🔄Update: [Lab-4] yolov8n Detect
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from ultralytics import YOLO
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import cv2
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# 加载最佳模型
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model = YOLO('runs/detect/yolov8n_coco128_exp1/weights/best.pt')
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# 在图像上进行推理
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source = 'datasets/img3.png' # 替换成你自己的测试图片路径
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results = model(source, save=True, conf=0.5) # conf为置信度阈值
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# 可视化结果(可选,使用OpenCV)
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# 读取带标注的结果图像
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result_image = results[0].plot() # 获取第一张图片的绘制结果
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cv2.imshow('Detection Result', result_image)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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# 也可以在视频或摄像头上进行推理
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# results = model('path/to/video.mp4', save=True, show=True)
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# results = model(0, show=True) # 0代表默认摄像头
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