geom_img/img_util.py

import geopandas as gpd
import matplotlib.pyplot as plt
from shapely.wkt import loads
from PIL import Image
import os
# 调整尺寸


def resizeImage(dir,fileName):
    # 打开原始图片
    original_image = Image.open(dir+"/"+fileName)
    # 调整图片尺寸到 256x256
    resized_image = original_image.resize((256, 256))
    dir = dir.replace('tb', 'tb_256')
    if not os.path.exists(dir):
        os.makedirs(dir)
    # 保存调整后的图片
    resized_image.save(dir+"/"+fileName)


# resizeImage('img/tb/6401812024070108270001change.png')

# 保存为 PNG 图片
def savePng(fileName, ewkt,dir):
    # 解析 WKT 数据字符串
    geometry = loads(ewkt.split(';')[1])  # 解析 WKT
    gdf = gpd.GeoDataFrame(geometry=[geometry])

    # 创建绘图
    fig, ax = plt.subplots(figsize=(10, 10))

    # 如果是 Polygon，处理其外部和内部
    if geometry.geom_type == 'Polygon':
        ax.fill(*geometry.exterior.xy, color='black')  # 填充外部为黑色
        for interior in geometry.interiors:
            ax.fill(*interior.xy, color='white')  # 填充内部（洞）为白色
    # 如果是 MultiPolygon，遍历每个 Polygon
    elif geometry.geom_type == 'MultiPolygon':
        for poly in geometry.geoms:  # 使用 geometry.geoms 进行迭代
            ax.fill(*poly.exterior.xy, color='black')  # 填充外部为黑色
            for interior in poly.interiors:
                ax.fill(*interior.xy, color='white')  # 填充内部（洞）为白色

    # 设置坐标轴范围
    ax.set_xlim(gdf.total_bounds[[0, 2]])
    ax.set_ylim(gdf.total_bounds[[1, 3]])

    # 去掉坐标轴
    ax.axis('off')

    # 保存为 PNG 图片
    dir=dir+'/tb'
    if not os.path.exists(dir):
        os.makedirs(dir)

    fileName = fileName + '.png'
    plt.savefig(dir+"/"+fileName, dpi=300, bbox_inches='tight', pad_inches=0)
    plt.close()

    # 调用 resizeImage 函数来调整图片大小
    resizeImage(dir,fileName)



# ewkt = "SRID=3857;POLYGON((13522050.0 3666550.0, 13522050.0 3657500.0, 13512100.0 3657500.0, 13512100.0 3666550.0, 13522050.0 3666550.0), (13516300.0 3662300.0, 13517350.0 3662300.0, 13517350.0 3663150.0, 13516300.0 3663150.0, 13516300.0 3662300.0))"
# savePng('111',ewkt)