| # 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 | |