1、使用matplotlib.path库

步骤：

创建多边形点
matplotlib.path生成多边形路径
判断点是否在多边形内

示例代码为：

import matplotlib.path as mplPath
import numpy as np

poly = [190, 50, 500, 310]
poly_path = mplPath.Path(np.array([[190, 50],
                                    [50, 500],
                                    [500, 310],
                                    [310, 190]])) #四个顶点
point = (200, 100)
print(point, " is in polygon: ", poly_path.contains_point(point))

point = (1200, 1000)
print(point, " is in polygon: ", poly_path.contains_point(point))

输出为：
(200, 100) is in polygon: True
(1200, 1000) is in polygon: False

如果是多个点，那么point是N,2的numpy ndarray即可。

2、使用shapely库

示例：

from shapely.geometry import Point
from shapely.geometry.polygon import Polygon

point = Point(0.5, 0.5)
polygon = Polygon([(0, 0), (0, 1), (1, 1), (1, 0)])
print(polygon.contains(point))

但shapely库只能用在linux系统

对比速度：

import matplotlib.path as mplPath
import numpy as np
import time
from shapely.geometry import Point
from shapely.geometry.polygon import Polygon

poly_path = mplPath.Path(np.array([[190, 50],[50, 500],[500, 310],[310, 190]]))
point1 = (200, 100)
point2 = (1200, 1000)
print(point1, " is in polygon: ", poly_path.contains_point(point1))
print(point2, " is in polygon: ", poly_path.contains_point(point2))
start = time.time()
for i in range(1000):
    poly_path.contains_point(point1)
duration = time.time()-start
print('total time',duration)

point1 = Point(200, 100)
point2 = Point(1200,1000)
polygon = Polygon([[190, 50],[50, 500],[500, 310],[310, 190]])
print(polygon.contains(point1))
print(polygon.contains(point2))
start = time.time()
for i in range(1000):
    polygon.contains(point1)
duration = time.time()-start
print('total time',duration)