Initial upload: LibreFCNr50 (FCN, BSD-3-Clause implied)

LICENSE

@@ -0,0 +1,29 @@
+BSD 3-Clause License
+
+Copyright (c) Soumith Chintala 2016, 
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+* Redistributions of source code must retain the above copyright notice, this
+  list of conditions and the following disclaimer.
+
+* 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.
+
+* Neither the name of the copyright holder nor the names of its
+  contributors may be used to endorse or promote products derived from
+  this software without specific prior written permission.
+
+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 HOLDER 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.

LibreFCNr50.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7c6b1ae664198b2f7228ed9b7f52fd14034771bc239d52c768a1494d1577c882
+size 141620335

NOTICE

@@ -0,0 +1,15 @@
+LibreFCNr50 weights
+-------------------
+
+This product contains weights released by torchvision
+(https://github.com/pytorch/vision) at commit 336d36e8db990a905498c73933e35231876e28bc.
+Official checkpoint: fcn_resnet50_coco-1167a1af.pth
+Copyright (c) Soumith Chintala 2016 and the torchvision contributors.
+
+The checkpoint has no separate per-object license file. Redistribution uses
+the releasing project's BSD-3-Clause license on an explicitly disclosed
+implied basis; this is not a publisher-confirmed checkpoint-specific grant.
+Torchvision warns that pretrained-model terms may derive from training data
+and users must determine permission for their use case.
+
+Conversion only adds LibreYOLO metadata. Learned tensors are unchanged.

README.md

@@ -0,0 +1,63 @@
+---
+license: bsd-3-clause
+library_name: libreyolo
+pipeline_tag: image-segmentation
+datasets:
+  - detection-datasets/coco
+tags:
+  - semantic-segmentation
+  - fcn
+  - torchvision
+  - libreyolo
+---
+
+# LibreFCNr50
+
+Torchvision FCN with a dilated ResNet-50 backbone, repackaged for LibreYOLO.
+The 2015 FCN work established end-to-end pixels-to-pixels prediction, but this
+checkpoint uses torchvision's later ResNet graph. It is **not** the original
+paper's VGG-based FCN-8s skip-fusion architecture.
+
+```python
+from libreyolo import LibreYOLO
+
+model = LibreYOLO("LibreFCNr50.pt")
+result = model.predict("image.jpg")
+mask = result.semantic_mask.data
+```
+
+## Source
+
+Derived from [pytorch/vision](https://github.com/pytorch/vision) at commit
+[`336d36e8db990a905498c73933e35231876e28bc`](https://github.com/pytorch/vision/commit/336d36e8db990a905498c73933e35231876e28bc).
+Copyright (c) Soumith Chintala 2016 and the torchvision contributors. The
+source implementation is BSD-3-Clause.
+
+Official checkpoint: [fcn_resnet50_coco-1167a1af.pth](https://download.pytorch.org/models/fcn_resnet50_coco-1167a1af.pth)
+Official checkpoint bytes: 141,567,418
+SHA-256: `1167a1affa42e1e62858f8d3fac12d109e0108327ffc91c5855a324b11683c36`
+
+Torchvision reports COCO-val2017-VOC-labels mIoU 60.5 and pixel
+accuracy 91.4.
+
+## Categories
+
+The 21 output channels are `__background__`, `aeroplane`, `bicycle`, `bird`, `boat`, `bottle`, `bus`, `car`, `cat`, `chair`, `cow`, `diningtable`, `dog`, `horse`, `motorbike`, `person`, `pottedplant`, `sheep`, `sofa`, `train`, `tvmonitor`.
+
+## Modifications
+
+Checkpoint metadata was added for LibreYOLO's v1.0 schema. Learned tensors and
+state-dict keys are unchanged, including the primary and auxiliary heads. The
+native LibreYOLO graph strict-loads the official state dict and both dense-logit
+outputs are bit-exact against torchvision. See
+`weights/convert_fcn_weights.py` in the
+[LibreYOLO source repository](https://github.com/LibreYOLO/libreyolo).
+
+## License
+
+The checkpoint publisher did not attach a separate per-object license file.
+This mirror applies the releasing project's BSD-3-Clause license on an
+**implied**, not publisher-confirmed, basis. Torchvision warns that pretrained
+models may have their own licenses or terms derived from training data and
+that users must determine whether they have permission for their use case.
+See [`LICENSE`](./LICENSE) and [`NOTICE`](./NOTICE).