使用OpenCV在Python中计算图像中黑色像素的数量

问题描述

我在Python中具有以下测试代码以读取，设置阈值和显示图像:

I have the following test code in Python to read, threshold and display an image:

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

# read image
img = cv2.imread('slice-309.png',0)
ret,thresh = cv2.threshold(img,0,230, cv2.THRESH_BINARY)
height, width = img.shape
print "height and width : ",height, width
size = img.size
print "size of the image in number of pixels", size

# plot the binary image
imgplot = plt.imshow(img, 'gray')
plt.show()

我想计算带有特定标签(例如黑色)的图像中的像素数.我怎样才能做到这一点 ?我看过OpenCV的教程，但没有找到任何帮助:-(

I would like to count the number of pixels within the image with a certain label, for instance black.How can I do that ? I looked at tutorials of OpenCV but did not find any help :-(

谢谢！

推荐答案

对于黑色图像，您将获得像素总数(行*列)，然后从 cv2.countNonZero(mat) .

For black images you get the total number of pixels (rows*cols) and then subtract it from the result you get from cv2.countNonZero(mat).

对于其他值，您可以使用 cv2.inRange() 返回一个二进制掩码，该掩码显示所需颜色/标签/值的所有位置，然后使用cv2.countNonZero计数其中的多少.

For other values, you can create a mask using cv2.inRange() to return a binary mask showing all the locations of the color/label/value you want and then use cv2.countNonZero to count how many of them there are.

更新(根据Miki的评论):

UPDATE (Per Miki's comment):

当尝试查找具有特定值的元素的数量时，Python允许您跳过cv2.inRange()调用并执行以下操作:

When trying to find the count of elements with a particular value, Python allows you to skip the cv2.inRange() call and just do:

cv2.countNonZero(img == scalar_value)

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