1. 圖檔加載、顯示和儲存

import cv2
# 生成圖檔
img = cv2.imread(r'C:\Users\Desktop\test1.jpg')
# 生成灰色圖檔
imgGrey = cv2.imread("1.jpg", 0)
#  展示原圖
cv2.imshow("img", img)
#  展示灰色圖檔
#cv2.imshow("imgGrey", imgGrey)
#  等待圖檔的關閉
cv2.waitKey(0)
# 儲存灰色圖檔
#cv2.imwrite("Copy.jpg", imgGrey)

2. 圖像顯示視窗建立與銷毀

cv2.namedWindow(視窗名，屬性) 建立一個視窗，屬性—指定視窗大小模式：

cv2.WINDOW_AUTOSIZE：根據圖像大小自動建立大小

cv2.WINDOW_NORMAL：視窗大小可調整

cv2.destoryAllWindows(視窗名) 删除任何建立的視窗

import cv2

# 生成圖檔

img = cv2.imread(r'C:\Users\Desktop\test1.jpg')

cv2.namedWindow("img", cv2.WINDOW_NORMAL)

cv2.imshow("img", img)

cv2.waitKey()

cv2.destroyAllWindows()

3. 圖檔寬、高、通道數擷取

img.shape 傳回圖像高（圖像矩陣的行數）、寬（圖像矩陣的列數）和通道數3個屬性組成的元組，若圖像是非彩色圖，則隻傳回高和寬組成的元組。

import cv2

img = cv2.imread(r'C:\Users\Desktop\test1.jpg')
imgGray = cv2.imread(r'C:\Users\Desktop\test1.jpg', 0)


print('****img*****)
print( img.shape)
print('width: ', img.shape[0])
print('heigh: ', img.shape[1])
print('channel: ', img.shape[2])


print('\n\n***imgGray**')
print(imgGray.shape)
print('width: ', imgGray.shape[0])
print('heigh: ', imgGray.shape[1])
print('channel: ', imgGray.shape[2])

4. 圖像像素數目和圖像資料類型的擷取

圖像矩陣img的size屬性和dtype分别對應圖像的像素總數目和圖像資料類型。一般情況下，圖像的資料類型是uint8。

import cv2

img = cv2.imread(r'C:\Users\Desktop\test1.jpg')

print('圖像類型： ', type(img))
print('圖像像素點數： ', img.size)
print('圖像像素灰階值類型：', img.dtype)

5. 生成指定大小的空圖像, 生成指定大小的空圖像

import cv2
import numpy as np

img = cv2.imread(r'C:\Users\Desktop\test1.jpg')
imgZero = np.zeros(img.shape, np.uint8)
imgFix = np.zeros((300, 500, 3), np.uint8)

cv2.imshow("imgZero", imgZero)
cv2.imshow("imgFix", imgFix)
cv2.waitKey()

6. 通路和操作圖像像素

OpenCV中圖像矩陣的順序是B、G、R。可以直接通過坐标位置通路和操作圖像像素。

import cv2
import numpy as np

img = cv2.imread(r'C:\Users\Desktop\test1.jpg')

pixel_50_100 = img[50, 100]
#傳回3個值，分别是該像素點在BGR通道的值
print(pixel_50_100)


img[50, 100] = (0, 0, 255)

cv2.imshow("img", img)
cv2.waitKey()

分開通路圖像某一通道像素值也very友善

import cv2
import numpy as np

img = cv2.imread(r'C:\Users\Desktop\test1.jpg')

img[0:100, 100:200, 0] = 255
img[100:200, 200:300, 1] = 255
img[200:300, 300:400, 2] = 255

cv2.imshow("img", img)
cv2.waitKey()

更改圖像某一矩形區域的像素值也很友善：

import cv2
import numpy as np

img = cv2.imread(r'C:\Users\Desktop\test1.jpg')
img[0:50, 1:100] = (0, 0, 255)

cv2.imshow("img", img)
cv2.waitKey()

7. 圖像三通道分離和合并

import cv2
import numpy as np

img = cv2.imread(r'C:\Users\Desktop\test1.jpg')


b, g, r = cv2.split(img)

# b = cv2.split(img)[0]
# g = cv2.split(img)[1]
# r = cv2.split(img)[2]


merged = cv2.merge([b, g, r])

cv2.imshow("Blue", b)
cv2.imshow("Green", g)
cv2.imshow("Red", r)

cv2.imshow("Merged", merged)
cv2.waitKey()

8. 抓取攝像頭

import cv2
import numpy as np

cap  = cv2.VideoCapture(0)

for i in range(0, 19):
     print(cap.get(i)) 

while(1):
    ret, frame = cap.read()
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
    lower_blue = np.array([100, 47, 47])
    upper_blue = np.array([124, 255,255])

    mask = cv2.inRange(hsv, lower_blue, upper_blue) #藍色掩模
    res = cv2.bitwise_and(frame, frame, mask = mask)

    cv2.imshow(u"Capture", frame)
    cv2.imshow(u"mask", mask)
    cv2.imshow(u"res", res)

    key = cv2.waitKey(1)
    if key & 0xff == ord('q') or key == 27:
         print(frame.shape,ret)
         break

cap.release()
cv2.destroyAllWindows()