Instructions to use PericlesRodrigues01/player-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use PericlesRodrigues01/player-detector with ultralytics:
from ultralytics import YOLOvv8 model = YOLOvv8.from_pretrained("PericlesRodrigues01/player-detector") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
⚽ Football & Sports Player Detection (YOLOv8)
This model is a fine-tuned version of YOLOv8 Nano, designed to detect players, balls, and sports equipment in match footage (Football/Tennis).
It was developed specifically to demonstrate Data Engineering techniques, achieving high generalization performance even when trained on a restricted dataset through the use of aggressive offline and online Data Augmentation strategies.
🏷️ Classes
The model is trained to detect the following 3 classes:
0: Person (Players)1: Ball (Football, Tennis ball)2: Equipment (Rackets)
💻 How to Use
To use this model in your Python project, you need the ultralytics and huggingface_hub libraries.
Installation
pip install ultralytics huggingface_hub
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