使用直方图的图像python opencv中的颜色百分比

时间:2017-04-02 11:38:41

标签: python opencv image-processing histogram

我是python和图像处理的初学者。我想使用直方图函数从图像中找到棕色的百分比。

我做了直方图功能,但我不知道如何找到图像中棕色的百分比。

这是我的python代码

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

img = cv2.imread('C:\Users\MainUser\Desktop\histogram\dates.jpg', -1)
cv2.imshow('GoldenGate',img)

color = ('b','g','r')
for channel,col in enumerate(color):
    histr = cv2.calcHist([img],[channel],None,[256],[0,256])
    plt.plot(histr,color = col)
    plt.xlim([0,256])
plt.title('Histogram for color scale picture')
plt.show()

while True:
    k = cv2.waitKey(0) & 0xFF     
    if k == 27: break             # ESC key to exit 
cv2.destroyAllWindows()

我使用的图像

the image that I use

我有这段代码的输出 enter image description here

2 个答案:

答案 0 :(得分:5)

import numpy as np
import cv2

img = cv2.imread('J9MbW.jpg')

brown = [145, 80, 40]  # RGB
diff = 20
boundaries = [([brown[2]-diff, brown[1]-diff, brown[0]-diff],
               [brown[2]+diff, brown[1]+diff, brown[0]+diff])]
# in order BGR as opencv represents images as numpy arrays in reverse order

for (lower, upper) in boundaries:
    lower = np.array(lower, dtype=np.uint8)
    upper = np.array(upper, dtype=np.uint8)
    mask = cv2.inRange(img, lower, upper)
    output = cv2.bitwise_and(img, img, mask=mask)

    ratio_brown = cv2.countNonZero(mask)/(img.size/3)
    print('brown pixel percentage:', np.round(ratio_brown*100, 2))

    cv2.imshow("images", np.hstack([img, output]))
    cv2.waitKey(0)

这对你有用。但请注意,它高度依赖于您的RGB棕色值以及您想要的容差(diff)。

如果您对上述代码的详细信息有任何疑问,请随时提出。

答案 1 :(得分:0)

我需要相同的结果,因此我使用了您的代码并计算了百分比。

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

img = cv2.imread('azul200.png', -1)
cv2.imshow('Imagem:',img)

color = ('b','g','r')
qtdBlue = 0
qtdGreen = 0
qtdRed = 0
totalPixels = 0

for channel,col in enumerate(color):
    histr = cv2.calcHist([img],[channel],None,[256],[1,256])
    plt.plot(histr,color = col)
    plt.xlim([0,256])
    totalPixels+=sum(histr)
    print histr
    if channel==0:
        qtdBlue = sum(histr)
    elif channel==1:
        qtdGreen = sum(histr)
    elif channel==2:
        qtdRed = sum(histr)

qtdBlue = (qtdBlue/totalPixels)*100
qtdGreen = (qtdGreen/totalPixels)*100
qtdRed = (qtdRed/totalPixels)*100

qtdBlue = filter(operator.isNumberType, qtdBlue)
qtdGreen = filter(operator.isNumberType, qtdGreen)
qtdRed = filter(operator.isNumberType, qtdRed)

plt.title("Red: "+str(qtdRed)+"%; Green: "+str(qtdGreen)+"%; Blue: "+str(qtdBlue)+"%")
plt.show()

我希望它有所帮助,对我有用。