生活就像大海，我就像一条咸鱼，在浩瀚的海洋中边浪边学，这是opencv笔记系列中的「彩色直方图」。
这一篇与上一篇类似 ，只不过是统计多通道图像的每个颜色通道的像素出现的概率，即彩色直方图。小编边浪边学，顺带以很咸鱼的方式把它们记录下来。
原图还是那一个她
代码和显示输出如下
import cv2
import numpy as np
import matplotlib.pyplot as plt
img = cv2.imread('test1.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
count_b = np.zeros(256,np.float32)
count_g = np.zeros(256,np.float32)
count_r = np.zeros(256,np.float32)
#每种色素出现的次数
for i in range(0,height):
for j in range(0,width):
b,g,r = img[i,j]
index_b = int(b)
index_g = int(g)
index_r = int(r)
count_b[index_b] = count_b[index_b] + 1
count_g[index_g] = count_g[index_g] + 1
count_r[index_r] = count_r[index_r] + 1
# 每种色素出现的概率
for i in range(0,256):
count_b[i] = count_b[i] / (height * width)
count_g[i] = count_g[i] / (height * width)
count_r[i] = count_r[i] / (height * width)
x = np.linspace(0,255,256)
y1 = count_b
plt.figure()
plt.bar(x,y1,0.9,alpha=1,color='b')
y2 = count_g
plt.figure()
plt.bar(x,y2,0.9,alpha=1,color='g')
y3 = count_r
plt.figure()
plt.bar(x,y3,0.9,alpha=1,color='r')
plt.show()
