"""
视觉:基本API应用(OPENCV)
"""
import cv2 import numpy as np"""图像读取方式3. 1.cv2.imread(filename or path, flags)flags=0:灰度图像;flags=1表示RGB图像;flags=-1表示alpha透明通道图像 """
import cv2
import numpy as np"""图像读取方式3.  1.cv2.imread(filename or path, flags)flags=0:灰度图像;flags=1表示RGB图像;flags=-1表示alpha透明通道图像
"""img = cv2.imread('000000005620.jpg')
# Gray是灰度图像;除以255是将像素转为0-1区间的值
Gray = img[:, :, 2]*0.3 + img[:, :, 1] * 0.59 + img[:, :, 0] * 0.11
gray = Gray/255
imgray = cv2.imread('000000005620.jpg', 0)# 加载透明通道图像
imalpha = cv2.imread('000000005620.jpg', -1)
print(gray)
if img is None:print('Image read error!')
else:# 图像可视化cv2.imshow('RGB of image', img)# 保存RGB图像cv2.imwrite('RGB.png', img)cv2.imshow('Gray of image', imgray)# 保存灰度图像cv2.imwrite('hd.png', imgray)cv2.imshow('alpha of image', imalpha)# 保存透明通道图像cv2.imwrite('alpha.png', imalpha)# cv2.imshow('Gray of image', gray)print(type(imalpha), imalpha.shape)# 等待读者操作:让图像显示暂停delay毫秒,当delay秒设置为0的时候,表示永远,当键盘任意输入的时候,结束暂停cv2.waitKey(0)# 窗口对象销毁cv2.destroyAllWindows() 
RGB:

Gray:

alpha(透明通道图像只有加载.png格式并带有净色的图像才会显示透明):

E:\myprogram\anaconda\envs\python3.6\python.exe E:/XXX/OPENCV/CV.py
 [[0.96862745 0.96078431 0.96470588 ... 0.97254902 0.97254902 0.97254902]
  [0.96862745 0.96078431 0.96078431 ... 0.94901961 0.95686275 0.96078431]
  [0.97254902 0.96470588 0.96470588 ... 0.98431373 0.98431373 0.98431373]
  ...
  [0.94117647 0.94117647 0.94117647 ... 0.95686275 0.95686275 0.95686275]
  [0.94901961 0.94901961 0.94901961 ... 0.95294118 0.95294118 0.95294118]
  [0.96078431 0.96078431 0.96078431 ... 0.9372549  0.9372549  0.9372549 ]]
 <class 'numpy.ndarray'> (612, 612, 3)
Process finished with exit code 0
------------------------------------------------------------------------------------------------------------------
import matplotlib.pyplot as plt
import cv2
import numpy as np"""图像显示除了使用opencv,还可以采用matplotlib.pyplot
"""img = cv2.imread('000000005620.jpg', 1)
img2 = np.zeros_like(img, dtype=img.dtype)
# 将opencv读取图像的方式转化为plt读取图像方式--->
# BGR---RGB
img2[:,:,0] = img[:,:,2]
img2[:,:,1] = img[:,:,1]
img2[:,:,2] = img[:,:,0]print(img2.shape)
plt.imshow(img)
plt.show() 
RGB & BGR
