"""
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
