英文:

Given a list of coordinate points for the perimeter of a shape, how do I return the set of all coordinate points for the enclosed area?

问题

以下是翻译好的部分：

我有一个二维坐标列表，表示形状的周边坐标，格式如下：
[[x1, y1], [x2, y2], [x3, y3], ... ,[xn, yn]]

我想要一个函数，该函数将返回由该周边坐标包围的区域的坐标。

背景信息：
周边坐标是围绕图像部分的坐标。我之所以想要这个区域的坐标，是因为当我绘制图像部分时，我想要能够突出显示整个区域。是否有一些能够高效完成这个任务的Python库和函数？

我相信可以使用很多for循环来完成这个任务，但我更愿意使用更高效的方法。

英文:

Python.

I have a 2d list of the coordinates for the perimeter of a shape in the following format:
[[x1, y1], [x2, y2], [x3, y3], ... ,[xn, yn]]

I want a function that will return the coordinates of the area enclosed by that perimeter.

Context:
The perimeter coordinates are the coordinates enclosing a section of an image. The reason that I want the coordinates of the area is because I want to be able to highlight the full area of the section of the image when I plot it. Is there some python library and function that can efficiently do this?

I'm sure this can be done with a lot of for loops, but I'd rather use a more efficient way.

答案1

得分: 0

Here is the translated code snippet:

如果我理解正确，您要么需要这些点坐标的凸包，要么需要一个边界框。所以，请检查以下代码，看看哪个适合您：

```python
from shapely.geometry import Point, MultiPoint

test_coordinates = [[1,1], [2,5], [7, 4], [3, 6], [9, 1], [5,2]]

# 为列表中的每个2D坐标创建点：
point_coordinates = [Point(x[0], x[1]) for x in test_coordinates]

# 创建所有点的单个多点表示：
multi_point = MultiPoint(point_coordinates)

# 凸包：
convex_hull = multi_point.convex_hull

# 凸包的坐标 - 请参阅下面的输出/注释
print(convex_hull.exterior.coords.xy)
#Out[23]: 
#(array('d', [1.0, 2.0, 3.0, 7.0, 9.0, 1.0]),
# array('d', [1.0, 5.0, 6.0, 4.0, 1.0, 1.0]))

# 边界框：
bounding_box = multi_point.bounds
print(bounding_box) 
# (1.0, 1.0, 9.0, 6.0)

因此，在以下图中，坐标是蓝色点，凸包是红色多边形，边界框是蓝色矩形：

要创建图表，以防您想查看您的数据：

import matplotlib.pyplot as plt
from shapely.geometry import box
# 绘制点
plt.scatter([point.x for point in point_coordinates], [point.y for point in point_coordinates])
# 绘制凸包
plt.plot(*convex_hull.exterior.xy, label='convex hull', color='red')
# 绘制边界框
plt.plot(*box(*bounding_box, ccw=True).exterior.xy, label='bounding_box', color='green')
# 将它们全部显示在一起！
plt.show()

This code is now translated into Chinese.

<details>
<summary>英文:</summary>

If I get it correctly, you either want a convex hull of those point coordinates, or a bounding box. So, check the following code and see which one suits you:

from shapely.geometry import Point, MultiPoint

test_coordinates = [[1,1], [2,5], [7, 4], [3, 6], [9, 1], [5,2]]

create points for each 2D coordinates in the list:

point_coordinates = [Point(x[0], x1) for x in test_coordinates]

create a single multipoint representation of all points:

multi_point = MultiPoint(point_coordinates)

convex hull:

convex_hull = multi_point.convex_hull

coordinates of the convex hull - see the output below / commented

print(convex_hull.exterior.coords.xy)
#Out[23]:
#(array('d', [1.0, 2.0, 3.0, 7.0, 9.0, 1.0]),

array('d', [1.0, 5.0, 6.0, 4.0, 1.0, 1.0]))

bounding box:

bounding_box = multi_point.bounds
print(bounding_box)

(1.0, 1.0, 9.0, 6.0)

So, in the following figure, the coordinates are the blue points, convex hull is the red polygon and bounding box is the blue rectangle:
[![enter image description here][1]][1]


To create the plots, in case you want to see for your data:

import matplotlib.pyplot as plt
from shapely. Geometry import box

plot points

plt.scatter([point.x for point in point_coordinates], [point.y for point in point_coordinates])

plot convex hull

plt.plot(*convex_hull.exterior.xy, label='convex hull', color='red')

plot bounding box

plt.plot(*box(*bounding_box, ccw=True).exterior.xy, label='bounding_box', color='green')

show it all together!

plt.show()

  [1]: https://i.stack.imgur.com/g7PMl.png

</details>