LibreMaskRCNN -- third-party attribution
========================================

Source: https://github.com/pytorch/vision
Commit: 336d36e8db990a905498c73933e35231876e28bc (torchvision v0.26.0)
License: BSD-3-Clause
Copyright (c) Soumith Chintala 2016

The mask-specific inference graph in nn.py is derived from torchvision's Mask
R-CNN mask RoI head, class-specific mask selection, and ResNet-50-FPN v2
builder. It extends LibreYOLO's separately attributed native Faster R-CNN
graph. LibreYOLO retains the upstream state-dict layout and adds its own
factory, checkpoint metadata, task dispatch, validation, class mapping,
postprocessing, and export/backend integration. Training-only matching,
sampling, and loss code is not included.

The official COCO checkpoint used for parity is not distributed in the
LibreYOLO source tree. Its separate LibreYOLO Hugging Face mirror uses
BSD-3-Clause on an explicitly disclosed implied basis: the checkpoint is
released by the BSD-licensed project but does not carry a per-object license
file. Torchvision warns that pretrained-model terms may derive from training
data and that users remain responsible for determining permission for their
use case. The mirror ships this BSD text and repeats that caveat; it must not
be described as an explicit checkpoint-specific grant.

BSD 3-Clause License

Copyright (c) Soumith Chintala 2016,

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