README.md

---
license: agpl-3.0
tags:
- soccer
- video
- foul
- recognition
- classification
---
# ⚽ OpenSportsLib Classification Model (MViT - V2)

## 📌 Overview

This model is a **video-based classification model** built using the **OpenSportsLib**, designed for **soccer action classification**.

- **Task**: Action / Event Classification  
- **Architecture**: MViT (Multiscale Vision Transformer)   
- **Library**: OpenSportsLib  
- **Input**: Video clips  

---

## 📂 Dataset

### Training Dataset

This model is trained on the **SoccerNet – MVFouls (Classification subset)**:

👉 https://huggingface.co/datasets/OpenSportsLab/soccernetpro-classification-vars/tree/mvfouls/train

- **Domain**: Soccer video understanding  
- **Task**: Event classification  
- **Modality**: Video  

---

## 📊 Benchmark Results

| Metric        | Score |
|--------------|------|
| Accuracy      | 0.57 |
| Balanced Accuracy     | 0.4  |
| Top-2     | 0.78 |

---

## 🔧 Using with OpenSportsLib

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 the library

```python
import opensportslib
print("OpenSportsLib imported successfully")
```

### Run inference

```python
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)
```
---

## 📜 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.

__

## 📎 Citation
```
@misc{opensportslib_mvitv2_classification,
  title={OpenSportsLib Classification MViT V2},
  author={OpenSportsLab},
  year={2026},
  howpublished={https://huggingface.co/OpenSportsLab/oslib-MViTv2-classification}
}
```

---

## 🙏 Acknowledgements

- **Dataset**: SoccerNet / OpenSportsLab  
- **Library**: https://github.com/OpenSportsLab/opensportslib