| # YOLOv9-s for the Coral Edge TPU — corresponding source |
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| The two `.tflite` files under `objectDetection/yolov9/tflite/` are mirrored |
| UNCHANGED from Dan Brown's releases of |
| https://github.com/dbro/frigate-detector-edgetpu-yolo9 (repository commit |
| d8ddfdaee7af76bf3847274604a5ecff0d8c1cc4, mirrored 2026-10-22): |
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| | File | Release | SHA-256 | |
| | --- | --- | --- | |
| | yolov9-s-relu6-best_320_int8_edgetpu.tflite | v1.0 | 49a38e77439b475d0d259a6d9fe7ea32fcaa58de3748499dd120aceebad9c591 | |
| | yolov9-s-relu6-tpumax_512_int8_edgetpu.tflite | v1.5 | f634f60259101556825fd69662f96282e74364b507f83e6382cc34d5d0e6170e | |
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| Corresponding source, in this directory: |
|
|
| - `yolov9-s-relu6-best.pt` — the fine-tuned PyTorch checkpoint (release v1.0, |
| SHA-256 0005b3e03044acb007dbc1d6be2d1040b64ca98e5d2c30aaf5678f0935c6ebf9). |
| - `notebooks/Fine_tune_YOLOv9_s_for_EdgeTPU_use_ReLU6_and_17_COCO_classes.ipynb` |
| — the fine-tuning recipe (ReLU6 activations, 17 COCO classes). |
| - `notebooks/Convert_YOLO_v9_ReLU6_PyTorch_format_to_EdgeTPU_for_Google_Coral.ipynb` |
| — the PyTorch → int8 TFLite → edgetpu_compiler conversion. |
| - `labels-coco17.txt`, `README.md`, `LICENSE.md` — as published. |
| |
| Licences: |
| |
| - Weights: derived from WongKinYiu/yolov9 `yolov9-s-converted.pt`, |
| GPL-3.0 (https://github.com/WongKinYiu/yolov9). The training code is that |
| repository. |
| - Notebooks and plugin code: MIT, © 2025 Dan Brown (`LICENSE.md`). |
| - Training data: COCO 2017, filtered to 17 classes. |
| |
| CamStack does not modify these files; it decodes their output with its own |
| `yolo-split-dfl` postprocessor. |
| |
