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- from ultralytics import YOLO
- # Load a pretrained YOLO11n model
- model = YOLO("yolo11s.pt")
- # Train the model on the COCO8 dataset for 100 epochs
- train_results = model.train(
- data="coco8.yaml", # Path to dataset configuration file
- epochs=100, # Number of training epochs
- imgsz=640, # Image size for training
- device="cuda", # Device to run on (e.g., 'cpu', 0, [0,1,2,3])
- )
- # Evaluate the model's performance on the validation set
- metrics = model.val()
- # Perform object detection on an image
- results = model("../resources/first_frame.png") # Predict on an image
- results[0].show() # Display results
- # Export the model to ONNX format for deployment
- # path = model.export(format="onnx") # Returns the path to the exported model
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