Python+OpenCV图像处理之直方图统计

"""
Author:XiaoMa
date:2021/10/24
"""
#调用需要的包
import cv2
import matplotlib.pyplot as plt
 
img0 = cv2.imread('E:\From Zhihu\For the desk\cvseven.jpeg')
img1 = cv2.cvtColor(img0, cv2.COLOR_BGR2GRAY)     #转化为灰度图
h, w = img1.shape[:2]
print(h, w)
cv2.namedWindow("W0")
cv2.imshow("W0", img1)
cv2.waiTKEy(delay = 0)

#绘制直方图
hist = cv2.calcHist([img1], [0], None, [256], [0, 255])
plt.plot(hist, color = 'lime', label = '直方图', linestyle = '--')
plt.legend()
plt.savefig('E:\From Zhihu\For the desk\cvseven1.jpeg')
plt.show()

"""
Author:XiaoMa
date:2021/10/24
"""
#调用需要的包
import cv2
import matplotlib.pyplot as plt
 
plt.rcParams['font.family'] = 'SimHei'       #将全局中文字体改为黑体
 
img0 = cv2.imread('E:\From Zhihu\For the desk\cvseven.jpeg')
img1 = cv2.cvtColor(img0, cv2.COLOR_BGR2GRAY)
h, w = img1.shape[:2]
print(h, w)
cv2.namedWindow("W0")
cv2.imshow("W0", img0)
cv2.waitKey(delay = 0)
 
#绘制直方图
hist = cv2.calcHist([img0], [0], None, [256], [0, 255])
plt.plot(hist, color = 'lime', label = '蓝色通道直方图', linestyle = '--', alpha = 1)
plt.legend()
plt.savefig('E:\From Zhihu\For the desk\cvseven1.jpeg')
plt.show()

##得到掩膜图
mask = np.zeros(img0.shape, np.uint8)    #将每一个像素点设置为0，就是黑色
mask[109:309, 212:412] = 255             #选取特定区域设置为白色
img0_1 = cv2.bitwise_and(img0, mask)     #图像与操作得到掩膜图
cv2.namedWindow("W1")
cv2.imshow("W1", img0_1)
cv2.waitKey(delay = 0)

#绘制掩膜直方图
##得到掩膜图
mask = np.zeros(img1.shape, np.uint8)    #将每一个像素点设置为0，就是黑色
mask[109:309, 212:412] = 255             #选取特定区域设置为白色
img1_1 = cv2.bitwise_and(img1, mask)     #图像与操作得到掩膜图
cv2.namedWindow("W1")
cv2.imshow("W1", img1_1)
cv2.waitKey(delay = 0)
##绘制掩膜直方图和部分图像直方图
hist1 = cv2.calcHist([img1], [0], mask, [256], [0, 255])         #掩膜图直方图，参数需要修改
hist2 = cv2.calcHist([img1], [0], None, [256], [0,255])
plt.plot(hist1, color = 'b', label = '掩膜直方图', linestyle = '--')
plt.plot(hist2, color = 'r', label = '原图直方图', linestyle = '-.')
plt.legend()
plt.savefig('E:\From Zhihu\For the desk\cvseven2.jpeg')
plt.show()

img0_2 = cv2.cvtColor(img0, cv2.COLOR_BGR2HSV) #将 RGB 空间转化为 HSV 空间
cv2.namedWindow("W2")
cv2.imshow("W2", img0_2)
cv2.waitKey(delay = 0)

##绘制H-S直方图
hist3 = cv2.calcHist ([img0_2], [0, 1], None , [180, 256], [0, 180, 0, 256])#官网给出的解释：channel = [0,1] 因为我们需要同时处理 H 和 S 平面；bins = [180,256] H 平面为 180，S 平面为 256；range = [0,180,0,256] 色调值介于 0 和 180 之间，饱和度介于 0 和 256 之间
plt.imshow(hist3)
plt.savefig('E:\From Zhihu\For the desk\cvseven3.jpeg')
plt.show()