scale2pdf 0.0.7

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Scale2Pdf

A library made at LAION to scale the parsing of PDFs on CPUs. We tested our pipeline on 44-page pdf and on cheap 2 thread CPU with 12GB ram, it took us 3 mins 22 seconds to parse the pdf, save its content both structure, bulk and its images. We provide following results through our framework

1. Table extraction
2. Equation extraction
3. Image Captions
4. Page extraction
5. Keyword extraction
6. Section extraction
7. Authors extraction
8. Bibliography extraction
9. Paragraph extraction
10. Image extraction
11. Abstract extraction

Features

1. added support for ray for scalability

Installation

pip install scale2pdf ray

then install

sudo apt install poppler-utils

from scale2pdf import scalablepdf 
from scale2pdf import extractimages

pdf_path = "/content/2408.06257v3.pdf"
scalablepdf(pdf_path, extract_images=True) # folder is automatically created and results are saved
# if you want to process a folder of pdfs with ray then
scalable_ray("example_folder", extract_images=True, num_cpus=4)
extractimages("2408.06257v3.pdf", "/path/to/output/folder")

Ray caution:

If you don't specify the CPU numbers then 4 CPU cores will be used at a time. You can increase it to the highest number of CPU cores available.

Speedup depends entirely on the CPU and resources available. I had used on a cheap CPU and it was bad since I had only two threads akin 2 CORE. (although threads here means core not threads themselves like in Computer Hardware)

CRAP CPU (NO GPU): 3 min 22 seconds to finish parsing and saving it to JSON.

A Sleeping AI framework made for friends at LAION AI.