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yolov8n.pt)1.0), left-right flips (0.5), scaling (0.5), translation (0.1).args.yaml:lr0): 0.01lrf): 0.01
pip install ultralytics torch torchvision1from ultralytics import YOLO
2
3model = YOLO("weights/best.pt")
4results = model("football.jpg")
5results[0].show()yolo task=detect mode=predict model=weights/best.pt source=football.jpg1.
2├── weights/
3│ ├── best.pt
4│ └── last.pt
5├── args.yaml
6├── results.csv
7├── results.png
8├── confusion_matrix.png
9├── confusion_matrix_normalized.png
10├── BoxPR_curve.png
11├── BoxP_curve.png
12├── BoxR_curve.png
13├── BoxF1_curve.png
14├── labels.jpg
15├── val_batch0_pred.jpg
16├── val_batch1_pred.jpg
17└── val_batch2_pred.jpg