yolov8测试代码

你可以使用以下代码来测试yolov8模型：

import torch
from PIL import Image
from torchvision.transforms import functional as F
from yolov8.ultralytics.yolo.v8.detect import detect

# 加载模型权重
weights_path = 'E:/AI/yolo/yolov8/ultralytics-main/ultralytics/yolo/v8/detect/yolov8n.pt'
model = torch.load(weights_path, map_location=torch.device('cpu'))

# 加载图像
image_path = 'path_to_image.jpg'
image = Image.open(image_path)

# 图像预处理
image_tensor = F.to_tensor(image)
image_tensor = image_tensor.unsqueeze(0)

# 进行目标检测
results = detect(model, image_tensor)

# 打印检测结果
print(results.pandas().xyxy\[0\])

请确保你已经安装了必要的依赖库，并将`weights_path`和`image_path`替换为你自己的路径。这段代码将加载yolov8模型的权重，对输入图像进行目标检测，并打印出检测结果。
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