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LibreYOLO9E2Em

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

TipoOtherVersiónRevision 33f1715Ccalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
76,9–130 MB
Versión
vRevision 33f1715
Actualizado
14 oct 2026
Descargas
0
Fuente
Hugging Face

Descripción de la fuente

LibreYOLO9E2Em

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

Source

Backbone, neck and one-to-many head derived from MultimediaTechLab/YOLO (release v1.0-alpha, file v9-m.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 = 0.4797, mAP50 = 0.6420.

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.

Fuentes

1 fuente
Hugging FacePrincipalVersión 33f1715bb7b3eb6affa9bd4ad5f37b3d4c7ffaf3
huggingface.co/LibreYOLO/LibreYOLO9E2Em/tree/33f1715bb7b3eb6affa9bd4ad5f37b3d4c7ffaf3

Verificado 26 ago

Artefactos del modelo

2 artefactos

LibreYOLO9E2Em.onnx

onnx · 76,9 MB · SHA-256 63dab9ae7f14…05c6 · Hugging Face

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LibreYOLO9E2Em.pt

pt · 130 MB · SHA-256 9e59be1bc545…4827 · Hugging Face

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Extractos de fuentes

2 extractos

--- license: mit library_name: libreyolo tags: - object-detection - yolov9 - nms-free - end-to-end --- # LibreYOLO9E2Em YOLOv9 end-to-end (NMS-free) variant, size-m, 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-m.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 = 0.4797, mAP50 = 0.6420**. 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/LibreYOLO9E2Em