PDF Parsing Project
PDF Parsing Project
Embedded Files
This project showcases a versatile PDF parsing program designed to extract various types of data, including text, images, and tables, from PDF files. The program is built using Python and integrates seamlessly with Django Rest Framework, offering a robust solution for parsing and storing PDF data through a RESTful API.
This project showcases a versatile PDF parsing program designed to extract various types of data, including text, images, and tables, from PDF files. The program is built using Python and integrates seamlessly with Django Rest Framework, offering a robust solution for parsing and storing PDF data through a RESTful API.
Key Features:
Key Features:
Text Extraction: Efficiently extracts textual information from PDF documents.
Text Extraction: Efficiently extracts textual information from PDF documents.
Image Extraction: Capable of extracting images embedded within PDF files.
Image Extraction: Capable of extracting images embedded within PDF files.
Table Extraction: Parses tabular data from PDFs, enhancing data comprehensibility.
Table Extraction: Parses tabular data from PDFs, enhancing data comprehensibility.
Download Functionality: Enables users to download the extracted data as a PDF for convenient offline access.
Download Functionality: Enables users to download the extracted data as a PDF for convenient offline access.
Django Rest Framework Integration: Stores the extracted data in a structured manner using the Django Rest Framework, providing a user-friendly API.
Django Rest Framework Integration: Stores the extracted data in a structured manner using the Django Rest Framework, providing a user-friendly API.
One Table data
One Table data
Extracted data in a JSON file
Extracted data in a JSON file
Data stored
Data stored
Django REST framework
Django REST framework
Downloaded Data
Downloaded Data
Testing front-end
Testing front-end
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