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OpenSportsLab/OSL-cls-action-mvitv2
OSL-cls-action-mvitv2 is a machine learning model from OpenSportsLab. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as agpl-3.0.
This model is a video-based classification model built using the OpenSportsLib, designed for soccer action classification.
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From the Hugging Face model README
This model is a video-based classification model built using the OpenSportsLib, designed for soccer action classification.
This model is trained on the SoccerNet – MVFouls (Classification subset):
👉 https://huggingface.co/datasets/OpenSportsLab/soccernetpro-classification-vars/tree/mvfouls/train
| Metric | Score |
|---|---|
| Accuracy | 0.57 |
| Balanced Accuracy | 0.4 |
| Top-2 | 0.78 |
For more details about OpenSportsLib visit the below link
👉 Github - https://github.com/OpenSportsLab/opensportslib
👉 PyPi - https://pypi.org/project/opensportslib/
👉 Documentations - https://opensportslab.github.io/opensportslib/
import opensportslib
print("OpenSportsLib imported successfully")
from opensportslib.apis import ClassificationModel
my_model = ClassificationModel(
config="/path/to/classification.yaml",
👉 weights="OpenSportsLab/OSL-cls-action-mvitv2",
)
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)
Open source license: AGPL 3.0 for research, academic, and community use.
Commercial license: For proprietary or commercial deployment, please contact the project maintainers.
__
@misc{opensportslib_mvitv2_classification,
title={OpenSportsLib Classification MViT V2},
author={OpenSportsLab},
year={2026},
howpublished={https://huggingface.co/OpenSportsLab/oslib-MViTv2-classification}
}