SnapMotion is the most famous and used tool to extract images from videos. The application allows you tu capture all frames you want without loss of quality. It has two modes: The manual mode where you can extract images precisely at the selected time. The batch processing mode where you can extract thousands images concurrently. SnapMotion is an application which allows you to extract images from videos in a quick and simple way. The extracted images are in the best possible quality. They can be extracted manually at a selected time or automatically every X number of seconds, depending on the settings. The images can be resized before being saved. A manual mode allowing you to extract images precisely at the selected time. A batch processing mode allowing you to extract thousands images concurrently. SnapMotion has been designed to support big video files such as 4K movies and to extract every frame of your media if needed. The application can play every video supported natively by macOS.

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Released:

A wrapper around the pdftoppm and pdftocairo command line tools to convert PDF to a PIL Image list.

Project description

A python (3.5+) 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:pathtopoppler-xxbin' as an argument in convert_from_path.

Mac

Mac users will have to install poppler for Mac.

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

Then simply do:

OR

OR better yet

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)

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)

Need help?

Use the mattermost chat to ask questions on the helpdesk and get direct support.

What's new?

• 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)

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