Ecosyste.ms: Repos

An open API service providing repository metadata for many open source software ecosystems.

GitHub / luuleitner / deepMTJ

Automatic muscle tendon junction tracking using deep learning 🦵🏼

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

Stars: 16
Forks: 0
Open Issues: 2

License: gpl-3.0
Language: Python
Repo Size: 42.1 MB
Dependencies: 120

Created: over 4 years ago
Updated: about 2 months ago
Last pushed: about 2 months ago
Last synced: 14 days ago

Topics: deep-learning, deepmtj, feature-detection, gait-analysis, locomotion, ultrasound-images

Files

Readme

Dependencies

requirements.txt pypi

blas =1.0=mkl
brotli =1.0.9=h8ffe710_6
brotli-bin =1.0.9=h8ffe710_6
ca-certificates =2022.4.26=haa95532_0
certifi =2022.6.15=py37haa95532_0
cloudpickle =2.0.0=pyhd3eb1b0_0
colorama =0.4.4=pyh9f0ad1d_0
cycler =0.11.0=pyhd8ed1ab_0
cytoolz =0.11.0=py37he774522_0
dask-core =2021.10.0=pyhd3eb1b0_0
fonttools =4.28.5=py37hcc03f2d_0
freeglut =3.2.2=h0e60522_1
freetype =2.10.4=h546665d_1
fsspec =2022.3.0=py37haa95532_0
h5py =2.10.0=py37h5e291fa_0
hdf5 =1.10.4=h7ebc959_0
icc_rt =2019.0.0=h0cc432a_1
icu =68.2=h0e60522_0
imageio =2.9.0=pyhd3eb1b0_0
intel-openmp =2020.2=254
jasper =2.0.33=h77af90b_0
jbig =2.1=h8d14728_2003
joblib =0.17.0=py_0
jpeg =9d=h8ffe710_0
kiwisolver =1.3.2=py37h8c56517_1
lcms2 =2.12=h2a16943_0
lerc =3.0=h0e60522_0
libblas =3.9.0=1_h8933c1f_netlib
libbrotlicommon =1.0.9=h8ffe710_6
libbrotlidec =1.0.9=h8ffe710_6
libbrotlienc =1.0.9=h8ffe710_6
libcblas =3.9.0=5_hd5c7e75_netlib
libclang =11.1.0=default_h5c34c98_1
libdeflate =1.8=h8ffe710_0
liblapack =3.9.0=5_hd5c7e75_netlib
liblapacke =3.9.0=5_hd5c7e75_netlib
libopencv =4.5.5=py37h04cf790_0
libpng =1.6.37=h1d00b33_2
libprotobuf =3.19.4=h7755175_0
libtiff =4.3.0=hd413186_2
libwebp-base =1.2.2=h8ffe710_1
libzlib =1.2.11=h8ffe710_1013
locket =1.0.0=py37haa95532_0
lz4-c =1.9.3=h8ffe710_1
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
matplotlib =3.5.1=py37h03978a9_0
matplotlib-base =3.5.1=py37h4a79c79_0
mkl =2019.4=245
mkl-service =2.3.0=py37hb782905_0
mkl_fft =1.2.0=py37h45dec08_0
mkl_random =1.0.4=py37h343c172_0
msys2-conda-epoch =20160418=1
munkres =1.1.4=pyh9f0ad1d_0
networkx =2.6.3=pyhd3eb1b0_0
numpy =1.19.1=py37h5510c5b_0
numpy-base =1.19.1=py37ha3acd2a_0
olefile =0.46=pyh9f0ad1d_1
opencv =4.5.5=py37h03978a9_0
openjpeg =2.4.0=hb211442_1
openssl =1.1.1o=h2bbff1b_0
os =0.1.4=0
packaging =21.3=pyhd8ed1ab_0
pandas =1.1.3=py37ha925a31_0
partd =1.2.0=pyhd3eb1b0_1
pillow =8.4.0=py37hd7d9ad0_0
pip =21.3.1=pyhd8ed1ab_0
plotly =5.5.0=py_0
py-opencv =4.5.5=py37h4038f58_0
pycoral =2.0.0=pypi_0
pyparsing =3.0.6=pyhd8ed1ab_0
pyqt =5.12.3=py37h03978a9_8
pyqt-impl =5.12.3=py37hf2a7229_8
pyqt5-sip =4.19.18=py37hf2a7229_8
pyqtchart =5.12=py37hf2a7229_8
pyqtwebengine =5.12.1=py37hf2a7229_8
pyreadline =2.1=py37_1
python =3.7.12=h7840368_100_cpython
python-dateutil =2.8.1=py_0
python_abi =3.7=2_cp37m
pytz =2020.1=py_0
pywavelets =1.3.0=py37h2bbff1b_0
pyyaml =5.3.1=py37he774522_0
qt =5.12.9=h5909a2a_4
qutil =3.2.1=6
scikit-image =0.19.2=py37hf11a4ad_0
scikit-learn =0.23.2=py37h47e9c7a_0
scipy =1.5.2=py37h9439919_0
setuptools =60.5.0=py37h03978a9_0
six =1.15.0=py_0
spm1d =0.4.0=py_2
sqlite =3.37.0=h8ffe710_0
tenacity =8.0.1=pyhd8ed1ab_0
tflite-runtime =2.5.0.post1=pypi_0
threadpoolctl =2.1.0=pyh5ca1d4c_0
tifffile =2020.10.1=py37h8c2d366_2
tk =8.6.11=h8ffe710_1
toolz =0.11.2=pyhd3eb1b0_0
tornado =6.1=py37hcc03f2d_2
tqdm =4.62.3=pyhd8ed1ab_0
ucrt =10.0.20348.0=h57928b3_0
unicodedata2 =14.0.0=py37hcc03f2d_0
vc =14.2=hb210afc_6
vs2015_runtime =14.29.30037=h902a5da_6
wheel =0.37.1=pyhd8ed1ab_0
xz =5.2.5=h62dcd97_1
yaml =0.1.7=vc14h4cb57cf_1
zlib =1.2.11=h8ffe710_1013
zstd =1.5.1=h6255e5f_0

setup.py pypi