Third-party model notice: YOLOv9-s EdgeTPU (GPL-3.0)

THIRD_PARTY_MODELS.md

@@ -32,6 +32,7 @@ under [Non-commercial models](#non-commercial-models).
 
 - © Ultralytics, AGPL-3.0. Corresponding source: the upstream Ultralytics checkpoint and build-camstack-models.py (with convert_lib.py) published at https://huggingface.co/camstack/camstack-models/tree/main/source. https://github.com/ultralytics/ultralytics
 - Coral Edge TPU models and AIY Vision Birds V1 © Google LLC, Apache-2.0. https://github.com/google-coral/test_data
+- YOLOv9-s EdgeTPU weights © 2025 Dan Brown (fine-tuned to 17 COCO classes, INT8, compiled for the Edge TPU; https://github.com/dbro/frigate-detector-edgetpu-yolo9, repository MIT). Derived from the YOLOv9 code and yolov9-s checkpoint of Chien-Yao Wang, I-Hau Yeh, Hong-Yuan Mark Liao, GPL-3.0 (https://github.com/WongKinYiu/yolov9). Corresponding source: the fine-tuning checkpoint (yolov9-s-relu6-best.pt), the fine-tuning and conversion notebooks and the publisher LICENSE, mirrored at https://huggingface.co/camstack/camstack-models/tree/main/source/yolov9-edgetpu-dbro. https://github.com/dbro/frigate-detector-edgetpu-yolo9
 - © Ultralytics, AGPL-3.0 (Ultralytics YOLOv9 weights). YOLOv9 architecture: Chien-Yao Wang, I-Hau Yeh, Hong-Yuan Mark Liao, GPL-3.0 (https://github.com/WongKinYiu/yolov9). Corresponding source: the upstream Ultralytics checkpoint and build-camstack-models.py (with convert_lib.py) published at https://huggingface.co/camstack/camstack-models/tree/main/source. https://github.com/ultralytics/ultralytics
 - RF-DETR © Roboflow, Apache-2.0. https://github.com/roboflow/rf-detr
 - YuNet weights Copyright (c) 2020 Shiqi Yu, MIT. Training code: ShiqiYu/libfacedetection.train, BSD-3-Clause. https://github.com/opencv/opencv_zoo/tree/main/models/face_detection_yunet
@@ -48,7 +49,7 @@ under [Non-commercial models](#non-commercial-models).
 
 Training data under attribution terms:
 
-- **COCO 2017** (training data of `yolo26n` and 50 more): annotations CC-BY-4.0; images under their Flickr owners' terms. https://cocodataset.org/#termsofuse
+- **COCO 2017** (training data of `yolo26n-seg` and 52 more): annotations CC-BY-4.0; images under their Flickr owners' terms. https://cocodataset.org/#termsofuse
 - **WIDER FACE** (training data of `yunet-2023mar`): research-oriented terms; images CC BY-NC-ND. http://shuoyang1213.me/WIDERFACE/
 - **Open Images V7** (training data of `animal-classifier`): annotations CC-BY-4.0 (Google LLC); images listed as CC-BY-2.0, no warranty. https://storage.googleapis.com/openimages/web/factsfigures_v7.html
 - **DrBimmer/vehicle-classification** (training data of `vehicle-type-v1`): CC-BY-NC-4.0 — treated as binding the trained weights (conservative reading). https://huggingface.co/datasets/DrBimmer/vehicle-classification
@@ -62,7 +63,7 @@ Training data under attribution terms:
   cards link here instead of repeating it.
 -->
 
-The folders `objectDetection/yolo26`, `objectDetection/yolov9` and `segmentation/yolo26-seg` of the model mirror hold Ultralytics weights,
+The folders `segmentation/yolo26-seg`, `objectDetection/yolo26` and `objectDetection/yolov9` of the model mirror hold Ultralytics weights,
 modified by CamStack and distributed under AGPL-3.0. Their Corresponding Source
 is published in the mirror itself, in its **`source/`** folder,
 **https://huggingface.co/camstack/camstack-models/tree/main/source**, together
@@ -120,8 +121,10 @@ entry kept resolvable for a saved selection but no longer offered.
 
