现有文件夹A内有若干张滑坡二进制掩码图像，如何在pycharm软件中利用代码求得值为1的多边形也就是滑坡体的目标检测VOC格式的标签以xml文件（应与每张图片一一对应）形式存贮到文件夹B，注意每张图片内有四个滑坡体，也就是每张照片需要四个检测框（可以通过多边形的连续性判断）

可以使用OpenCV和xml.etree.ElementTree模块实现，代码如下：

import cv2
import numpy as np
import os
import xml.etree.ElementTree as ET

folder_A = "path/to/folder/A"
folder_B = "path/to/folder/B"

# Function to generate VOC format XML file
def generate_xml(filename, width, height, objects):
    annotation = ET.Element("annotation")
    ET.SubElement(annotation, "folder").text = "Folder name"
    ET.SubElement(annotation, "filename").text = filename
    ET.SubElement(annotation, "path").text = os.path.join(os.getcwd(), filename)
    size = ET.SubElement(annotation, "size")
    ET.SubElement(size, "width").text = str(width)
    ET.SubElement(size, "height").text = str(height)
    ET.SubElement(size, "depth").text = "3"
    for obj in objects:
        ob = ET.SubElement(annotation, "object")
        ET.SubElement(ob, "name").text = "slip"
        ET.SubElement(ob, "pose").text = "Unspecified"
        ET.SubElement(ob, "truncated").text = "0"
        ET.SubElement(ob, "difficult").text = "0"
        bbox = ET.SubElement(ob, "bndbox")
        ET.SubElement(bbox, "xmin").text = str(obj[0])
        ET.SubElement(bbox, "ymin").text = str(obj[1])
        ET.SubElement(bbox, "xmax").text = str(obj[2])
        ET.SubElement(bbox, "ymax").text = str(obj[3])
    xml_str = ET.tostring(annotation)
    return xml_str

# Loop through all images in folder A
for file in os.listdir(folder_A):
    if file.endswith(".bin"):
        # Read binary image
        img_bin = np.fromfile(os.path.join(folder_A, file), np.uint8)
        img = cv2.imdecode(img_bin, cv2.IMREAD_GRAYSCALE)
        # Convert binary to binary edge image
        ret, thresh = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY)
        edges = cv2.Canny(thresh, 100, 200)
        # Find contours and draw bounding boxes
        contours, hierarchy = cv2.findContours(edges, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
        objects = []
        for cnt in contours:
            # Approximate contour as polygon
            epsilon = 0.01 * cv2.arcLength(cnt, True)
            approx = cv2.approxPolyDP(cnt, epsilon, True)
            # Check if polygon has 4 sides (i.e., a rectangle)
            if len(approx) == 4:
                x, y, w, h = cv2.boundingRect(approx)
                objects.append([x, y, x + w, y + h])
        # Generate XML file
        xml_str = generate_xml(file + ".xml", img.shape[1], img.shape[0], objects)
        # Save XML file
        with open(os.path.join(folder_B, file + ".xml"), "wb") as f:
            f.write(xml_str)

需要安装OpenCV和numpy模块，代码中的文件夹路径需要根据实际情况修改。