AmyloidPETNet/environment.yml at main · sotiraslab/AmyloidPETNet · GitHub

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name: p3.7torch1.8
channels:
  - pytorch-lts
  - nvidia
  - defaults
dependencies:
  - _libgcc_mutex=0.1=main
  - _openmp_mutex=5.1=1_gnu
  - blas=1.0=mkl
  - bzip2=1.0.8=h7b6447c_0
  - ca-certificates=2023.01.10=h06a4308_0
  - certifi=2022.12.7=py38h06a4308_0
  - cloudpickle=2.0.0=pyhd3eb1b0_0
  - cudatoolkit=11.1.74=h6bb024c_0
  - cytoolz=0.11.0=py38h7b6447c_0
  - dask-core=2022.7.0=py38h06a4308_0
  - ffmpeg=4.2.2=h20bf706_0
  - flit-core=3.6.0=pyhd3eb1b0_0
  - freetype=2.11.0=h70c0345_0
  - fsspec=2022.11.0=py38h06a4308_0
  - giflib=5.2.1=h7b6447c_0
  - gmp=6.2.1=h295c915_3
  - gnutls=3.6.15=he1e5248_0
  - imageio=2.19.3=py38h06a4308_0
  - intel-openmp=2021.4.0=h06a4308_3561
  - jpeg=9b=h024ee3a_2
  - lame=3.100=h7b6447c_0
  - lcms2=2.12=h3be6417_0
  - ld_impl_linux-64=2.38=h1181459_1
  - libffi=3.3=he6710b0_2
  - libgcc-ng=9.1.0=hdf63c60_0
  - libgfortran-ng=7.3.0=hdf63c60_0
  - libgomp=11.2.0=h1234567_1
  - libidn2=2.3.2=h7f8727e_0
  - libopus=1.3.1=h7b6447c_0
  - libpng=1.6.37=hbc83047_0
  - libstdcxx-ng=9.1.0=hdf63c60_0
  - libtasn1=4.16.0=h27cfd23_0
  - libtiff=4.1.0=h2733197_1
  - libunistring=0.9.10=h27cfd23_0
  - libuv=1.40.0=h7b6447c_0
  - libvpx=1.7.0=h439df22_0
  - libwebp=1.2.0=h89dd481_0
  - locket=1.0.0=py38h06a4308_0
  - lz4-c=1.9.3=h295c915_1
  - mkl=2021.4.0=h06a4308_640
  - mkl-service=2.4.0=py38h7f8727e_0
  - mkl_fft=1.3.1=py38hd3c417c_0
  - mkl_random=1.2.2=py38h51133e4_0
  - ncurses=6.3=h7f8727e_2
  - nettle=3.7.3=hbbd107a_1
  - networkx=2.8.4=py38h06a4308_0
  - ninja=1.10.2=h06a4308_5
  - ninja-base=1.10.2=hd09550d_5
  - numpy-base=1.22.3=py38hf524024_0
  - openh264=2.1.1=h4ff587b_0
  - openssl=1.1.1s=h7f8727e_0
  - packaging=22.0=py38h06a4308_0
  - partd=1.2.0=pyhd3eb1b0_1
  - pillow=9.0.1=py38h22f2fdc_0
  - pip=22.3.1=py38h06a4308_0
  - python=3.8.13=h12debd9_0
  - pytorch=1.8.2=py3.8_cuda11.1_cudnn8.0.5_0
  - pywavelets=1.3.0=py38h7f8727e_0
  - pyyaml=6.0=py38h7f8727e_1
  - readline=8.1.2=h7f8727e_1
  - setuptools=65.6.3=py38h06a4308_0
  - six=1.16.0=pyhd3eb1b0_1
  - sqlite=3.38.5=hc218d9a_0
  - tifffile=2020.10.1=py38hdd07704_2
  - tk=8.6.12=h1ccaba5_0
  - toolz=0.12.0=py38h06a4308_0
  - torchaudio=0.8.2=py38
  - torchvision=0.9.2=py38_cu111
  - typing_extensions=4.4.0=py38h06a4308_0
  - wheel=0.37.1=pyhd3eb1b0_0
  - x264=1!157.20191217=h7b6447c_0
  - xz=5.2.5=h7f8727e_1
  - yaml=0.2.5=h7b6447c_0
  - zlib=1.2.12=h7f8727e_2
  - zstd=1.4.9=haebb681_0
  - pip:
    - absl-py==1.2.0
    - anti-clustering==0.2.1
    - matplotlib==3.7.5
    - nibabel==5.2.1
    - monai==0.8.0
    - numpy==1.23.3
    - ortools==9.3.10497
    - pandas==1.4.4
    - protobuf==4.21.7
    - pydicom==2.2.2
    - scikit-image==0.19.3
    - scikit-learn==1.1.2
    - scipy==1.9.2
    - torchsummary==1.5.1
    - tqdm==4.62.3