 | Catalog ids | Upstream | Code / weights | Training data | CamStack changes | Downloaded from |
 | --- | --- | --- | --- | --- | --- |
+| `yolo26n-seg`, `yolo26s-seg`, `yolo26m-seg` | [Ultralytics](https://github.com/ultralytics/ultralytics) | AGPL-3.0 / AGPL-3.0 (`AGPL-3.0.txt`) | COCO 2017: annotations CC-BY-4.0; images under their Flickr owners' terms | exported to ONNX, OpenVINO IR and CoreML | mirror `segmentation/yolo26-seg` |
 | `yolo26n` (default), `yolo26s`, `yolo26m`, `yolo26l`, `yolo26x` (hidden), `yolo26n-fp16` (hidden), `yolo26n-int8`, `yolo26s-fp16` (hidden), `yolo26s-int8`, `yolo26m-fp16` (hidden), `yolo26m-int8`, `yolo26l-fp16` (hidden), `yolo26l-int8`, `yolo26n-320`, `yolo26n-320-int8`, `yolo26n-256`, `yolo26n-256-int8`, `yolo26s-320`, `yolo26s-320-int8`, `yolo26s-256`, `yolo26s-256-int8`, `yolo26m-320`, `yolo26m-320-int8`, `yolo26m-256`, `yolo26m-256-int8`, `yolo26l-320`, `yolo26l-320-int8`, `yolo26l-256`, `yolo26l-256-int8`, `yolo26x-fp16` (hidden), `yolo26x-int8` (hidden) | [Ultralytics](https://github.com/ultralytics/ultralytics) | AGPL-3.0 / AGPL-3.0 (`AGPL-3.0.txt`) | COCO 2017: annotations CC-BY-4.0; images under their Flickr owners' terms | exported to ONNX, OpenVINO IR and CoreML (scripts/build-camstack-models.py); OpenVINO FP16 export; exported to OpenVINO IR, then OpenVINO NNCF INT8 post-training quantisation; re-exported at 320×320 to ONNX, OpenVINO IR and CoreML; re-exported at 320×320 to OpenVINO IR; OpenVINO NNCF INT8 post-training quantisation; re-exported at 256×256 to ONNX, OpenVINO IR and CoreML; re-exported at 256×256 to OpenVINO IR; OpenVINO NNCF INT8 post-training quantisation | mirror `objectDetection/yolo26` |
 | `ssd-mobilenet-v2-coco-edgetpu` (default) | [Google Coral test_data](https://github.com/google-coral/test_data) | Apache-2.0 / Apache-2.0 (`Apache-2.0.txt`) | COCO 2017: annotations CC-BY-4.0; images under their Flickr owners' terms | none | https://github.com/google-coral/test_data |
+| `yolov9s-320-edgetpu`, `yolov9s-512-edgetpu` | [YOLOv9-s EdgeTPU (Dan Brown)](https://github.com/dbro/frigate-detector-edgetpu-yolo9) | GPL-3.0 / GPL-3.0 (`GPL-3.0.txt`) | COCO 2017: annotations CC-BY-4.0; images under their Flickr owners' terms | none: the publisher release files are mirrored byte-identical | mirror `objectDetection/yolov9` |
 | `yolov9t-320`, `yolov9t-320-int8`, `yolov9t-640`, `yolov9t-640-int8`, `yolov9s-320`, `yolov9s-320-int8`, `yolov9s-640`, `yolov9s-640-int8`, `yolov9m-320`, `yolov9m-320-int8`, `yolov9m-640`, `yolov9m-640-int8`, `yolov9c-320`, `yolov9c-320-int8`, `yolov9c-640`, `yolov9c-640-int8` | [Ultralytics](https://github.com/ultralytics/ultralytics) | AGPL-3.0 / AGPL-3.0 (`AGPL-3.0.txt`) | COCO 2017: annotations CC-BY-4.0; images under their Flickr owners' terms | exported at 320×320 to ONNX, OpenVINO IR FP16 and CoreML; exported at 320×320 to OpenVINO IR; OpenVINO NNCF INT8 post-training quantisation; exported at 640×640 to ONNX, OpenVINO IR FP16 and CoreML; exported at 640×640 to OpenVINO IR; OpenVINO NNCF INT8 post-training quantisation | mirror `objectDetection/yolov9` |
 
 ### Package detection
@@ -134,7 +137,7 @@ entry kept resolvable for a saved selection but no longer offered.
 
 | Catalog ids | Upstream | Code / weights | Training data | CamStack changes | Downloaded from |
 | --- | --- | --- | --- | --- | --- |
-| `yunet-2023mar` (default) | [OpenCV Zoo YuNet](https://github.com/opencv/opencv_zoo/tree/main/models/face_detection_yunet) | BSD-3-Clause (`BSD-3-Clause.txt`) / MIT (`MIT-yunet-reference.txt`) | WIDER FACE: research-oriented terms; images CC BY-NC-ND | input contract baked into the graph (the pool RGB /255 becomes the upstream BGR 0..255: Mul(255) plus a channel Gather); internal tensor names cleared in the OpenVINO IR; ONNX fp32, OpenVINO IR fp32, CoreML fp16 (scripts/build-yunet-model.py) | mirror `faceDetection/yunet` |
+| `yunet-2023mar` (default) | [OpenCV Zoo YuNet](https://github.com/opencv/opencv_zoo/tree/main/models/face_detection_yunet) | BSD-3-Clause (`BSD-3-Clause.txt`) / MIT (`MIT-yunet-reference.txt`) | WIDER FACE: research-oriented terms; images CC BY-NC-ND | input contract baked into the graph (the pool RGB /255 becomes the upstream BGR 0..255: Mul(255) plus a channel Gather); internal tensor names cleared in the OpenVINO IR; ONNX fp32, OpenVINO IR fp32, CoreML fp16 (scripts/build-yunet-model.py); Edge TPU build: the bake folded into the first Conv, full-integer int8 post-training quantisation calibrated on CamStack person crops, compiled with edgetpu_compiler 14 (scripts/build-yunet-edgetpu.py) | mirror `faceDetection/yunet` |
 
