A package for extracting tables and images from PDFs
Project description
PDFHarvester
PDFHarvester is a Python package for extracting tables, images, and keywords from PDF documents.
Installation
You can install PDFHarvester using pip:
pip install PDFHarvester
Usage
To extract tables, images, and keywords from a PDF document using PDFHarvester, you can use the following functions:
import pdfharvest as ph
tables = ph.extract_table('path/to/pdf')
images = ph.extract_images('path/to/pdf')
keywords = ph.extract_keywords('path/to/pdf')
extract_table
returns a list of pandas dataframes, one for each table in the PDF. extract_images
returns a list of images as numpy arrays, and extract_keywords
returns a list of keywords as strings.
#Contributing Bug reports and pull requests are welcome on GitHub at https://github.com/yourusername/PDFHarvester. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the Contributor Covenant code of conduct.
#License The package is available as open source under the terms of the MIT License, © 2023 Hashim Puthiyakath.
Please let me know if you have any further questions or concerns.
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