LibreYOLO9E2Em
YOLOv9 end-to-end (NMS-free) variant, size-m, for LibreYOLO.
Fonte do modelo
- Tipo
- Other
- Tamanho do arquivo
- 76,9–130 MB
- Versão
- vRevision 33f1715
- Atualizado
- 14 de out. de 2026
- Downloads
- 0
- Fonte
- Hugging Face
Descrição da fonte
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.
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Artefatos de modelo
2 artefatos
Artefatos de modelo
2 artefatosTrechos de fonte
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Trechos de fonte
2 trechos--- 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
