Initial upload: LibreDeepLabv3mv3-sem (DeepLabv3, BSD-3-Clause implied)

.gitattributes

@@ -1,35 +1 @@
-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
-*.bz2 filter=lfs diff=lfs merge=lfs -text
-*.ckpt filter=lfs diff=lfs merge=lfs -text
-*.ftz filter=lfs diff=lfs merge=lfs -text
-*.gz filter=lfs diff=lfs merge=lfs -text
-*.h5 filter=lfs diff=lfs merge=lfs -text
-*.joblib filter=lfs diff=lfs merge=lfs -text
-*.lfs.* filter=lfs diff=lfs merge=lfs -text
-*.mlmodel filter=lfs diff=lfs merge=lfs -text
-*.model filter=lfs diff=lfs merge=lfs -text
-*.msgpack filter=lfs diff=lfs merge=lfs -text
-*.npy filter=lfs diff=lfs merge=lfs -text
-*.npz filter=lfs diff=lfs merge=lfs -text
-*.onnx filter=lfs diff=lfs merge=lfs -text
-*.ot filter=lfs diff=lfs merge=lfs -text
-*.parquet filter=lfs diff=lfs merge=lfs -text
-*.pb filter=lfs diff=lfs merge=lfs -text
-*.pickle filter=lfs diff=lfs merge=lfs -text
-*.pkl filter=lfs diff=lfs merge=lfs -text
 *.pt filter=lfs diff=lfs merge=lfs -text
-*.pth filter=lfs diff=lfs merge=lfs -text
-*.rar filter=lfs diff=lfs merge=lfs -text
-*.safetensors filter=lfs diff=lfs merge=lfs -text
-saved_model/**/* filter=lfs diff=lfs merge=lfs -text
-*.tar.* filter=lfs diff=lfs merge=lfs -text
-*.tar filter=lfs diff=lfs merge=lfs -text
-*.tflite filter=lfs diff=lfs merge=lfs -text
-*.tgz filter=lfs diff=lfs merge=lfs -text
-*.wasm filter=lfs diff=lfs merge=lfs -text
-*.xz filter=lfs diff=lfs merge=lfs -text
-*.zip filter=lfs diff=lfs merge=lfs -text
-*.zst filter=lfs diff=lfs merge=lfs -text
-*tfevents* filter=lfs diff=lfs merge=lfs -text

LICENSE

@@ -0,0 +1,30 @@
+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.

LibreDeepLabv3mv3-sem.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fb83a67bca845817d816d139af6fb6a4b9d809c0a813ebcfcb1e2a5fbd222682
+size 44325189

NOTICE

@@ -0,0 +1,17 @@
+LibreDeepLabv3mv3-sem weights
+-----------------------------
+
+This product contains weights released by torchvision
+(https://github.com/pytorch/vision) at commit 336d36e8db990a905498c73933e35231876e28bc.
+Official checkpoint: deeplabv3_mobilenet_v3_large-fc3c493d.pth
+Copyright (c) Soumith Chintala 2016 and 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. COCO annotations are
+CC BY 4.0 and source images retain their individual Flickr terms.
+
+Conversion removes only the training-time auxiliary classifier and adds
+LibreYOLO metadata. Every retained learned tensor is unchanged.

README.md

@@ -0,0 +1,78 @@
+---
+license: bsd-3-clause
+library_name: libreyolo
+pipeline_tag: image-segmentation
+datasets:
+  - detection-datasets/coco
+tags:
+  - semantic-segmentation
+  - deeplabv3
+  - torchvision
+  - pascal-voc
+  - libreyolo
+---
+
+# LibreDeepLabv3mv3-sem
+
+DeepLabv3 semantic segmentation with dilated MobileNetV3-Large, output stride 16, repackaged for
+LibreYOLO. It predicts background plus 20 Pascal VOC-named foreground classes
+from a checkpoint trained on the matching COCO subset. This is DeepLabv3, not
+DeepLabv3+; there is no decoder or CRF.
+
+```python
+from libreyolo import LibreYOLO
+
+model = LibreYOLO("LibreDeepLabv3mv3-sem.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)
+(torchvision v0.26.0). Copyright (c) Soumith Chintala 2016 and torchvision
+contributors. The source implementation is BSD-3-Clause.
+
+Official checkpoint: [deeplabv3_mobilenet_v3_large-fc3c493d.pth](https://download.pytorch.org/models/deeplabv3_mobilenet_v3_large-fc3c493d.pth)  
+Bytes: `44356159`  
+SHA-256: `fc3c493d68e89cc31ef488c803d5d7dd2f3190fb570598faa49fef69be8e5e70`  
+Published mIoU / pixel accuracy: 60.3 / 91.2.
+
+The published metrics use torchvision's aspect-preserving evaluation preset.
+LibreYOLO uses a fixed 520x520 stretch deployment contract, followed by
+ImageNet normalization and restoration of the output mask to the source
+canvas, so end-to-end metrics can differ.
+
+## Modifications and verification
+
+Conversion removes only the training-time `aux_classifier.*` tensors and adds
+LibreYOLO v1.0 checkpoint metadata. Every retained runtime tensor and state-dict
+key is unchanged. The native 520x520 logits are bit-exact against the pinned
+torchvision implementation before postprocessing (`max_abs_diff == 0.0`).
+
+The fixed-shape deployment graph was also tested through LibreYOLO's unified
+backend:
+
+- ONNX Runtime CPU: 100% identical public mask pixels; maximum logit difference
+  `3.06e-5`.
+- TorchScript: bit-exact logits and 100% identical public mask pixels.
+- OpenVINO CPU: 99.9876% identical public mask pixels using
+  the runtime's default reduced-precision execution hint.
+- TensorRT 10.16 FP32 on RTX 5070 Ti: 99.9851% identical public
+  mask pixels.
+
+The converted file has `44325189` bytes and SHA-256
+`fb83a67bca845817d816d139af6fb6a4b9d809c0a813ebcfcb1e2a5fbd222682`. See `docs/provenance/deeplabv3.md` and
+`weights/convert_deeplabv3_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 licenses or terms derived from training data and that users
+must determine whether they have permission for their use case. COCO
+annotations are CC BY 4.0; source images retain their individual Flickr terms.
+See [`LICENSE`](./LICENSE) and [`NOTICE`](./NOTICE).