小编The*_*cle的帖子

I'am trying to run a simple geopandas code using ANACONDA spyder. However, I'am encountering an error.

I have included the code and the error as below:

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here is the code:

import geopandas as gpd
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
world.plot()
import matplotlib.pyplot as plt
plt.show()

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here is the error:

File "C:\Users\usr\Anaconda3\lib\site-packages\geopandas\plotting.py", line 90, in plot_polygon_collection "The descartes package is required for plotting polygons in geopandas."

ImportError: The descartes package is required for plotting polygons in geopandas.

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I checked online …

有没有办法将图像转换为矢量化形式，如下所示：

我已经查找了 CNN、Pillow 和 CV2 方法，但是我没有在网上找到任何可用的资源来实现此图像转换。

感谢您在此事上的帮助。

正常图像：

矢量化图像：

更新：

我已经使用SLIC方法实现了图像分割，以下是新代码和结果图像。可以看出，新图像接近矢量化图像（期望的结果），但质量/细节差异仍然很大。

还有其他想法吗？

from skimage import data, segmentation, color
from skimage.future import graph
from matplotlib import pyplot as plt
from PIL import Image
from skimage import io

path='/home/user/Desktop/Image1.jpeg'
img = io.imread(path)

labels1 = segmentation.slic(img, compactness=50, n_segments=5000,
                        start_label=1)
out1 = color.label2rgb(labels1, img, kind='avg', bg_label=0)
out1 = Image.fromarray(out1, 'RGB')
out1.save('/home/user/Desktop/1.png')
g = graph.rag_mean_color(img, labels1, mode='similarity')
labels2 = graph.cut_normalized(labels1, g)
out2 = color.label2rgb(labels2, img, kind='avg', bg_label=0)
out2 = Image.fromarray(out2, 'RGB')
out2.save('/home/user/Desktop/2.png')

fig, ax = …