yolov7检测输出xml格式文件

你可以使用以下代码将YOLOv7检测的输出转换为XML格式的文件：

import xml.etree.ElementTree as ET
import numpy as np

def create_xml(image_name, detections, save_path):
    root = ET.Element("annotation")

    folder = ET.SubElement(root, "folder")
    folder.text = "images"

    filename = ET.SubElement(root, "filename")
    filename.text = image_name

    size = ET.SubElement(root, "size")
    width = ET.SubElement(size, "width")
    height = ET.SubElement(size, "height")
    depth = ET.SubElement(size, "depth")
    width.text = str(detections.shape[1])
    height.text = str(detections.shape[0])
    depth.text = str(detections.shape[2])

    for detection in detections:
        object_elem = ET.SubElement(root, "object")
        name = ET.SubElement(object_elem, "name")
        name.text = detection[0]

        bndbox = ET.SubElement(object_elem, "bndbox")
        xmin = ET.SubElement(bndbox, "xmin")
        ymin = ET.SubElement(bndbox, "ymin")
        xmax = ET.SubElement(bndbox, "xmax")
        ymax = ET.SubElement(bndbox, "ymax")
        xmin.text = str(int(detection[1]))
        ymin.text = str(int(detection[2]))
        xmax.text = str(int(detection[3]))
        ymax.text = str(int(detection[4]))

    tree = ET.ElementTree(root)
    tree.write(save_path)

# 示例用法
image_name = "example.jpg"
detections = np.array([["person", 100, 200, 300, 400], ["car", 50, 60, 200, 150]])
save_path = "output.xml"

create_xml(image_name, detections, save_path)

在上面的示例代码中，`detections` 是一个形状为 (N, 5) 的numpy数组，其中N表示检测到的物体数量。每个检测由类别名称、边界框的左上角坐标（xmin，ymin）和右下角坐标（xmax，ymax）组成。你可以根据自己的需求修改代码以适应YOLOv7模型的输出格式。