28 lines
861 B
Python
28 lines
861 B
Python
import torch
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from ultralytics import YOLO
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# 加载预训练的模型
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model = YOLO('weights/plate_detect.pt')
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# 设置图像路径
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image_path = r'D:\Project\ChePai\test\images\val\20230331163841.jpg'
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# 进行推理
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results = model(image_path)
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# 解析结果
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for r in results:
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boxes = r.boxes # 包含检测结果的Boxes对象
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# 获取边界框坐标
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box_coordinates = boxes.xyxy.cpu().numpy()
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# 获取置信度分数
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confidences = boxes.conf.cpu().numpy()
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# 获取类别标签
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labels = boxes.cls.cpu().numpy().astype(int)
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# 打印检测结果
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for i in range(len(box_coordinates)):
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x1, y1, x2, y2 = box_coordinates[i]
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confidence = confidences[i]
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label = model.names[labels[i]]
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print(f'Object: {label}, Confidence: {confidence:.2f}, Bounding Box: ({x1:.2f}, {y1:.2f}, {x2:.2f}, {y2:.2f})') |