import torch
from ultralytics import YOLO

# 加载预训练的模型
model = YOLO('weights/plate_detect.pt')

# 设置图像路径
image_path = r'D:\Project\ChePai\test\images\val\20230331163841.jpg'

# 进行推理
results = model(image_path)

# 解析结果
for r in results:
    boxes = r.boxes  # 包含检测结果的Boxes对象
    # 获取边界框坐标
    box_coordinates = boxes.xyxy.cpu().numpy()
    # 获取置信度分数
    confidences = boxes.conf.cpu().numpy()
    # 获取类别标签
    labels = boxes.cls.cpu().numpy().astype(int)

    # 打印检测结果
    for i in range(len(box_coordinates)):
        x1, y1, x2, y2 = box_coordinates[i]
        confidence = confidences[i]
        label = model.names[labels[i]]
        print(f'Object: {label}, Confidence: {confidence:.2f}, Bounding Box: ({x1:.2f}, {y1:.2f}, {x2:.2f}, {y2:.2f})')