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- 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
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