ljpeg 3.7.0

Read and transform LJPEG images

ljpeg

Read and transform LJPEG images into modern formats.

Installation

Warning: You must have installed the flex parser on your operating system:

pip install ljpeg

By default, we offer you a binary called jpeg_static. However, you can produce your jpeg binary:

cd jpegdir && make

Getting started

Download a set of mammograms with:

wget -r -q ftp://figment.csee.usf.edu:21/pub/DDSM/cases/normals/normal_08/case4606/

Transform a lot of mammograms parallely:

find . -type f -name '*.LJPEG' | parallel -j+0 "ljpeg {} $(pwd)/{/.}.tiff --verify"

Convert to TIFF (requires the .ics file in the same directory as LJPEG):

ljpeg $(pwd)/C_0029_1.LEFT_CC.LJPEG $(pwd)/output.tiff

Convert to TIFF and verify that no information has been lost:

ljpeg $(pwd)/C_0029_1.LEFT_CC.LJPEG $(pwd)/output.tiff --verify

Convert to jpeg for visualization with down-sizing scale=0.3 (16-bit TIFF is not good for direct visualization):

ljpeg $(pwd)/C_0029_1.LEFT_CC.LJPEG $(pwd)/output.jpg --visual --scale 0.3

Convert to TIFF and map gray levels to optical density level:

ljpeg $(pwd)/C_0029_1.LEFT_CC.LJPEG $(pwd)/output.jpg --od-correct

Note that output file can be any format that’s supported by OpenCV (which includes all common types). Most file formats only support 8-bit images, so directly saving into such file formats will cause problems. Add “–visual” to normalize color into 8-bit before saving to such file formats.

The Stanford ljpeg code is in public domain and is therefore OK to be included here. I did minor modification to make the code compile under modern Linux.

Making Changes & Contributing

This project uses pre-commit, please make sure to install it before making any changes:

pip install pre-commit
cd demo-project
pre-commit install

It is a good idea to update the hooks to the latest version:

pre-commit autoupdate

Don’t forget to tell your contributors to also install and use pre-commit.

Note

This project has been set up using PyScaffold 4.2.2.post1.dev3+g01e6e81. For details and usage information on PyScaffold see https://pyscaffold.org/.