unco | undo any command -

by kazuho C Version: v0.2.0 License: No License

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kandi X-RAY | unco Summary

unco is a C library. unco has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

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unco has a low active ecosystem.

It has 212 star(s) with 12 fork(s). There are 10 watchers for this library.

It had no major release in the last 6 months.

There are 6 open issues and 6 have been closed. On average issues are closed in 0 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of unco is v0.2.0

Quality

unco has 0 bugs and 0 code smells.

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unco has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

unco code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

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Community Discussions

Trending Discussions on unco

Remove uncommon keys from two dictionaries in Python

General approach to parsing text with special characters from PDF using Tesseract?

Dynamically look for index() in list from set of options

QUESTION

Remove uncommon keys from two dictionaries in Python

Asked 2022-Mar-12 at 05:52

I'm writing a program in Python that is meant to remove uncommon keys and their associated values from two dictionaries. For example, given the following dictionaries:

...

ANSWER

Answered 2022-Mar-12 at 05:13

In a case like this, it's usually best to copy over the things you want into a new object, rather than modify the one you have, especially when you are iterating through the old object.

Source https://stackoverflow.com/questions/71447111

QUESTION

General approach to parsing text with special characters from PDF using Tesseract?

Asked 2021-Jun-15 at 20:17

I would like to extract the definitions from the book The Navajo Language: A Grammar and Colloquial Dictionary by Young and Morgan. They look like this (very blurry):

I tried running it through the Google Cloud Vision API, and got decent results, but it doesn't know what to do with these "special" letters with accent marks on them, or the curls and lines on/through them. And because of the blurryness (there are no alternative sources of the PDF), it gets a lot of them wrong. So I'm thinking of doing it from scratch in Tesseract. Note the term is bold and the definition is not bold.

How can I use Node.js and Tesseract to get basically an array of JSON objects sort of like this:

...

ANSWER

Answered 2021-Jun-15 at 20:17

Tesseract takes a lang variable that you can expand to include different languages if they're installed. I've used the UB Mannheim (https://github.com/UB-Mannheim/tesseract/wiki) installation which includes a ton of languages supported.

To get better and more accurate results, the best thing to do is to process the image before handing it to Tesseract. Set a white/black threshold so that you have black text on white background with no shading. I'm not sure how to do this in Node, but I've done it with Python's OpenCV library.

If that font doesn't get you decent results with the out of the box, then you'll want to train your own, yes. This blog post walks through the process in great detail: https://towardsdatascience.com/simple-ocr-with-tesseract-a4341e4564b6. It revolves around using the jTessBoxEditor to hand-label the objects detected in the images you're using.

Edit: In brief, the process to train your own:

Install jTessBoxEditor (https://sourceforge.net/projects/vietocr/files/jTessBoxEditor/). Requires Java Runtime installed as well.
Collect your training images. They want to be .tiffs. I found I got fairly accurate results with not a whole lot of images that had a good sample of all the characters I wanted to detect. Maybe 30/40 images. It's tedious, so you don't want to do TOO many, but need enough in order to get a good sampling.
Use jTessBoxEditor to merge all the images into a single .tiff
Create a training label file (.box)j. This is done with Tesseract itself. tesseract your_language.font.exp0.tif your_language.font.exp0 makebox
Now you can open the box file in jTessBoxEditor and you'll see how/where it detected the characters. Bounding boxes and what character it saw. The tedious part: Hand fix all the bounding boxes and characters to accurately represent what is in the images. Not joking, it's tedious. Slap some tv episodes up and just churn through it.
Train the tesseract model itself

save a file: font_properties who's content is font 0 0 0 0 0
run the following commands:

tesseract num.font.exp0.tif font_name.font.exp0 nobatch box.train

unicharset_extractor font_name.font.exp0.box

shapeclustering -F font_properties -U unicharset -O font_name.unicharset font_name.font.exp0.tr

mftraining -F font_properties -U unicharset -O font_name.unicharset font_name.font.exp0.tr

cntraining font_name.font.exp0.tr

You should, in there close to the end see some output that looks like this:

Master shape_table:Number of shapes = 10 max unichars = 1 number with multiple unichars = 0

That number of shapes should roughly be the number of characters present in all the image files you've provided.

If it went well, you should have 4 files created: inttemp normproto pffmtable shapetable. Rename them all with the prefix of your_language from before. So e.g. your_language.inttemp etc.

Then run:

combine_tessdata your_language

The file: your_language.traineddata is the model. Copy that into your Tesseract's data folder. On Windows, it'll be like: C:\Program Files x86\tesseract\4.0\tessdata and on Linux it's probably something like /usr/shared/tesseract/4.0/tessdata.

Then when you run Tesseract, you'll pass the lang=your_language. I found best results when I still passed an existing language as well, so like for my stuff it was still English I was grabbing, just funny fonts. So I still wanted the English as well, so I'd pass: lang=your_language+eng.

Source https://stackoverflow.com/questions/67991718

QUESTION

Dynamically look for index() in list from set of options

Asked 2020-Jan-12 at 23:41

def _parse_options(productcode_array):
    if not self._check_productcode_has_options(productcode_array):
        return None
    possible_options = {"UV1", "UV2", "Satin", "Linen", "Unco", "Natural"}
    option_index = productcode_array.index()

...

ANSWER

Answered 2020-Jan-12 at 23:39

Example with try/except:

Source https://stackoverflow.com/questions/59709003

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