pylibjpeg-rle
A fast DICOM (PackBits) RLE plugin for pylibjpeg, written in Rust with a Python wrapper.
Linux, MacOS and Windows are all supported.
Installation
Installing the current release
pip install pylibjpeg-rle
Installing the development version
Make sure Python, Git and Rust are installed. For Windows, you also need to install Microsoft's C++ Build Tools.
git clone https://github.com/pydicom/pylibjpeg-rle
cd pylibjpeg-rle
python -m pip install .
Supported Transfer Syntaxes
| UID | Description | Decoding | Encoding |
|---|---|---|---|
| 1.2.840.10008.1.2.5 | RLE Lossless | Yes | Yes |
Usage
Decoding
With pylibjpeg
from pydicom import dcmread
from pydicom.data import get_testdata_file
ds = dcmread(get_testdata_file("OBXXXX1A_rle.dcm"))
arr = ds.pixel_array
Standalone with pydicom
Alternatively you can use the included functions to decode a given dataset:
from rle import pixel_array, generate_frames
# Return the entire Pixel Data as an ndarray
arr = pixel_array(ds)
# Generator function that only processes 1 frame at a time,
# may help reduce memory usage when dealing with large Pixel Data
for arr in generate_frames(ds):
print(arr.shape)
Encoding
Standalone with pydicom
Convert uncompressed pixel data to RLE encoding and save:
from pydicom import dcmread
from pydicom.data import get_testdata_file
from pydicom.uid import RLELossless
from rle import pixel_data
# Get the uncompressed pixel data
ds = dcmread(get_testdata_file("OBXXXX1A.dcm"))
arr = ds.pixel_array
# RLE encode and encapsulate `arr`
ds.PixelData = pixel_data(arr, ds)
# Set the correct *Transfer Syntax UID*
ds.file_meta.TransferSyntaxUID = RLELossless
ds.save_as('as_rle.dcm')
Benchmarks
Decoding
Time per 1000 decodes, pydicom's default RLE decoder vs. pylibjpeg-rle:
| Dataset | Pixels | Bytes | pydicom | pylibjpeg-rle |
|---|---|---|---|---|
| OBXXXX1A_rle.dcm | 480,000 | 480,000 | 5.7 s | 1.1 s |
| OBXXXX1A_rle_2frame.dcm | 960,000 | 960,000 | 11.5 s | 2.1 s |
| SC_rgb_rle.dcm | 10,000 | 30,000 | 0.28 s | 0.19 s |
| SC_rgb_rle_2frame.dcm | 20,000 | 60,000 | 0.45 s | 0.28 s |
| MR_small_RLE.dcm | 4,096 | 8,192 | 0.46 s | 0.15 s |
| emri_small_RLE.dcm | 40,960 | 81,920 | 1.8 s | 0.67 s |
| SC_rgb_rle_16bit.dcm | 10,000 | 60,000 | 0.48 s | 0.25 s |
| SC_rgb_rle_16bit_2frame.dcm | 20,000 | 120,000 | 0.86 s | 0.39 s |
| rtdose_rle_1frame.dcm | 100 | 400 | 0.16 s | 0.13 s |
| rtdose_rle.dcm | 1,500 | 6,000 | 1.0 s | 0.64 s |
| SC_rgb_rle_32bit.dcm | 10,000 | 120,000 | 0.82 s | 0.35 s |
| SC_rgb_rle_32bit_2frame.dcm | 20,000 | 240,000 | 1.5 s | 0.60 s |
Encoding
Time per 1000 encodes, pydicom's default RLE encoder vs. pylibjpeg-rle and python-gdcm:
| Dataset | Pixels | Bytes | pydicom | pylibjpeg-rle | python-gdcm |
|---|---|---|---|---|---|
| OBXXXX1A.dcm | 480,000 | 480,000 | 30.6 s | 1.4 s | 1.5 s |
| SC_rgb.dcm | 10,000 | 30,000 | 1.9 s | 0.11 s | 0.21 s |
| MR_small.dcm | 4,096 | 8,192 | 3.0 s | 0.11 s | 0.29 s |
| SC_rgb_16bit.dcm | 10,000 | 60,000 | 3.6 s | 0.18 s | 0.28 s |
| rtdose_1frame.dcm | 100 | 400 | 0.28 s | 0.04 s | 0.14 s |
| SC_rgb_32bit.dcm | 10,000 | 120,000 | 7.1 s | 0.32 s | 0.43 s |
3 maintainers
Release files for pylibjpeg-rle 2.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pylibjpeg_rle-2.2.0.tar.gz | 29.1 kB | Details |
Built distributions (wheels)
Total release size: 6.6 MB
Release files / pylibjpeg_rle-2.2.0.tar.gz
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