80 lines
3.3 KiB
Python
80 lines
3.3 KiB
Python
#encoding=utf-8
|
|
import xml.etree.ElementTree as ET
|
|
import pandas as pd
|
|
import csv
|
|
|
|
def xml2csv(xmlpath):
|
|
tree_obj = ET.parse(xmlpath)
|
|
|
|
# 得到所有匹配Region 标签的Element对象的list集合
|
|
list_Region = tree_obj.findall("Region")
|
|
for Region in list_Region:
|
|
# 几何面对应的类(phenology_name)在标签<Region name="water" color="255,0,0">
|
|
Region_dict = Region.attrib
|
|
phenology_name = Region_dict.get("name")
|
|
print(phenology_name)
|
|
list_GeometryDef = Region.findall("GeometryDef")
|
|
list_Polygon = list_GeometryDef[0].findall("Polygon") # 获得该类下的几何面list
|
|
for polygon in list_Polygon:
|
|
# 从polygon list中获取得到<Coordinates>标签的数据 注意是空格分隔的和csv中不同
|
|
Coordinates_list = coordinates = polygon.find('.//Coordinates').text.strip().split()
|
|
# POLYGON((119.035 31.51,119.035 31.50,119.033 31.50)) csv中
|
|
print("value")
|
|
|
|
# 向csv中写
|
|
def csvfile(csvpath,data):
|
|
|
|
with open(csvpath, 'a', newline='') as file:
|
|
# 2. step
|
|
writer = csv.writer(file)
|
|
# data example
|
|
#data = ["This", "is", "a", "Test"]
|
|
writer.writerow(data)
|
|
|
|
|
|
# Define the structure of the data
|
|
#data示例 student_header = ['name', 'age', 'major', 'minor']
|
|
def csvcreateTitile(csvpath,data):
|
|
# 1. Open a new CSV file
|
|
with open(csvpath, 'w') as file:
|
|
# 2. Create a CSV writer
|
|
writer = csv.writer(file)
|
|
# 3. Write data to the file
|
|
writer.writerow(data)
|
|
|
|
# 将列表中的坐标对转换为字符串
|
|
def createcsv_roi_polygon(coordinates):
|
|
coord_str = ', '.join([f'{coordinates[i]} {coordinates[i + 1]}' for i in range(0, len(coordinates), 2)])
|
|
# 构建最终的POLYGON字符串
|
|
polygon_str = f'POLYGON(({coord_str}))'
|
|
print(polygon_str)
|
|
return polygon_str
|
|
|
|
if __name__ == '__main__':
|
|
xmlpath = r"E:\MicroWorkspace\GF3A_nanjing\input-ortho\test_shp\test.xml"
|
|
|
|
tree_obj = ET.parse(xmlpath)
|
|
csv_header = ['sar_img_name', 'phenology_id', 'phenology_name', 'roi_polygon']
|
|
csvpath = r"E:\MicroWorkspace\GF3A_nanjing\input-ortho\test_shp\test.csv"
|
|
# csvcreateTitile(csvpath,csv_header)
|
|
csvfile(csvpath,csv_header)
|
|
# 得到所有匹配Region 标签的Element对象的list集合
|
|
list_Region = tree_obj.findall("Region")
|
|
for Region in list_Region:
|
|
# 几何面对应的类(phenology_name)在标签<Region name="water" color="255,0,0">
|
|
Region_dict = Region.attrib
|
|
phenology_name = Region_dict.get("name")
|
|
print(phenology_name)
|
|
# list_GeometryDef = Region.findall("GeometryDef")
|
|
list_Polygon = Region.findall(".//Polygon") # 获得该类下的几何面list
|
|
count = 1
|
|
for polygon in list_Polygon:
|
|
# 从polygon list中获取得到<Coordinates>标签的数据 注意是空格分隔的和csv中不同
|
|
Coordinates_list = coordinates = polygon.find('.//Coordinates').text.strip().split()
|
|
# 将坐标和ploygon对应的写入到.csv中
|
|
polygon_str=createcsv_roi_polygon(Coordinates_list)
|
|
# POLYGON((119.035 31.51,119.035 31.50,119.033 31.50)) csv中
|
|
data = ['0', count, phenology_name, polygon_str]
|
|
csvfile(csvpath,data)
|
|
count += 1
|