# Main framework env: SMP / Attention-UNet / TransUNet / Swin-Unet + SegGuidedDiff
# Modern stack (matches detected host: CUDA 12.8). bf16 on A100, fp16 on V100.
name: seggen
channels: [conda-forge]
dependencies:
  - python=3.11
  - pip
  - pip:
      # install torch matching your CUDA (host has cu128):
      #   pip install torch torchvision --index-url https://download.pytorch.org/whl/cu128
      - segmentation-models-pytorch
      - albumentations==2.0.8        # pin: avoids AGPL AlbumentationsX on -U
      - monai                        # transforms + HD95 metric
      - medpy                        # HD95 fallback
      - opencv-python-headless
      - numpy
      - pyyaml
      - timm
      - einops
      - ml-collections               # required by TransUNet config
      - tqdm
      # SegGuidedDiff (runs in this env too — modern deps):
      - diffusers==0.21.4
      - datasets==2.14.5