Question

图像中的区域由4个坐标x1,y1,x2,y2,x3,y3,x4,y4定义，我想检索该区域内的所有像素坐标x,y。

Answer 1

假设是矩形，您可以使用https://embed.plnkr.co/F3t6gI8TPUZwCOnA/为左上角和右下角之间的点生成坐标矩阵。

X, Y = np.mgrid[xmin:xmax, ymin:ymax]

并将它们转换为带有

的二维坐标数组

np.vstack((X.ravel(), Y.ravel()))

编辑：任意形状

正如Mark Setchell指出的那样，你的问题中没有任何关于矩形形状的讨论。

如果要列出任意路径内的所有点，不一定是4个顶点，可以使用contains_points() np.mgrid中的matplotlib。

以下是从Path

派生的一些代码

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.path import Path

import skimage.data

# path vertex coordinates
vertices = np.asarray([(100, 100),
                       (300,  80),
                       (350, 200),
                       ( 60, 150)])

# create dummy image
img = skimage.data.chelsea()

# from vertices to a matplotlib path
path = Path(vertices)
xmin, ymin, xmax, ymax = np.asarray(path.get_extents(), dtype=int).ravel()

# create a mesh grid for the whole image, you could also limit the
# grid to the extents above, I'm creating a full grid for the plot below
x, y = np.mgrid[:img.shape[1], :img.shape[0]]
# mesh grid to a list of points
points = np.vstack((x.ravel(), y.ravel())).T

# select points included in the path
mask = path.contains_points(points)
path_points = points[np.where(mask)]

# reshape mask for display
img_mask = mask.reshape(x.shape).T

# now lets plot something to convince ourselves everything works
fig, ax = plt.subplots()

# masked image
ax.imshow(img * img_mask[..., None])
# a random sample from path_points
idx = np.random.choice(np.arange(path_points.shape[0]), 200)
ax.scatter(path_points[idx, 0], path_points[idx, 1], alpha=0.3, color='cyan')

another answer of mine

如何获取python中图像中指定区域中的所有像素坐标？

1 个答案: