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LibreYOLO9E2Ec

YOLOv9 end-to-end (NMS-free) variant, size-c, for LibreYOLO.

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Other
File size
97.4–161 MB
Version
vRevision fd006fb
Updated
Oct 12, 2026
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0
Source
Hugging Face

Source description

LibreYOLO9E2Ec

YOLOv9 end-to-end (NMS-free) variant, size-c, for LibreYOLO.

Source

Backbone, neck and one-to-many head derived from MultimediaTechLab/YOLO (release v1.0-alpha, file v9-c.pt). Copyright (c) 2024 Kin-Yiu Wong and Hao-Tang Tsui. Licensed under the MIT License.

Modifications

Backbone, neck and one-to-many head: state-dict key remapping only; learned parameters unchanged from upstream.

One-to-one head (head.one2one_cv2, head.one2one_cv3): trained from scratch on COCO 2017 with the rest of the network frozen.

mAP (COCO val2017, COCOeval): mAP50-95 = 0.4944, mAP50 = 0.6603.

See LibreYOLO issue #84 and PR #156 for the recipe.

License

MIT License. See the LICENSE file in this repository.

Acknowledgements

The YOLOv9-E2E architecture (NMS-free one-to-one head added to YOLOv9) and the frozen-backbone fine-tuning recipe used to train the released weights are the work of testdummyvt . first proposed in LibreYOLO issue #84 and contributed via PR #156.

Sources

1 source
Hugging FacePrimaryVersion fd006fb169296cf29a0272a447b0c1534922d983
huggingface.co/LibreYOLO/LibreYOLO9E2Ec/tree/fd006fb169296cf29a0272a447b0c1534922d983

Verified Aug 26

Model artifacts

2 artifacts

LibreYOLO9E2Ec.onnx

onnx · 97.4 MB · SHA-256 fee82515d9c5…57a5 · Hugging Face

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LibreYOLO9E2Ec.pt

pt · 161 MB · SHA-256 1458324eeb5a…8fdd · Hugging Face

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Source excerpts

2 excerpts

--- license: mit library_name: libreyolo tags: - object-detection - yolov9 - nms-free - end-to-end --- # LibreYOLO9E2Ec YOLOv9 end-to-end (NMS-free) variant, size-c, for LibreYOLO. ## Source Backbone, neck and one-to-many head derived from [MultimediaTechLab/YOLO](https://github.com/MultimediaTechLab/YOLO) (release v1.0-alpha, file `v9-c.pt`). Copyright (c) 2024 Kin-Yiu Wong and Hao-Tang Tsui. Licensed under the MIT License. ## Modifications Backbone, neck and one-to-many head: state-dict key remapping only; learned parameters unchanged from upstream. One-to-one head (`head.one2one_cv2`, `head.one2one_cv3`): trained from scratch on COCO 2017 with the rest of the network frozen. mAP (COCO val2017, COCOeval): **mAP50-95 = 0.4944, mAP50 = 0.6603**. See [LibreYOLO issue #84](https://github.com/LibreYOLO/libreyolo/issues/84) and [PR #156](https://github.com/LibreYOLO/libreyolo/pull/156) for the recipe. ## License MIT License. See the [`LICENSE`](./LICENSE) file in this repository. ## Acknowledgements The YOLOv9-E2E architecture (NMS-free one-to-one head added to YOLOv9) and the frozen-backbone fine-tuning recipe used to train the released weights are the work of [testdummyvt](https://github.com/testdummyvt) . first proposed in [LibreYOLO issue #84](https://github.com/LibreYOLO/libreyolo/issues/84) and contributed via [PR #156](https://github.com/LibreYOLO/libreyolo/pull/156).

Source context: 0 downloads · 0 likes · Pipeline object-detection · Library libreyolo · Repo LibreYOLO/LibreYOLO9E2Ec