torch
torchvision
pytorch-lightning>=2.4.0
torchmetrics
segmentation-models-pytorch
hydra-core>=1.3.0
kornia
albumentations>=1.4.0
pandas
pyarrow
tensorboardX
pillow
matplotlib
scipy
numpy
pytorch_toolbelt==0.4.3
descartes==1.1.0
pyogrio>=0.7.2
psycopg2-binary
shapely>=2.0.0
geopandas>=1.1.0
geoalchemy2>=0.13.0
rasterio
sahi>=0.10.4
skan>=0.11.0
tqdm
rtree==1.0.0
bidict==0.21.2
Cython>=3.0.0
ninja>=1.11.0
pyyaml>=5.4
pycocotools
multiprocess==0.70.19
wget==3.2
fastapi>=0.100.0
uvicorn>=0.20.0
httpx>=0.23.0
pydantic-settings>=2.0.0
similaritymeasures==1.4.0
colorama==0.4.5
swifter==1.0.9
python-multipart==0.0.27
seaborn==0.13.2
scikit-learn>=1.3.2
scikit-image>=0.21.0
typing_extensions>=4.0.0

# ── Transformer / foundation-model support (optional) ──────────────────────
# These libraries are NOT installed by default to keep the base footprint small.
#
# Install all at once via the pip extras group:
#   pip install "pytorch_segmentation_models_trainer[transformers]"
#
# Or individually:
#   pip install transformers>=4.30.0  # HuggingFace models (Segformer, Mask2Former…)
#   pip install peft>=0.6.0           # LoRA / adapter fine-tuning
#   pip install timm>=0.9.0           # timm standalone encoder support
#
# TerraTorch (geospatial foundation models – Prithvi, Clay, SatMAE) is not yet
# on PyPI; install directly from source:
#   pip install terratorch
#
# Uncomment below only if you want these pinned in a requirements-based install:
# transformers>=4.30.0
# peft>=0.6.0
# timm>=0.9.0
# terratorch
