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ingradient-lib-temp

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0.8.1 ingradient_lib_temp-0.8.1-py2-none-any.whl

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Project: ingradient-lib-temp
Version: 0.8.1
Filename: ingradient_lib_temp-0.8.1-py2-none-any.whl
Download: [link]
Size: 41831
MD5: bf56d2298c6c347bd6509ad68add45f9
SHA256: c96adca47e1f5cb37a7c9c16a86563b706f0fc28664c38a5b8cb18e634d64f8c
Uploaded: 2021-10-24 09:17:38 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: ingradient-lib-temp
Version: 0.8.1
Summary: Medical Deep Learning Framework.
Author: seungyeob.seon
Author-Email: liamseon[at]gmail.com
Home-Page: https://github.com/InGradient/InGradient_AI_Library
License: MIT
Keywords: pypi deploy
Requires-Dist: SimpleITK
Requires-Dist: revlib
[No description]

WHEEL

Wheel-Version: 1.0
Generator: bdist_wheel (0.33.1)
Root-Is-Purelib: true
Tag: py2-none-any

RECORD

Path Digest Size
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ingradient_library/data_oganizer.py sha256=bNdDXE7lddorCzRsO4bbuZbJEvPGrRsY7e9C6Sc5508 1063
ingradient_library/data_organizer.py sha256=hdkl506dECbxxSHcQUcRvnnOIUDL1zewnRhV4xrs0cM 3530
ingradient_library/dataloads.py sha256=3q4nvC7EbmVkKVjcsfKHspLaho9oWuv-9JU56gdCrxY 27363
ingradient_library/deep_supervision_loss.py sha256=9RNZ4mF28EkoBNGemxIRJ_o1uMq4WIbz5akt5flzyjg 3987
ingradient_library/dice_loss.py sha256=M8z7MPelCMKplNYJgrQc51CifcF8XPMs409i9LeyD2A 1884
ingradient_library/get_imbalance_weight.py sha256=fWPw6jyAWaD81WQjU7RvKeO5UpfRrNMr1s2l7pgByd8 385
ingradient_library/get_information.py sha256=_MWh-pxvN8jPjZtcm4U8QBoeEAWE9mJvzC5zLqkB5E8 995
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ingradient_library/maic.py sha256=-MMJMxc1kgEVE28Oj4_ApC67MArHLUbELIBysCdFb-k 3292
ingradient_library/main.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
ingradient_library/medical_decathlon_organizer.py sha256=3Tvige-CekScv2DhuwzZ7lJAa0Ypu8o0Xv6bCrPQ1Pk 728
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ingradient_lib_temp-0.8.1.dist-info/RECORD — —

top_level.txt

active_contour_loss
data_augmentation
data_organizer
dataloads
deep_supervision_loss
get_imbalance_weight
get_nnunet_setting
inference
ingradient_library
loss
lr_scheduler
maic
medical_decathlon_organizer
model
nnunet_3D_run
optimizer
patch_transform
preprocessing
sampling
trainer
transform
unet
visualization