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Showing content from https://github.com/pydicom/pylibjpeg below:

pydicom/pylibjpeg: A Python framework for decoding JPEG images, with a focus on supporting pydicom

A Python 3.8+ framework for decoding JPEG images and decoding/encoding RLE datasets, with a focus on providing support for pydicom.

The package can be installed with extra requirements to enable support for JPEG (with libjpeg), JPEG 2000 (with openjpeg) and Run-Length Encoding (RLE) (with rle), respectively:

pip install pylibjpeg[libjpeg,openjpeg,rle]

Or alternatively with just all:

pip install pylibjpeg[all]

Make sure Git is installed, then

git clone https://github.com/pydicom/pylibjpeg
python -m pip install pylibjpeg

One or more plugins are required before pylibjpeg is able to handle JPEG images or RLE datasets. To handle a given format or DICOM Transfer Syntax you first have to install the corresponding package:

If you're not sure what the dataset's Transfer Syntax UID is, it can be determined with:

>>> from pydicom import dcmread
>>> ds = dcmread('path/to/dicom_file')
>>> ds.file_meta.TransferSyntaxUID.name

Assuming you have pydicom v2.1+ and suitable plugins installed:

from pydicom import dcmread
from pydicom.data import get_testdata_file

# With the pylibjpeg-libjpeg plugin
ds = dcmread(get_testdata_file('JPEG-LL.dcm'))
jpg_arr = ds.pixel_array

# With the pylibjpeg-openjpeg plugin
ds = dcmread(get_testdata_file('JPEG2000.dcm'))
j2k_arr = ds.pixel_array

# With the pylibjpeg-rle plugin and pydicom v2.2+
ds = dcmread(get_testdata_file('OBXXXX1A_rle.dcm'))
# pydicom defaults to the numpy handler for RLE so need
# to explicitly specify the use of pylibjpeg
ds.decompress("pylibjpeg")
rle_arr = ds.pixel_array

You can also just use pylibjpeg to decode JPEG images to a numpy ndarray, provided you have a suitable plugin installed:

from pylibjpeg import decode

# Can decode using the path to a JPG file as str or path-like
arr = decode('filename.jpg')

# Or a file-like...
with open('filename.jpg', 'rb') as f:
    arr = decode(f)

# Or bytes...
with open('filename.jpg', 'rb') as f:
    arr  = decode(f.read())

Assuming you have pydicom v2.2+ and suitable plugins installed:

from pydicom import dcmread
from pydicom.data import get_testdata_file
from pydicom.uid import RLELossless

ds = dcmread(get_testdata_file("CT_small.dcm"))

# Encode in-place using RLE Lossless and update the dataset
# Updates the Pixel Data, Transfer Syntax UID and Planar Configuration
ds.compress(RLELossless)

# Save compressed
ds.save_as("CT_small_rle.dcm")

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