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GitHub / LTTM / SDR

PyTorch implementation of: Michieli U. and Zanuttigh P., "Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations", CVPR 2021.

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LTTM%2FSDR

Stars: 43
Forks: 5
Open Issues: 0

License: apache-2.0
Language: Python
Repo Size: 7.08 MB
Dependencies: 136

Created: about 3 years ago
Updated: over 1 year ago
Last pushed: about 2 years ago
Last synced: about 1 year ago

Files

Readme

Dependencies

requirements.txt pypi

attrs =19.1.0=py_0
backcall =0.1.0=py37_0
blas =1.0=mkl
bleach =3.1.0=py_0
ca-certificates =2020.1.1=0
certifi =2019.11.28=py37_1
cffi =1.14.0=py37h7a1dbc1_0
chardet =3.0.4=py37_1003
cloudpickle =1.3.0=py_0
cmake =3.16.3=pypi_0
colorama =0.4.3=py_0
configobj =5.0.6=py37_1
constantly =15.1.0=pyh91ea838_0
cudatoolkit =10.1.243=h74a9793_0
cycler =0.10.0=py37_0
dask-core =2.12.0=py_0
decorator =4.4.0=py_0
defusedxml =0.6.0=py_0
dill =0.3.1.1=py37_0
entrypoints =0.3=py37_0
freetype =2.9.1=ha9979f8_1
future =0.17.1=py37_0
google-pasta =0.1.7=py_0
h5py =2.10.0=py37h5e291fa_0
hdf5 =1.10.4=h7ebc959_0
icc_rt =2019.0.0=h0cc432a_1
icu =58.2=ha66f8fd_1
imageio =2.8.0=py_0
inplace-abn =1.0.11=pypi_0
intel-openmp =2020.0=166
ipykernel =5.1.4=py37h39e3cac_0
ipython =7.13.0=py37h5ca1d4c_0
ipython_genutils =0.2.0=py37_0
ipywidgets =7.5.1=py_0
jedi =0.15.1=py37_0
jinja2 =2.11.1=py_0
joblib =0.14.1=py_0
jpeg =9b=hb83a4c4_2
jsonschema =3.0.2=py37_0
jupyter =1.0.0=py37_7
jupyter_client =6.0.0=py_0
jupyter_console =6.1.0=py_0
jupyter_core =4.6.1=py37_0
keras-applications =1.0.8=py_0
keras-preprocessing =1.1.0=py_1
kiwisolver =1.1.0=py37ha925a31_0
libpng =1.6.37=h2a8f88b_0
libsodium =1.0.16=h9d3ae62_0
libtiff =4.1.0=h56a325e_0
m2w64-gcc-libgfortran =5.3.0=6
m2w64-gcc-libs =5.3.0=7
m2w64-gcc-libs-core =5.3.0=7
m2w64-gmp =6.1.0=2
m2w64-libwinpthread-git =5.0.0.4634.697f757=2
markdown =3.1.1=py37_0
markupsafe =1.1.1=py37he774522_0
matplotlib =3.1.1=py37hc8f65d3_0
mistune =0.8.4=py37he774522_0
mkl =2020.0=166
mkl-service =2.3.0=py37hb782905_0
mkl_fft =1.0.15=py37h14836fe_0
mkl_random =1.1.0=py37h675688f_0
msys2-conda-epoch =20160418=1
multicoretsne =0.1=pypi_0
nbconvert =5.6.1=py37_0
nbformat =4.4.0=py37_0
networkx =2.4=py_0
ninja =1.9.0=py37h74a9793_0
nose =1.3.7=py37_2
notebook =6.0.3=py37_0
numpy =1.18.1=py37h93ca92e_0
numpy-base =1.18.1=py37hc3f5095_1
olefile =0.46=py_0
opencv-python =4.2.0.34=pypi_0
openssl =1.1.1f=he774522_0
pandas =1.0.3=py37h47e9c7a_0
pandoc =2.2.3.2=0
pandocfilters =1.4.2=py37_1
parso =0.5.1=py_0
pexpect =4.7.0=py37_0
pickleshare =0.7.5=py37_0
pillow =7.0.0=py37hcc1f983_0
pip =20.0.2=py37_1
prometheus_client =0.7.1=py_0
prompt_toolkit =3.0.3=py_0
protobuf =3.11.3=pypi_0
pycparser =2.20=py_0
pygments =2.4.2=py_0
pyparsing =2.4.2=py_0
pyqt =5.9.2=py37h6538335_2
pyreadline =2.1=py37_1
pyrsistent =0.15.4=py37he774522_0
pyserial =3.4=py37_0
python =3.7.6=h60c2a47_2
python-dateutil =2.8.1=py_0
pytorch =1.4.0=py3.7_cuda101_cudnn7_0
pytz =2019.3=py_0
pywavelets =1.0.3=py37h8c2d366_1
pywin32 =227=py37he774522_1
pywinpty =0.5.7=py37_0
pyzmq =18.1.0=py37ha925a31_0
qt =5.9.7=vc14h73c81de_0
qtconsole =4.5.5=py_0
scikit-image =0.14.0=py37h6538335_1
scikit-learn =0.22.1=py37h6288b17_0
scipy =1.3.1=py37h29ff71c_0
seaborn =0.10.0=py_0
send2trash =1.5.0=py37_0
setuptools =46.0.0=py37_0
simplegeneric =0.8.1=py37_2
sip =4.19.8=py37h6538335_0
six =1.12.0=py37_0
sqlite =3.31.1=he774522_0
tensorboardx =2.0=pypi_0
termcolor =1.1.0=py37_1
terminado =0.8.2=py37_0
testpath =0.4.4=py_0
tk =8.6.8=hfa6e2cd_0
toolz =0.10.0=py_0
torchvision =0.5.0=py37_cu101
tornado =6.0.3=py37he774522_3
traitlets =4.3.3=py37_0
vc =14.1=h0510ff6_4
vs2015_runtime =14.16.27012=hf0eaf9b_1
wcwidth =0.1.7=py37_0
webencodings =0.5.1=py37_1
wheel =0.34.2=py37_0
widgetsnbextension =3.5.1=py37_0
wincertstore =0.2=py37_0
winpty =0.4.3=4
wrapt =1.11.2=py37he774522_0
xz =5.2.4=h2fa13f4_4
zeromq =4.3.1=h33f27b4_3
zipp =2.2.0=py_0
zlib =1.2.11=h62dcd97_3
zstd =1.3.7=h508b16e_0