Python：检测图像中的边缘矩形并将其裁剪成正方形？

Question

我已经弄清楚如何使用 PIL 检测图像中的边缘（图像大多是带有黑色绘图标记的白色背景）。如何检测包含这些边缘的矩形，以便裁剪图像。

例如，我想裁剪如下内容：

进入：

或者这个：

进入：

我熟悉 PIL 中的裁剪，但我不知道如何围绕对象自动居中。

更新：

我已通过执行以下操作设法检测到边缘：

from PIL import Image, ImageFilter
image = Image.open("myImage.png")
image = image.filter(ImageFilter.FIND_EDGES)

如何获得包含所有这些边的矩形？

Answer 1

你可以做到这一点，例如使用 opencv

import cv2

#Load the image in black and white (0 - b/w, 1 - color).
img = cv2.imread('input.png', 0)

#Get the height and width of the image.
h, w = img.shape[:2]

#Invert the image to be white on black for compatibility with findContours function.
imgray = 255 - img
#Binarize the image and call it thresh.
ret, thresh = cv2.threshold(imgray, 127, 255, cv2.THRESH_BINARY)

#Find all the contours in thresh. In your case the 3 and the additional strike
contours, hierarchy = cv2.findContours(thresh, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
#Calculate bounding rectangles for each contour.
rects = [cv2.boundingRect(cnt) for cnt in contours]

#Calculate the combined bounding rectangle points.
top_x = min([x for (x, y, w, h) in rects])
top_y = min([y for (x, y, w, h) in rects])
bottom_x = max([x+w for (x, y, w, h) in rects])
bottom_y = max([y+h for (x, y, w, h) in rects])

#Draw the rectangle on the image
out = cv2.rectangle(img, (top_x, top_y), (bottom_x, bottom_y), (0, 255, 0), 2)
#Save it as out.jpg
cv2.imwrite('out.jpg', img)

示例输出