HABIT (Habitat Analysis: Biomedical Imaging Toolkit)
Copyright (c) 2024-2026 Li Chao, Dong Mengshi and HABIT Contributors.

This product is licensed under the Apache License, Version 2.0. A copy of the
license is included in the LICENSE file at the root of this distribution.

If you redistribute HABIT or a derivative work, Apache-2.0 section 4(d)
requires that you also carry a readable copy of the attribution notices below.

When HABIT is used in scientific work, the authors additionally request -- but
do not require as a condition of this license -- that you cite the project. See
CITATION.cff for citation metadata.

---------------------------------------------------------------------------
Third-party components incorporated into HABIT
---------------------------------------------------------------------------

The license texts below are reproduced so that MIT and BSD-2-Clause-Patent
obligations travel with every source and binary redistribution (git clone,
sdist, and wheel). HABIT modifications to these components remain under
Apache-2.0.

1. VMAF
   https://github.com/Netflix/vmaf
   Copyright (c) 2020 Netflix, Inc.
   Licensed under BSD-2-Clause-Patent

   The DeLong AUC comparison routines are adapted from this project in:

     - habit/kernels/statistics.py
     - habit/compat/engines/machine_learning/statistics/delong_test.py

   Full license text:

     LICENSE - BSD+Patent
     SPDX short identifier: BSD-2-Clause-Patent

     Note: This license is designed to provide: a) a simple permissive
     license; b) that is compatible with the GNU General Public License
     (GPL), version 2; and c) which also has an express patent grant
     included.

     Copyright (c) 2020 Netflix, Inc.

     Redistribution and use in source and binary forms, with or without
     modification, are permitted provided that the following conditions
     are met:

     1. Redistributions of source code must retain the above copyright
        notice, this list of conditions and the following disclaimer.

     2. Redistributions in binary form must reproduce the above copyright
        notice, this list of conditions and the following disclaimer in
        the documentation and/or other materials provided with the
        distribution.

     Subject to the terms and conditions of this license, each copyright
     holder and contributor hereby grants to those receiving rights under
     this license a perpetual, worldwide, non-exclusive, no-charge,
     royalty-free, irrevocable (except for failure to satisfy the
     conditions of this license) patent license to make, have made, use,
     offer to sell, sell, import, and otherwise transfer this software,
     where such license applies only to those patent claims, already
     acquired or hereafter acquired, licensable by such copyright holder
     or contributor that are necessarily infringed by:

     (a) their Contribution(s) (the licensed copyrights of copyright
         holders and non-copyrightable additions of contributors, in
         source or binary form) alone; or

     (b) combination of their Contribution(s) with the work of authorship
         to which such Contribution(s) was added by such copyright holder
         or contributor, if, at the time the Contribution is added, such
         addition causes such combination to be necessarily infringed.
         The patent license shall not apply to any other combinations
         which include the Contribution.

     Except as expressly stated above, no rights or licenses from any
     copyright holder or contributor is granted under this license,
     whether expressly, by implication, estoppel or otherwise.

     DISCLAIMER

     THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
     "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
     LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
     FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
     COPYRIGHT HOLDERS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT,
     INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
     (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
     SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
     HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
     STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
     ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED
     OF THE POSSIBILITY OF SUCH DAMAGE.

2. PyTorchRadiomics
   https://github.com/lyhyl/pytorchradiomics
   Copyright (c) 2024 lyhyl
   Licensed under the MIT License

   The GPU feature classes in habit/kernels/radiomics/torchradiomics/ are
   vendored from this project and adapted for HABIT. A copy of the MIT
   license also ships next to those modules as LICENSE.

   Full license text:

     MIT License

     Copyright (c) 2024 lyhyl

     Permission is hereby granted, free of charge, to any person obtaining
     a copy of this software and associated documentation files (the
     "Software"), to deal in the Software without restriction, including
     without limitation the rights to use, copy, modify, merge, publish,
     distribute, sublicense, and/or sell copies of the Software, and to
     permit persons to whom the Software is furnished to do so, subject
     to the following conditions:

     The above copyright notice and this permission notice shall be
     included in all copies or substantial portions of the Software.

     THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
     EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
     MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
     NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS
     BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN
     ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
     CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
     SOFTWARE.

---------------------------------------------------------------------------
Runtime dependencies
---------------------------------------------------------------------------

HABIT depends on third-party packages that are installed separately and remain
governed by their own licenses, including PyRadiomics, SimpleITK, ANTsPy,
scikit-learn, scikit-image, pandas, NumPy, SciPy, XGBoost, and pydicom. Those
licenses are not reproduced here; consult each package's own distribution.
