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A python module that wraps the pdftoppm utility to convert PDF to PIL Image object

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pdf2image

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A python (3.7+) module that wraps pdftoppm and pdftocairo to convert PDF to a PIL Image object

How to install

pip install pdf2image

Windows

Windows users will have to build or download poppler for Windows. I recommend @oschwartz10612 version which is the most up-to-date. You will then have to add the bin/ folder to PATH or use poppler_path = r"C:\path\to\poppler-xx\bin" as an argument in convert_from_path.

Mac

Mac users will have to install poppler.

Installing using Brew:

brew install poppler

Linux

Most distros ship with pdftoppm and pdftocairo. If they are not installed, refer to your package manager to install poppler-utils

Platform-independant (Using conda)

  1. Install poppler: conda install -c conda-forge poppler
  2. Install pdf2image: pip install pdf2image

How does it work?

from pdf2image import convert_from_path, convert_from_bytes
from pdf2image.exceptions import (
    PDFInfoNotInstalledError,
    PDFPageCountError,
    PDFSyntaxError
)

Then simply do:

images = convert_from_path('/home/belval/example.pdf')

OR

images = convert_from_bytes(open('/home/belval/example.pdf', 'rb').read())

OR better yet

import tempfile

with tempfile.TemporaryDirectory() as path:
    images_from_path = convert_from_path('/home/belval/example.pdf', output_folder=path)
    # Do something here

images will be a list of PIL Image representing each page of the PDF document.

Here are the definitions:

convert_from_path(pdf_path, dpi=200, output_folder=None, first_page=None, last_page=None, fmt='ppm', jpegopt=None, thread_count=1, userpw=None, use_cropbox=False, strict=False, transparent=False, single_file=False, output_file=str(uuid.uuid4()), poppler_path=None, grayscale=False, size=None, paths_only=False, use_pdftocairo=False, timeout=600, hide_attributes=False)

convert_from_bytes(pdf_file, dpi=200, output_folder=None, first_page=None, last_page=None, fmt='ppm', jpegopt=None, thread_count=1, userpw=None, use_cropbox=False, strict=False, transparent=False, single_file=False, output_file=str(uuid.uuid4()), poppler_path=None, grayscale=False, size=None, paths_only=False, use_pdftocairo=False, timeout=600, hide_attributes=False)

What's new?

  • Allow users to hide attributes when using pdftoppm with hide_attributes (Thank you @StaticRocket)
  • Fix console opening on Windows (Thank you @OhMyAgnes!)
  • Add timeout parameter which raises PDFPopplerTimeoutError after the given number of seconds.
  • Add use_pdftocairo parameter which forces pdf2image to use pdftocairo. Should improve performance.
  • Fixed a bug where using pdf2image with multiple threads (but not multiple processes) would cause and exception
  • jpegopt parameter allows for tuning of the output JPEG when using fmt="jpeg" (-jpegopt in pdftoppm CLI) (Thank you @abieler)
  • pdfinfo_from_path and pdfinfo_from_bytes which expose the output of the pdfinfo CLI
  • paths_only parameter will return image paths instead of Image objects, to prevent OOM when converting a big PDF
  • size parameter allows you to define the shape of the resulting images (-scale-to in pdftoppm CLI)
    • size=400 will fit the image to a 400x400 box, preserving aspect ratio
    • size=(400, None) will make the image 400 pixels wide, preserving aspect ratio
    • size=(500, 500) will resize the image to 500x500 pixels, not preserving aspect ratio
  • grayscale parameter allows you to convert images to grayscale (-gray in pdftoppm CLI)
  • single_file parameter allows you to convert the first PDF page only, without adding digits at the end of the output_file
  • Allow the user to specify poppler's installation path with poppler_path

Performance tips

  • Using an output folder is significantly faster if you are using an SSD. Otherwise i/o usually becomes the bottleneck.
  • Using multiple threads can give you some gains but avoid more than 4 as this will cause i/o bottleneck (even on my NVMe SSD!).
  • If i/o is your bottleneck, using the JPEG format can lead to significant gains.
  • PNG format is pretty slow, this is because of the compression.
  • If you want to know the best settings (most settings will be fine anyway) you can clone the project and run python tests.py to get timings.

Limitations / known issues

  • A relatively big PDF will use up all your memory and cause the process to be killed (unless you use an output folder)
  • Sometimes fail read pdf signed using DocuSign, Solution for DocuSign issue.