background color variation. We can use a morphological chain to clean the result a little bit, let's see the code:
QUESTION
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.
ANSWER
Answered 2021-Mar-29 at 15:53You need to know the followings:
Now if we center the image (by adding borders):
Second, we need to make the characters in the image bold to make the OCR result accurate.
Now OCR:
QUESTION
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.
...ANSWER
Answered 2020-Mar-08 at 10:32Found it,
QUESTION
I want to convert the C++ version Result iterator example in tesseract-ocr doc to Python.
...ANSWER
Answered 2020-Feb-11 at 15:21I think the problem is that api->Recognize() expects a pointer as first argument. They mistakenly put a 0 in their example but it should be nullptr. 0 and nullptr both have the same value but on 64bits systems they don't have the same size (usually ; I assume on some weird non-x86 systems this may not be true either).
Their example still works with a C++ compiler because the compiler is aware that the function expects a pointer (64bits) and fix it silently.
In your example, it seems you haven't specified the exact prototype of TessBaseAPIRecognize() to ctypes. So ctypes can't know a pointer (64 bits) is expected by this function. Instead it assumes that this function expects an integer (32 bits) --> it crashes.
My suggestions:
- Use
ctypes.c_void_p(None)instead of 0 - If you intend to use that in production, specify to ctypes all the function prototypes
- Be careful with the examples you look at: Those examples use Tesseract base API (C++ API) whereas if you want to use libtesseract with Python + ctypes, you have to use Tesseract C API. Those 2 APIs are very similar but may not be identical.
If you need further help, you can have a look at how things are done in PyOCR. If you decide to use PyOCR in your project, just beware that the license of PyOCR is GPLv3+, which implies some restrictions.
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