layout-parser | Unified Toolkit for Deep Learning Based Document Image | Computer Vision library

by Layout-Parser Python Version: v0.3.4 License: Apache-2.0

X-Ray Key Features Code Snippets(5)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | layout-parser Summary

layout-parser is a Python library typically used in Artificial Intelligence, Computer Vision, Deep Learning, Pytorch applications. layout-parser has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install layout-parser' or download it from GitHub, PyPI.

LayoutParser aims to provide a wide range of tools that aims to streamline Document Image Analysis (DIA) tasks. Please check the LayoutParser demo video (1 min) or full talk (15 min) for details. And here are some key features:.

Support

Quality

Security

License

Reuse

Support

layout-parser has a medium active ecosystem.

It has 3669 star(s) with 365 fork(s). There are 63 watchers for this library.

It had no major release in the last 12 months.

There are 72 open issues and 54 have been closed. On average issues are closed in 31 days. There are 9 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of layout-parser is v0.3.4

Quality

layout-parser has 0 bugs and 0 code smells.

Security

layout-parser has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

layout-parser code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

layout-parser is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

layout-parser releases are available to install and integrate.

Deployable package is available in PyPI.

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

Installation instructions, examples and code snippets are available.

It has 3664 lines of code, 282 functions and 45 files.

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

Top functions reviewed by kandi - BETA

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

Draw text on canvas .
Load a PDF file .
Draws a box .
Gather the full text annotation from the response .
Get a local path to a local path .
Initialize the model .
Returns a list of tokens that are line - wise close .
Gives generalized connected component analysis .
Load predictor .
Extract words from pdfplumber .

Get all kandi verified functions for this library.

layout-parser Key Features

No Key Features are available at this moment for layout-parser.

layout-parser Examples and Code Snippets

How to use Traits Manager with your mod

PHP

Lines of Code : 3

License : Strong Copyleft (GPL-3.0)

Copy

if CpecificTraitsManager ~= nil then
	CpecificTraitsManager.SetData(require('script/~path/__tables'))
end

ScanDB

Python

Lines of Code : 2

License : No License

Copy

celery -A ScanDB worker --loglevel=info

python manage.py runserver

MacOS M1 system is detected as ARM by Python package even though I'm using Rosetta

Python

Lines of Code : 3

License : Strong Copyleft (CC BY-SA 4.0)

Copy

> python -c 'import platform; print(platform.platform())'
macOS-12.0.1-arm64-i386-64bit

PyTorch throws OSError on Detectron2LayoutModel()

Python

Lines of Code : 2

License : Strong Copyleft (CC BY-SA 4.0)

Copy

pytesseract.pytesseract.tesseract_cmd = r'path\to\folder\Tesseract_OCR\tesseract.exe'

PyTorch throws OSError on Detectron2LayoutModel()

Python

Lines of Code : 2

License : Strong Copyleft (CC BY-SA 4.0)

Copy

model = lp.Detectron2LayoutModel(config_path='path/to/config.yaml', ...)

Community Discussions

Trending Discussions on layout-parser

MacOS M1 system is detected as ARM by Python package even though I'm using Rosetta

QUESTION

MacOS M1 system is detected as ARM by Python package even though I'm using Rosetta

Asked 2021-Dec-07 at 00:04

I'm on a Macbook with M1 (Apple ARM architecture) and I've tried running the following Python code using the layoutparser library, which indirectly uses pycocotools:

...

ANSWER

Answered 2021-Dec-07 at 00:04

Charles Duffy explained the problem in the comments, thank you! 😃

When I checked the platform in Python, it was indeed ARM:

Source https://stackoverflow.com/questions/70253218

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

Vulnerabilities

No vulnerabilities reported

Install layout-parser

After several major updates, layoutparser provides various functionalities and deep learning models from different backends. But it still easy to install layoutparser, and we designed the installation method in a way such that you can choose to install only the needed dependencies for your project:. Extra steps are needed if you want to use Detectron2-based models. Please check installation.md for additional details on layoutparser installation.