from PIL import Image
from ultralytics import YOLO

# 加载预训练的YOLOv8n模型
model = YOLO('models/detection/best.pt')

# 在'bus.jpg'上运行推理
results = model(['/home/nvidia/newdisk/hkpc/2.jpg'])  # 结果列表

# 展示结果
for r in results:
    print("=========================")
    result_list = r.boxes.data.tolist()
    for sublist in result_list:
        print(sublist)
        conf = sublist[4]
        if float(conf) > 0.5:
            width = sublist[2] - sublist[0]
            hight = sublist[3] - sublist[1]
            print('width='+str(width)+" hight="+str(hight))

            #print(r.probs)  # 打印包含检测到的类别概率的Probs对象
            im_array = r.plot()  # 绘制包含预测结果的BGR numpy数组
            im = Image.fromarray(im_array[..., ::-1])  # RGB PIL图像
            # im.show()  # 显示图像
            im.save('results.jpg')  # 保存图像