 ### Face recognition
 
@@ -146,7 +149,7 @@ entry kept resolvable for a saved selection but no longer offered.
 
 | Catalog ids | Upstream | Code / weights | Training data | CamStack changes | Downloaded from |
 | --- | --- | --- | --- | --- | --- |
-| `yolox-tiny-plate` (default) | [open-lpr models (faisalthaheem/open-lpr-models), YOLOX-tiny](https://huggingface.co/faisalthaheem/open-lpr-models) | Apache-2.0 / Apache-2.0 (`Apache-2.0.txt`) | Simanno annotated plate corpus plus community-contributed photographs, pseudo-labelled by a teacher model (not published; the upstream NOTICE says the photographs were uploaded without consent obtained): UNKNOWN | input contract baked into the graph (static 1x3x640x640 RGB /255 becomes the upstream BGR 0..255: Mul(255) plus a channel Gather) and the output reshaped to the YOLOv8 layout (cx, cy, w, h, obj*cls); ONNX fp32, OpenVINO IR fp16, CoreML fp16 (scripts/build-yolox-plate-model.py) | mirror `plateDetection/yolox-tiny-plate` |
+| `yolox-tiny-plate` (default) | [open-lpr models (faisalthaheem/open-lpr-models), YOLOX-tiny](https://huggingface.co/faisalthaheem/open-lpr-models) | Apache-2.0 / Apache-2.0 (`Apache-2.0.txt`) | Simanno annotated plate corpus plus community-contributed photographs, pseudo-labelled by a teacher model (not published; the upstream NOTICE says the photographs were uploaded without consent obtained): UNKNOWN | input contract baked into the graph (static 1x3x640x640 RGB /255 becomes the upstream BGR 0..255: Mul(255) plus a channel Gather) and the output reshaped to the YOLOv8 layout (cx, cy, w, h, obj*cls); ONNX fp32, OpenVINO IR fp16, CoreML fp16 (scripts/build-yolox-plate-model.py); Edge TPU build: the Focus stem rewritten as the equivalent 6x6 stride-2 Conv with the input bake folded into it, the graph cut before the grid decode (raw per-stride head), full-integer int8 post-training quantisation calibrated on CamStack vehicle crops, compiled with edgetpu_compiler 14 (scripts/build-yolox-plate-edgetpu.py) | mirror `plateDetection/yolox-tiny-plate` |
 
 ### Licence plate reading
 
@@ -164,7 +167,7 @@ entry kept resolvable for a saved selection but no longer offered.
 
 | Catalog ids | Upstream | Code / weights | Training data | CamStack changes | Downloaded from |
 | --- | --- | --- | --- | --- | --- |
-| `bird-classifier` (default) | [Google AIY Vision birds_V1](https://github.com/google-coral/test_data) | — / Apache-2.0 (`Apache-2.0.txt`) | — | converted from TensorFlow with tf2onnx; OpenVINO IR and CoreML derived from it | mirror `animalClassification/bird-classifier` |
+| `bird-classifier` (default) | [Google AIY Vision birds_V1](https://github.com/google-coral/test_data) | — / Apache-2.0 (`Apache-2.0.txt`) | — | converted from TensorFlow with tf2onnx; OpenVINO IR and CoreML derived from it; the Edge TPU build is the Google full-integer quantised TFLite of the same model, compiled with edgetpu_compiler 14 (scripts/build-bird-classifier-edgetpu.py) | mirror `animalClassification/bird-classifier` |
 
 ### Vehicle classifier
 
@@ -190,12 +193,6 @@ entry kept resolvable for a saved selection but no longer offered.
 | --- | --- | --- | --- | --- | --- |
 | `u2netp` (default) | [xuebinqin/U-2-Net](https://github.com/xuebinqin/U-2-Net) | Apache-2.0 / Apache-2.0 (`Apache-2.0.txt`) | DUTS-TR: not checked | converted to ONNX, OpenVINO IR and CoreML | mirror `segmentationRefiner/u2netp` |
 
-### Instance segmentation (dormant step)
-
-| Catalog ids | Upstream | Code / weights | Training data | CamStack changes | Downloaded from |
-| --- | --- | --- | --- | --- | --- |
-| `yolo26n-seg`, `yolo26s-seg`, `yolo26m-seg` | [Ultralytics](https://github.com/ultralytics/ultralytics) | AGPL-3.0 / AGPL-3.0 (`AGPL-3.0.txt`) | COCO 2017: annotations CC-BY-4.0; images under their Flickr owners' terms | exported to ONNX, OpenVINO IR and CoreML | mirror `segmentation/yolo26-seg` |
-
 ### Audio
 
 | Catalog ids | Upstream | Code / weights | Training data | CamStack changes | Downloaded from |