BBIT-Kai
34 lines
858 B
Python
34 lines
858 B
Python
from ultralytics import YOLO
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import os
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# 设置工作目录为你的项目路径
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os.chdir("/home/bbit/mine/yolo/")
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# Load a pretrained YOLO11n model
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model = YOLO("models/yolo11x.pt")
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# Train the model on the COCO8 dataset for 100 epochs
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train_results = model.train(
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data="SilkwormCocoonDataset/data.yaml",
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epochs=100,
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imgsz=768,
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batch=8,
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device="cuda:0",
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amp=True,
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half=True,
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optimizer="auto",
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warmup_epochs=3,
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mosaic=1.0,
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mixup=0.1
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)
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# Evaluate the model's performance on the validation set
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metrics = model.val()
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# # Perform object detection on an image
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# results = model("path/to/image.jpg") # Predict on an image
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# results[0].show() # Display results
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# Export the model to ONNX format for deployment
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path = model.export(format="models/yolo11x_silkworm_cocoon") # Returns the path to the exported model |