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pyjpegls

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1.5.1 pyjpegls-1.5.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
pyjpegls-1.5.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
pyjpegls-1.5.1-cp39-cp39-win_amd64.whl
pyjpegls-1.5.1-cp39-cp39-macosx_10_9_x86_64.whl
pyjpegls-1.5.1-cp39-cp39-macosx_11_0_arm64.whl
pyjpegls-1.5.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
pyjpegls-1.5.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
pyjpegls-1.5.1-cp313-cp313-win_amd64.whl
pyjpegls-1.5.1-cp313-cp313-macosx_10_13_x86_64.whl
pyjpegls-1.5.1-cp313-cp313-macosx_11_0_arm64.whl
pyjpegls-1.5.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
pyjpegls-1.5.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
pyjpegls-1.5.1-cp312-cp312-win_amd64.whl
pyjpegls-1.5.1-cp312-cp312-macosx_10_13_x86_64.whl
pyjpegls-1.5.1-cp312-cp312-macosx_11_0_arm64.whl
pyjpegls-1.5.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
pyjpegls-1.5.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
pyjpegls-1.5.1-cp311-cp311-win_amd64.whl
pyjpegls-1.5.1-cp311-cp311-macosx_10_9_x86_64.whl
pyjpegls-1.5.1-cp311-cp311-macosx_11_0_arm64.whl
pyjpegls-1.5.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
pyjpegls-1.5.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
pyjpegls-1.5.1-cp310-cp310-win_amd64.whl
pyjpegls-1.5.1-cp310-cp310-macosx_10_9_x86_64.whl
pyjpegls-1.5.1-cp310-cp310-macosx_11_0_arm64.whl

Wheel Details

Project: pyjpegls
Version: 1.5.1
Filename: pyjpegls-1.5.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Download: [link]
Size: 2642182
MD5: 65504577339077aa53b950a13f51f8ed
SHA256: 747919893b160ff61f67dfb69593f9653c2597bb5b481baa2a7a315ea26c588e
Uploaded: 2024-10-28 11:23:21 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: pyjpegls
Version: 1.5.1
Summary: JPEG-LS for Python via CharLS C++ Library
Author: pydicom contributors
Author-Email: "Pierre V. Villeneuve" <pierre.villeneuve[at]gmail.com>
Project-Url: documentation, https://pydicom.github.io/pydicom
Project-Url: download, https://github.com/pydicom/pyjpegls/archive/master.zip
Project-Url: homepage, https://github.com/pydicom/pyjpegls
Project-Url: repository, https://github.com/pydicom/pyjpegls
License: MIT
Keywords: python, jpeg
Classifier: License :: OSI Approved :: MIT License
Classifier: Development Status :: 5 - Production/Stable
Classifier: Natural Language :: English
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: File Formats
Classifier: Topic :: Scientific/Engineering :: Image Processing
Requires-Python: >=3.9
Requires-Dist: numpy (>=2.0)
Description-Content-Type: text/markdown
[Description omitted; length: 3127 characters]

WHEEL

Wheel-Version: 1.0
Generator: setuptools (75.2.0)
Root-Is-Purelib: false
Tag: cp39-cp39-manylinux_2_17_x86_64
Tag: cp39-cp39-manylinux2014_x86_64

