valkit | The set of validators for Python | Validation library

by mdevaev Python Version: 0.1.4 License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | valkit Summary

valkit is a Python library typically used in Utilities, Validation applications. valkit has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can install using 'pip install valkit' or download it from GitHub, PyPI.

The set of validators for Python 3

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Quality

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Support

valkit has a low active ecosystem.

It has 2 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 12 months.

valkit has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of valkit is 0.1.4

Quality

valkit has 0 bugs and 0 code smells.

Security

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

valkit code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

valkit does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

valkit releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

It has 775 lines of code, 72 functions and 15 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed valkit and discovered the below as its top functions. This is intended to give you an instant insight into valkit implemented functionality, and help decide if they suit your requirements.

Validate arg .
Validate a path .
Validate logging level .
Validate a valid IP address .
Validate that arg is a valid IP address family .
Check if a string matches a regular expression .
Return a list of strings .
Validate a port number .
Validate a filename .
Validate if arg is empty .

Get all kandi verified functions for this library.

valkit Key Features

No Key Features are available at this moment for valkit.

valkit Examples and Code Snippets

No Code Snippets are available at this moment for valkit.

Community Discussions

Trending Discussions on valkit

How can I maximise the reliability of tesseract ocr for text recognition as much as possible?

QUESTION

How can I maximise the reliability of tesseract ocr for text recognition as much as possible?

Asked 2022-Jan-03 at 23:33

I am attempting to collect data from a shop in a game ( starbase ) in order to feed the data to a website in order to be able to display them as a candle stick chart

So far I have started using Tesseract OCR 5.0.0 and I have been running into issues as I cannot get the values reliably

I have seen that the images can be pre-processed in order to increase the reliability but I have run into a bottleneck as I am not familiar enough with Tesseract and OpenCV in order to know what to do more

Please note that since this is an in-game UI the images are going to be very constant as there is no colour variations / light changes / font size changes / ... I technically only need to get it to work once and that's it

Here are the steps I have taken so far and the results :

I have started by getting a screen of only the part of the UI I am interested in in order to remove as much clutter as possible

I have then set a threshold as shown here ( I will also be using the cropping part when doing the automation but I am not there yet ), set the language to English and the psm argument to 6 witch gives me the following code :

...

ANSWER

Answered 2022-Jan-03 at 23:02

Pytesseract, on its own, doesn't handle table detection very well - the table format isn't retained in the output, which can make it difficult to parse, as seen in your output.

So splitting the table into distinct columns, performing OCR on each, and then rejoining the columns will help. This is slower, but it is more accurate.

Dilation can help, which adds white pixels to existing white areas (using the threshold and image you currently have). This expands the narrow areas of the numbers.

In my experience, to improve the accuracy generally means splitting the table up into different sections, as well as testing different thresholds and dilation settings.

Source https://stackoverflow.com/questions/70570743

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install valkit

You can install using 'pip install valkit' or download it from GitHub, PyPI.
You can use valkit like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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