β½ OpenSportsLib Localization Model (E2E)
π Overview
This model is a video-based localization model built using the OpenSportsLib, designed for soccer action localization.
- Task: Action Spotting / Localization
- Architecture: E2E
- Backend: Dali
- Library: OpenSportsLib
- Input: Video clips (224p)
π Dataset
Training Dataset
This model is trained on the SoccerNet β Ball Action Spotting 2025 (12 classes):
π https://huggingface.co/datasets/OpenSportsLab/soccernetpro-localization-snbas/tree/224p
- Domain: Soccer video understanding
- Task: Action Spotting
- Modality: Video
- Classes: [PASS, DRIVE, HEADER, HIGH PASS, OUT, CROSS, THROW IN, SHOT, BALL PLAYER BLOCK, PLAYER SUCCESSFUL TACKLE, FREE KICK, GOAL]
π Benchmark Results
| Metric | Score |
|---|---|
| tight mAP | 47.98 |
| loose mAP | 58.35 |
π§ Using with OpenSportsLib
For more details about OpenSportsLib visit the below link
π Github - https://github.com/OpenSportsLab/opensportslib
π PyPi - https://pypi.org/project/opensportslib/
π Documentations - https://opensportslab.github.io/opensportslib/
Import the library
import opensportslib
print("OpenSportsLib imported successfully")
Run inference
from opensportslib.apis import LocalizationModel
my_model = LocalizationModel(
config="/path/to/localization.yaml",
π weights="OpenSportsLab/OSL-loc-snbas-2025-e2e",
)
predictions = my_model.infer(
test_set="/path/to/test.json",
)
saved_predictions = my_model.save_predictions(
output_path="/path/to/predictions.json",
predictions=predictions,
)
metrics = my_model.evaluate(
test_set="/path/to/test.json",
predictions=saved_predictions,
)
print(metrics)
π License
Open source license: AGPL 3.0 for research, academic, and community use.
Commercial license: For proprietary or commercial deployment, please contact the project maintainers.
__
π Citation
@misc{opensportslib_e2e_localization_snbas_2025,
title={OpenSportsLib Localization E2E SNBAS 2025},
author={OpenSportsLab},
year={2026},
howpublished={https://huggingface.co/OpenSportsLab/oslib-e2e-localization-snbas-2025}
}
π Acknowledgements
- Dataset: SoccerNet / OpenSportsLab
- Library: https://github.com/OpenSportsLab/opensportslib
- Downloads last month
- 46
Inference Providers NEW
This model isn't deployed by any Inference Provider. π Ask for provider support