khmereasytools 0.3.8

A simple, self-contained library for Khmer text processing, with optional OCR and POS tagging support.

Khmer Easy Tools

A simple, user-friendly, and self-contained Python library for common Khmer Natural Language Processing (NLP) tasks. This package provides easy-to-use functions for keyword extraction and segmentation without requiring complex external dependencies for its core features.

Installation

Install the base package:

pip install khmereasytools

Installing Optional Features

You can install the features you need.

# To install support for POS tagging (khpos)
pip install khmereasytools[khmernltk]

# To install support for OCR (khocr)
pip install khmereasytools[ocr]

# To install all optional features
pip install khmereasytools[all]

For OCR functionality, you must also install Google's Tesseract OCR engine on your system.

• Tesseract Installation Guide
• Make sure to install the Khmer (khm) language data.

How to Use

Keyword Extraction (khfilter)

Uses a built-in segmentation algorithm to find words and remove stop words by using Khmer Stop Word and Segmentaion Dictionary.

import khmereasytools as ket
text = "នេះគឺជាប្រាសាទអង្គរវត្តស្ថិតនៅក្នុងខេត្តសៀមរាប"
keywords = ket.khfilter(text)
print(f"Keywords: '{keywords}'")

Text Segmentation (khseg)

Uses a built-in segmentation algorithm to split text into words.

import khmereasytools as ket
text = "នេះគឺជាប្រាសាទអង្គរវត្ត"
words = ket.khseg(text)
print(f"Segmented Words: {words}")

Syllable Segmentation (khsyllable)

Uses a built-in rule-based method to split text into syllables.

import khmereasytools as ket
text = "សាលារៀន"
syllables = ket.khsyllable(text)
print(f"Syllables: {syllables}")

Part-of-Speech Tagging (khpos)

Requires khmernltk to be installed.

import khmereasytools as ket
# pip install khmereasytools[khmernltk]
text = "ខ្ញុំស្រឡាញ់ភាសាខ្មែរ"
tags = ket.khpos(text)
print(f"POS Tags: {tags}")

OCR from Image (khocr)

Requires ocr dependencies to be installed.

import khmereasytools as ket
# pip install khmereasytools[ocr]
# text_from_image = ket.khocr('khmer_text.png')
# print(f"Text from OCR: {text_from_image}")