80 lines
3.3 KiB
Python
80 lines
3.3 KiB
Python
#encoding=utf-8
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import xml.etree.ElementTree as ET
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import pandas as pd
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import csv
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def xml2csv(xmlpath):
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tree_obj = ET.parse(xmlpath)
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# 得到所有匹配Region 标签的Element对象的list集合
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list_Region = tree_obj.findall("Region")
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for Region in list_Region:
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# 几何面对应的类(phenology_name)在标签<Region name="water" color="255,0,0">
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Region_dict = Region.attrib
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phenology_name = Region_dict.get("name")
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print(phenology_name)
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list_GeometryDef = Region.findall("GeometryDef")
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list_Polygon = list_GeometryDef[0].findall("Polygon") # 获得该类下的几何面list
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for polygon in list_Polygon:
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# 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
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Coordinates_list = coordinates = polygon.find('.//Coordinates').text.strip().split()
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# POLYGON((119.035 31.51,119.035 31.50,119.033 31.50)) csv中
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print("value")
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# 向csv中写
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def csvfile(csvpath,data):
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with open(csvpath, 'a', newline='') as file:
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# 2. step
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writer = csv.writer(file)
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# data example
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#data = ["This", "is", "a", "Test"]
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writer.writerow(data)
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# Define the structure of the data
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#data示例 student_header = ['name', 'age', 'major', 'minor']
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def csvcreateTitile(csvpath,data):
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# 1. Open a new CSV file
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with open(csvpath, 'w') as file:
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# 2. Create a CSV writer
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writer = csv.writer(file)
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# 3. Write data to the file
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writer.writerow(data)
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# 将列表中的坐标对转换为字符串
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def createcsv_roi_polygon(coordinates):
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coord_str = ', '.join([f'{coordinates[i]} {coordinates[i + 1]}' for i in range(0, len(coordinates), 2)])
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# 构建最终的POLYGON字符串
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polygon_str = f'POLYGON(({coord_str}))'
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print(polygon_str)
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return polygon_str
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if __name__ == '__main__':
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xmlpath = r"F:\MicroWorkspace\Micro\likun-GF3-VegetationP\vegTest.xml"
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tree_obj = ET.parse(xmlpath)
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csv_header = ['sar_img_name', 'phenology_id', 'phenology_name', 'roi_polygon']
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csvpath = r"F:\MicroWorkspace\Micro\likun-GF3-VegetationP\vegTest.csv"
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# csvcreateTitile(csvpath,csv_header)
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csvfile(csvpath,csv_header)
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# 得到所有匹配Region 标签的Element对象的list集合
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list_Region = tree_obj.findall("Region")
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for Region in list_Region:
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# 几何面对应的类(phenology_name)在标签<Region name="water" color="255,0,0">
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Region_dict = Region.attrib
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phenology_name = Region_dict.get("name")
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print(phenology_name)
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# list_GeometryDef = Region.findall("GeometryDef")
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list_Polygon = Region.findall(".//Polygon") # 获得该类下的几何面list
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count = 1
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for polygon in list_Polygon:
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# 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
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Coordinates_list = coordinates = polygon.find('.//Coordinates').text.strip().split()
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# 将坐标和ploygon对应的写入到.csv中
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polygon_str=createcsv_roi_polygon(Coordinates_list)
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# POLYGON((119.035 31.51,119.035 31.50,119.033 31.50)) csv中
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data = ['0', count, phenology_name, polygon_str]
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csvfile(csvpath,data)
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count += 1
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