environment.yml

name: doubletake
channels:
  - default
  - pytorch
  - conda-forge
  - nvidia
  - pytorch3d
dependencies:
  - clang=15.0.7
  - llvm-openmp=15.0.7
  - python=3.9.7
  - numpy=1.26.4
  - pytorch=2.0.1
  - torchvision
  - pytorch-cuda=11.7
  - cudatoolkit-dev=11.7  # nvcc
  - lightning=2.0.0
  - pytorch3d=0.7.4 # mesh rendering, https://github.com/facebookresearch/pytorch3d/issues/1679
  - pillow # image op
  - tensorboard # logging
  - matplotlib # plotting
  - gxx=8.5 # for JIT compiling
  - libxcrypt=4.4 # as above
  - pip
  - pip:
    - black==23.1.0
    - isort==5.12.0
    - kornia==0.6.7 # gradients
    - antialiased-cnns # anti aliased resnet
    - efficientnet_pytorch
    - timm # efficent
    - trimesh # mesh loading/storage, and mesh generation
    - transforms3d # for NeuralRecon's arkit
    - einops # batching one liners
    - moviepy # storing videos
    - pyrender==0.1.45 # rendering meshes
    - open3d==0.18.0 # mesh fusion
    - scipy==1.12.0 # transformations and a few others
    - protobuf<4.21.0 # lighting/tensorboard fix
    - setuptools==59.5.0 # fix for tensorboard
    - pytest==7.2.2
    - pytest-cov==2.7.1
    - pytest-timeout==2.1.0
    - pytest-fail-slow==0.3.0
    - loguru==0.7.2
    - https://github.com/JamieWatson683/scikit-image/archive/single_mesh.zip # single mesh exporting for measure.marching_cubes
    - opencv-python==4.9.0.80
    - ninja==1.11.1.1