# Pinned Python stack for regenerating the int_hyper integer-codec vectors (the
# pretrained mbt2018_mean, exported to integers; tools/wai_sota_vectors.sh). The vectors are regenerated rather than committed,
# so the export must run against a fixed stack: an upgrade that changes the
# pretrained weights or the float analysis transform must arrive as a reviewed
# change here, not silently on the next CI run.
#
# torch/torchvision: install from the CPU wheel index first on Linux, or pip
# resolves the GPU builds (several GB). `==2.14.0` matches `2.14.0+cpu`.
#   pip install torch==2.14.0 torchvision==0.29.0 --index-url https://download.pytorch.org/whl/cpu
#   pip install -r tools/requirements-sota-int.txt
torch==2.14.0
torchvision==0.29.0
# BSD-3-Clause-Clear. Supplies the mbt2018_mean architecture and the URL of its
# published checkpoint, mbt2018-mean-6-a19628ab.pth.tar. The checkpoint is NOT
# verified by compressai or torch.hub (the zoo calls torch.hub without
# check_hash), so wai_sota_int_synth_export.py pins its full SHA-256 and refuses
# to load any other bytes.
compressai==1.2.8
# compressai 1.2.8 requires numpy<2.
numpy==1.26.4
pillow==12.3.0
# Source image only: `skimage.data.astronaut()` ships inside the wheel and is a
# NASA photograph documented there as "No known copyright restrictions, released
# into the public domain" (the function's docstring).
scikit-image==0.26.0