# SlicerNNUNet: run trained nnU-Net v2 segmentation models in 3D Slicer. Point it
# at a model folder (or a published model), pick the input volume(s), and the
# module runs nnUNetv2_predict in a separate process and loads the result as a
# segmentation.
#
# PURE-SCRIPTED: nothing to compile. Upstream pip-installs nnunetv2 and PyTorch
# (through the PyTorch extension); here they are RPMs (python3-nnunetv2,
# python3-torch). Patch0 makes the module use them.

%global commit      b1ee4304c5db948d3be4db022d25e87a9572de80
%global shortcommit %(c=%{commit}; echo ${c:0:8})
%global snapdate    20261002

%global slicer_inst   %{_prefix}/lib/slicer
%global slicer_subdir Slicer-5.12
%global qtsm          %{slicer_inst}/lib/%{slicer_subdir}/qt-scripted-modules

Name:           3dslicer-nnunet
Version:        0
Release:        0.1.%{snapdate}git%{shortcommit}%{?dist}
Summary:        nnU-Net v2 segmentation models in 3D Slicer (SlicerNNUNet)

License:        BSD-3-Clause
URL:            https://github.com/KitwareMedical/SlicerNNUnet
Source0:        %{url}/archive/%{commit}/SlicerNNUnet-%{shortcommit}.tar.gz
# - SegmentationLogic._findUNetPredictPath(): also find nnUNetv2_predict on PATH. It
#   only looked in <sys.executable>/../lib/Python/{Scripts,bin} (upstream's bundled
#   Python); the RPM's script is /usr/bin/nnUNetv2_predict, so every run failed with
#   "Failed to find nnUNet predict path."
# - InstallLogic.setupPythonRequirements(): when the installed python3-nnunetv2 does
#   not satisfy the requested version, say so with a dnf hint; never pip-install
#   nnunetv2 or PyTorch (a user-site copy would sit behind the system packages).
# - Process._report(): decode nnUNetv2_predict output with bytes.decode, not
#   qt.QTextCodec, which Qt6 removed: every output line and error was lost.
Patch0:         3dslicer-nnunet-fedora-packages.patch

BuildArch:      noarch

Requires:       3dslicer
Requires:       python3-nnunetv2
Requires:       python3-torch
Requires:       python3-packaging
# EXTENSION_DEPENDS PyTorch: InstallLogic imports PyTorchUtils.
Requires:       3dslicer-pytorch

%description
SlicerNNUNet runs trained nnU-Net v2 segmentation models in 3D Slicer: select
a model folder and the input volume(s), and the module runs nnUNetv2_predict
in a separate process and loads the result as a segmentation.

nnU-Net and PyTorch come from Fedora packages (python3-nnunetv2,
python3-torch). Fedora's PyTorch has no CUDA support, so NVIDIA GPUs are not
used; inference runs on the CPU, or on AMD GPUs through ROCm.

%prep
%autosetup -n SlicerNNUnet-%{commit} -p1

%build
# Pure-scripted: nothing to compile.

%install
# Install what SlicerNNUnet/CMakeLists.txt lists, at the paths
# slicerMacroBuildScriptedModule uses -- except Testing/*: the self tests need the
# SlicerPythonTestRunner extension (not packaged), and a top-level "Testing" package
# in the shared qt-scripted-modules directory would collide with other extensions.
_dir=SlicerNNUnet; _mod=SlicerNNUNet; _n=0
for _f in $(sed -n '/^set(MODULE_PYTHON_\(SCRIPTS\|RESOURCES\)$/,/^  )$/p' $_dir/CMakeLists.txt \
            | grep -vE '^set\(|^  \)$' | sed -e 's/^ *//' -e "s/\${MODULE_NAME}/$_mod/g" | grep -v '^Testing/'); do
    test -f "$_dir/$_f" || { echo "ERROR: $_mod lists $_f, which is missing" >&2; exit 1; }
    install -Dpm0644 "$_dir/$_f" "%{buildroot}%{qtsm}/$_f"
    _n=$((_n + 1))
done
test "$_n" -eq 11 || { echo "ERROR: installed $_n $_mod files, expected 11" >&2; exit 1; }

( cd %{buildroot} && find . \( -type f -o -type l \) | sed 's|^\.||' ) > %{_builddir}/nnunet.files

%files -f %{_builddir}/nnunet.files
%license LICENSE
%doc README.md

%changelog
* Sat Oct 10 2026 Morgan Hough <morgan.hough@gmail.com> - 0-0.1.20261002gitb1ee4304
- Initial package. SlicerNNUNet on python3-nnunetv2 / python3-torch (Patch0: find
  /usr/bin/nnUNetv2_predict; no pip install; nnU-Net output decoded without the
  Qt5-only QTextCodec).