Wheelodex » Projects » pyjpegls » pyjpegls-1.5.1-cp39-cp39-win_amd64.whl

pyjpegls

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-win_amd64.whl
Download:	[link]
Size:	1143562
MD5:	`793b2a7d46a19b09129bf85d4ace02f6`
SHA256:	`51579d55f38ce96e593f14168fb2df062b5101e55ffd7ec59e0d8b926d9a3122`
Uploaded:	2024-10-28 11:23:22 +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
License-File:	license.txt

[Description omitted; length: 3127 characters]

WHEEL

Wheel-Version:	1.0
Generator:	setuptools (75.2.0)
Root-Is-Purelib:	false
Tag:	cp39-cp39-win_amd64

RECORD

Path	Digest	Size
_CharLS.cp39-win_amd64.pyd	sha256=E2_VXycANTpsBCUrW1MMFR03r5OryWCSByDraOd6lgU	277504
jpeg_ls/CharLS.py	sha256=l4ba8QBKDT_3OPoxfgcBcgG1ti6yNFX7MZSnaEBl3uo	15321
jpeg_ls/_CharLS.pyx	sha256=nngNBDna6XcXgeZFaLpWRnhghr19TXsQt90xY9C_-5E	11801
jpeg_ls/__init__.py	sha256=gk9Kpou8LzXWFuRDOMVwhNiK40VKdZitfJps3b2j6IY	834
jpeg_ls/data_io.py	sha256=ShKz4rxvV65vILaOFzgm_UgHR8Y-r2ybBjmaLPbAAg0	698
jpeg_ls/define_charls_dll.h	sha256=RGuWiE4kmIPmB_CTQCJLWAYSK4fKAcj6bvaZgdFTEH4	187
jpeg_ls/example.py	sha256=-rxeIi5qPByOOsIfz8z9X2zX-i7Btmzb5To6RZ_LCy8	943
jpeg_ls/tests/__init__.py	sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU	0
jpeg_ls/tests/test_decode.py	sha256=odiD5AV4n9OF-XraHXq1DjTpwyZqkkEXTB7AQFp7BCI	19504
jpeg_ls/tests/test_encode.py	sha256=EnWn7plMWkd9xTpiNAaEm1NN1r2FsLdIVeTl9LpLwS0	19087
jpeg_ls/tests/jlsimV100/README_IMG.TXT	sha256=ngvzw23TFZRqnnBhjsZZz4TvNAoCG6ai8Um5iEjXTrQ	3247
jpeg_ls/tests/jlsimV100/T16E0.JLS	sha256=AWmqtuuDmSXMeBAW48PtGdMj-t7pnZdHN154e4jk0j8	60077
jpeg_ls/tests/jlsimV100/T16E3.JLS	sha256=47cyfSMiR5Sb1qpFINOiYnu2DJUv8j1wDJKQCnCGOBM	42189
jpeg_ls/tests/jlsimV100/T8C0E0.JLS	sha256=jFZPvTqGZ70HHMjZlJUv3649YttcNZvkttZzToms6m0	102248
jpeg_ls/tests/jlsimV100/T8C0E3.JLS	sha256=Y1Zzfb9RaAAM68XkBW4E62h2ZM0VeX3jJPoIRetAfcM	63645
jpeg_ls/tests/jlsimV100/T8C1E0.JLS	sha256=_db6IvlBNffD23ky2iFUrvx5CF_sOz9l2opi1pZLgHg	100615
jpeg_ls/tests/jlsimV100/T8C1E3.JLS	sha256=vkHJwmh1QtRSFxrmKcdpBbevcHPZ21b5pUm2Mj327R4	63005
jpeg_ls/tests/jlsimV100/T8C2E0.JLS	sha256=LL8dOLnRhqBup7Gcx032JZ0jjHifSe1zKajjSv1rpa4	99734
jpeg_ls/tests/jlsimV100/T8C2E3.JLS	sha256=3x-o4awyVqLqImmW0nyL1QSnygg4VnSu33e27dQr6N4	62300
jpeg_ls/tests/jlsimV100/T8NDE0.JLS	sha256=w-EkTfwDVibL3qeomoEg_eOuTesihHaVkoz71fNohK4	9421
jpeg_ls/tests/jlsimV100/T8NDE3.JLS	sha256=BZfBbW1g2J8Kqecaj9a7-YLvGuItS4r8iX2vpo79kOg	6111
jpeg_ls/tests/jlsimV100/T8SSE0.JLS	sha256=vugG2S-xHc2vStHbzGlWIvlf3U2KfW139y_BoNmPbSY	51781
jpeg_ls/tests/jlsimV100/T8SSE3.JLS	sha256=IV4-F2EkdJkXupZ2xFlwlyVyHMJuCFG0-XwapfZ3-w8	32231
jpeg_ls/tests/jlsimV100/TEST16.PGM	sha256=HrIAGg_mbJ1Ed2tAo1qqO2ik_nTLdJ5icdllIzeBSdI	131088
jpeg_ls/tests/jlsimV100/TEST8.PPM	sha256=p-yqhBuKfcExpzAH8NbAdzLpAQKYEORco8x4j9-elZM	196623
jpeg_ls/tests/jlsimV100/TEST8B.PGM	sha256=PEpNJNV9Jq_Iara8RIbcgT6DqPWVsMDs5zehrXQCoGA	65551
jpeg_ls/tests/jlsimV100/TEST8BS2.PGM	sha256=bPQonwr9idBiL_C_wEqDB3CxBLlpumno6VKxg0-vaaQ	16399
jpeg_ls/tests/jlsimV100/TEST8G.PGM	sha256=rmB60bYe-jQIMamw8MIo91KQjsWbIN6qVLTAQZ0OAP0	65551
jpeg_ls/tests/jlsimV100/TEST8GR4.PGM	sha256=nLW0ORKDb86LH0DrKtZ_7Z0cMDQhZB5n1nWZCdEON9M	16398
jpeg_ls/tests/jlsimV100/TEST8R.PGM	sha256=lHT77C_lQiGwlD9PQwFPcEaaJHhlTR9Kwd4FvtPOsYI	65551
pyjpegls-1.5.1.dist-info/METADATA	sha256=UxU9SCbHF6vAp8_l_GV7PIhrrBW5tvgRMeeVL4Oe4-E	4633
pyjpegls-1.5.1.dist-info/WHEEL	sha256=UAgGEIlEKluxCX20ppULf3M0rfG_1DUMdncOI_parX8	99
pyjpegls-1.5.1.dist-info/license.txt	sha256=MdEd3Vz9VVNJUfTPs1QK6VlvKbYMrMjYedYBEJ2S1e8	1194
pyjpegls-1.5.1.dist-info/top_level.txt	sha256=Dr3kJtOpIGlM1pqaYKuLugMeAnNIZorU5et1wnS_-Yg	16
pyjpegls-1.5.1.dist-info/RECORD	—	—

top_level.txt

_CharLS

jpeg_ls