WordSegmentation | Segmentation of a text-line into words | Computer Vision library

by githubharald Python Version: Current License: MIT

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

kandi X-RAY | WordSegmentation Summary

WordSegmentation is a Python library typically used in Artificial Intelligence, Computer Vision applications. WordSegmentation has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However WordSegmentation build file is not available. You can download it from GitHub.

Segmentation of a text-line into words.

Support

Quality

Security

License

Reuse

Support

WordSegmentation has a low active ecosystem.

It has 98 star(s) with 45 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 2 have been closed. On average issues are closed in 1 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of WordSegmentation is current.

Quality

WordSegmentation has 0 bugs and 0 code smells.

Security

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

WordSegmentation code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

WordSegmentation is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

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

WordSegmentation has no build file. You will be need to create the build yourself to build the component from source.

WordSegmentation saves you 23 person hours of effort in developing the same functionality from scratch.

It has 64 lines of code, 4 functions and 2 files.

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

Top functions reviewed by kandi - BETA

kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of WordSegmentation

Get all kandi verified functions for this library.

WordSegmentation Key Features

No Key Features are available at this moment for WordSegmentation.

WordSegmentation Examples and Code Snippets

No Code Snippets are available at this moment for WordSegmentation.

Community Discussions

Trending Discussions on WordSegmentation

WordSegmentation in SymSpellPlusPlus

QUESTION

WordSegmentation in SymSpellPlusPlus

Asked 2019-May-31 at 13:04

I'd like to use C++ version of SymSpell, which is called SymSpellPlusPlus. In C# version using WordSegmentation looks like this (from the first link):

...

ANSWER

Answered 2019-May-31 at 13:04

The library is buggy and the author needs to make some fixes.

First, compiling gives us a warning about SuggestItem::ShallowCopy, which returns a local variable by reference. Very bad! We can change that to return by value, probably.

This doesn't fix the crash, though.

If we clone the library's repo then run the following testcase in a debugger:

Source https://stackoverflow.com/questions/56394962

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

Vulnerabilities

No vulnerabilities reported

Install WordSegmentation

You can download it from GitHub.
You can use WordSegmentation 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

An anisotropic filter kernel is applied to the input image to create blobs corresponding to words. After thresholding the blob-image, connected components are extracted which correspond to words.

Find more information at: