图像区域的最小边界框?

时间:2013-11-07 15:02:15

标签: python opencv

我找到了一种计算图像上封闭区域的最小边界框的方法(同时考虑旋转角度)。

我可以使用以下代码提取该图像的质心坐标,边界框的宽度和长度以及旋转角度:

from PIL import Image
import cv2
import numpy as np
from matplotlib import pyplot as plt

image_file = Image.open("binaryraster.png")
image_file = image_file.convert('1')
image_file.save('result.png')

img = cv2.imread('result.png',0)
edges = cv2.Canny(img,100,200)
plt.subplot(111),plt.imshow(edges,cmap = 'gray')
plt.title('Canny Edge detection'), plt.xticks([]), plt.yticks([])

ret,thresh = cv2.threshold(img,127,255,0)
contours,hierarchy = cv2.findContours(thresh, 1, 2)

cnt = contours[0]


leftmost = tuple(cnt[cnt[:,:,0].argmin()][0])
rightmost = tuple(cnt[cnt[:,:,0].argmax()][0])
topmost = tuple(cnt[cnt[:,:,1].argmin()][0])
bottommost = tuple(cnt[cnt[:,:,1].argmax()][0])

rect = cv2.minAreaRect(cnt)
box = cv2.cv.BoxPoints(rect)
box = np.int0(box)



M = cv2.moments(cnt)
centroid_x = int(M['m10']/M['m00'])
centroid_y = int(M['m01']/M['m00'])

print (leftmost)
print (rightmost)
print (topmost)
print (bottommost)

print(centroid_x)
print(centroid_y)

print(rect)
print(box)

plt.show()

当我在一张图片中有很多区域时,我的代码无法提取所有这些信息。

你可以帮我吗

1 个答案:

答案 0 :(得分:0)

cnt = contours[0] # you're only checking the 1st contour here

你可能想要遍历所有找到的轮廓:

for cnt in contours:

    leftmost = tuple(cnt[cnt[:,:,0].argmin()][0])
    rightmost = tuple(cnt[cnt[:,:,0].argmax()][0])
    topmost = tuple(cnt[cnt[:,:,1].argmin()][0])
    bottommost = tuple(cnt[cnt[:,:,1].argmax()][0])

    rect = cv2.minAreaRect(cnt)
    box = cv2.cv.BoxPoints(rect)
    box = np.int0(box)



    M = cv2.moments(cnt)
    centroid_x = int(M['m10']/M['m00'])
    centroid_y = int(M['m01']/M['m00'])

    print (leftmost)
    print (rightmost)
    print (topmost)
    print (bottommost)

    print(centroid_x)
    print(centroid_y)

    print(rect)
    print(box)