environment.yaml

name: deepspot2cell

channels:
  - pytorch
  - nvidia
  - conda-forge

dependencies:
  - python=3.10
  - pip

  # PyTorch — installed via conda for reliable CUDA integration.
  # GPU (CUDA 12.4):  keep all four lines below as-is
  # GPU (CUDA 11.8):  change pytorch-cuda=12.4 → pytorch-cuda=11.8
  # CPU-only:         remove the pytorch-cuda line entirely
  - pytorch>=2.2.0
  - torchvision>=0.17.0
  - torchaudio>=2.2.0
  - pytorch-cuda=12.4

  # Core scientific stack — conda builds link against system BLAS/LAPACK
  - numpy>=1.23.0
  - pandas>=1.5.0
  - scipy>=1.11.0
  - scikit-learn>=1.2.0
  - numba>=0.56.0
  - llvmlite>=0.39.0
  - h5py>=3.8.0
  - pyyaml>=6.0
  - matplotlib>=3.8.0
  - tqdm>=4.65.0

  # Spatial / single-cell biology
  - anndata>=0.8.0
  - scanpy>=1.9.0

  # Image processing — pyvips and shapely install more reliably via conda
  - pyvips>=2.2.1
  - shapely>=2.0

  - pip:
      # Everything else is pip-only or not on the pytorch/conda-forge channels.
      # torch/torchvision/torchaudio are NOT repeated here to avoid conflicts.
      - lightning>=2.2.0
      - torchmetrics>=1.3.0
      - squidpy>=1.2.0
      - hest>=0.2.0
      - timm>=0.9.12
      - transformers>=4.42.0
      - huggingface_hub>=0.23.0
      - einops>=0.7.0
      - opencv-python>=4.9.0
      - pillow>=10.0.0
      - plotnine>=0.12.0
      - psutil>=5.9.0