RECORD

Path Digest Size
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jpeg_ls/CharLS.py sha256=lFD_C4T8CpI3CLVXSUur-Q4xf4DSYcj9osAFVjsUn1U 14880
jpeg_ls/data_io.py sha256=L_cDU3W-a1bTFif4hL2alZwdSQ_bmIM0ZjOb3U-G_R8 675
jpeg_ls/example.py sha256=h1SN2uwd8UOMAM4wSz1Vn57C-5n12mS3W3KWSn2eSeQ 913
jpeg_ls/define_charls_dll.h sha256=RGuWiE4kmIPmB_CTQCJLWAYSK4fKAcj6bvaZgdFTEH4 187
jpeg_ls/_CharLS.pyx sha256=IY-Bj1Ug_ZjDDWGUkEB3l7bcFADiwh2HAY8pKSgFVEE 11406
jpeg_ls/__init__.py sha256=gk9Kpou8LzXWFuRDOMVwhNiK40VKdZitfJps3b2j6IY 834
jpeg_ls/tests/test_decode.py sha256=QI4ugCDrAvdscdeUK7soqHeWnBbE3nwjYyopwmZT-FE 18929
jpeg_ls/tests/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
jpeg_ls/tests/test_encode.py sha256=SA1kX4ODQYOgdeXR-5v5dwY2If4xQGtjHRjsAC6RtIo 18449
jpeg_ls/tests/jlsimV100/TEST16.PGM sha256=HrIAGg_mbJ1Ed2tAo1qqO2ik_nTLdJ5icdllIzeBSdI 131088
jpeg_ls/tests/jlsimV100/T16E0.JLS sha256=AWmqtuuDmSXMeBAW48PtGdMj-t7pnZdHN154e4jk0j8 60077
jpeg_ls/tests/jlsimV100/T8SSE3.JLS sha256=IV4-F2EkdJkXupZ2xFlwlyVyHMJuCFG0-XwapfZ3-w8 32231
jpeg_ls/tests/jlsimV100/T8C2E3.JLS sha256=3x-o4awyVqLqImmW0nyL1QSnygg4VnSu33e27dQr6N4 62300
jpeg_ls/tests/jlsimV100/T16E3.JLS sha256=47cyfSMiR5Sb1qpFINOiYnu2DJUv8j1wDJKQCnCGOBM 42189
jpeg_ls/tests/jlsimV100/T8C1E3.JLS sha256=vkHJwmh1QtRSFxrmKcdpBbevcHPZ21b5pUm2Mj327R4 63005
jpeg_ls/tests/jlsimV100/T8C0E0.JLS sha256=jFZPvTqGZ70HHMjZlJUv3649YttcNZvkttZzToms6m0 102248
jpeg_ls/tests/jlsimV100/TEST8R.PGM sha256=lHT77C_lQiGwlD9PQwFPcEaaJHhlTR9Kwd4FvtPOsYI 65551
jpeg_ls/tests/jlsimV100/README_IMG.TXT sha256=CfhG64Ap10iPzmPiE2F9liY95yWPzDcFG_Xr0-ttFiA 3157
jpeg_ls/tests/jlsimV100/TEST8B.PGM sha256=PEpNJNV9Jq_Iara8RIbcgT6DqPWVsMDs5zehrXQCoGA 65551
jpeg_ls/tests/jlsimV100/T8NDE0.JLS sha256=w-EkTfwDVibL3qeomoEg_eOuTesihHaVkoz71fNohK4 9421
jpeg_ls/tests/jlsimV100/T8SSE0.JLS sha256=vugG2S-xHc2vStHbzGlWIvlf3U2KfW139y_BoNmPbSY 51781
jpeg_ls/tests/jlsimV100/TEST8BS2.PGM sha256=bPQonwr9idBiL_C_wEqDB3CxBLlpumno6VKxg0-vaaQ 16399
jpeg_ls/tests/jlsimV100/T8C2E0.JLS sha256=LL8dOLnRhqBup7Gcx032JZ0jjHifSe1zKajjSv1rpa4 99734
jpeg_ls/tests/jlsimV100/T8C1E0.JLS sha256=_db6IvlBNffD23ky2iFUrvx5CF_sOz9l2opi1pZLgHg 100615
jpeg_ls/tests/jlsimV100/T8NDE3.JLS sha256=BZfBbW1g2J8Kqecaj9a7-YLvGuItS4r8iX2vpo79kOg 6111
jpeg_ls/tests/jlsimV100/TEST8GR4.PGM sha256=nLW0ORKDb86LH0DrKtZ_7Z0cMDQhZB5n1nWZCdEON9M 16398
jpeg_ls/tests/jlsimV100/TEST8G.PGM sha256=rmB60bYe-jQIMamw8MIo91KQjsWbIN6qVLTAQZ0OAP0 65551
jpeg_ls/tests/jlsimV100/T8C0E3.JLS sha256=Y1Zzfb9RaAAM68XkBW4E62h2ZM0VeX3jJPoIRetAfcM 63645
jpeg_ls/tests/jlsimV100/TEST8.PPM sha256=p-yqhBuKfcExpzAH8NbAdzLpAQKYEORco8x4j9-elZM 196623
pyjpegls-1.5.1.dist-info/top_level.txt sha256=Dr3kJtOpIGlM1pqaYKuLugMeAnNIZorU5et1wnS_-Yg 16
pyjpegls-1.5.1.dist-info/RECORD — —
pyjpegls-1.5.1.dist-info/METADATA sha256=2RmOfVOJ64XemtZyLQEcAcIRt7GDiN_tlDP-Le9U80w 4520
pyjpegls-1.5.1.dist-info/WHEEL sha256=kSJjjAI8d0NP8TzOGVWuKHf8Zn9O8E8Zof2t_MzmXHg 147

top_level.txt

_CharLS
jpeg_ls